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Beyond bordersGlobal biotechnology report 2012

To our clients and friends:

Welcome to the 26th annual issue of Beyond borders, Ernst & Young’s annual report on the global biotechnology industry.

Our analysis of trends across the leading centers of biotech activity reveals both signs of hope and causes for concern. The financial performance of publicly traded companies is more robust than at any time since the onset of the global financial crisis, with the industry returning to double-digit revenue growth. Companies that had made drastic cuts in R&D spending in the aftermath of the crisis are now making substantial increases in their pipeline development efforts.

But even as things are heading back to normal on the financial performance front, the financing situation remains mired in the “new normal” we have been describing for the last few years. While the biotech industry raised more capital in 2011 than at any time since the genomics bubble of 2000, this increase was driven entirely by large debt financings by the industry’s commercial leaders. The money flowing to the vast majority of smaller firms, including pre-commercial, R&D-phase companies — a measure we refer to as “innovation capital” — has remained flat for the last several years.

As such, the question we have posed for the last two years is more relevant than ever: how can biotech innovation be sustained during a time of serious resource constraints? In this year’s Point of view article, we offer a perspective that addresses not just the challenges in the changing health care ecosystem but also the latent opportunities. The paradigm we present — the holistic open learning network, or HOLNet — takes advantage of health care’s move to an outcomes-focused, patient-centric, data-driven future. HOLNets could fundamentally change how R&D is funded and conducted, by bringing together a diverse range of participants, encouraging the pooling of precompetitive data and permitting researchers to learn in real time from each others’ insights and missteps.

These are timely topics, and we look forward to exploring them with you — and helping each other learn in real time — through our Global Life Sciences Blog and other social media venues. Please look for information about the blog on ey.com/lifesciences in the months ahead and join the conversation. Ernst & Young’s global organization stands ready to help you address your business challenges.

Gautam JaggiManaging Editor, Beyond borders

Glen T. GiovannettiGlobal Biotechnology Leader

1 Perspectives1 Point of view

HOLNets: learning from the whole network

2 Focusing on what you do best• Bruce Booth, Atlas Venture

5 Collaborative innovation• David Steinberg, PureTech Ventures

7 More pharma spinoffs?• Ron Cohen, Acorda Therapeutics

8 Case study: Coalition Against Major Diseases (CAMD)• Marc Cantillon, Coalition Against Major Diseases

9 Case study: One Mind for Research• Magali Haas, One Mind for Research

10 Leveraging our strengths• Samantha Du, Sequoia Capital China

12 Making it happen: building collective intent care networks to change health care delivery• Sanjeev Wadhwa, Ernst & Young

15 Getting personal, getting networked• Christian Itin, Micromet

17 Partnering for specialization• John Maraganore, Alnylam Pharmaceuticals

20 Patient-centric innovationN. Anthony Coles, Onyx Pharmaceuticals

21 Protecting the biotech ecosystemMoncef Slaoui, GlaxoSmithKline

22 To boost R&D, stop flying blind and start observingJoshua Boger, Vertex Pharmaceuticals

25 Financial performanceRecovery and stabilization

27 • United States

32 • Europe

36 • Canada

37 • Australia

39 FinancingInnovative capital


51 • Europe

55 • Canada

59 DealsPharma recalibrates


69 • Europe

71 • Canada

73 Products and pipelinePromising signs

81 Acknowledgments82 Data exhibit index84 Global biotechnology contacts

Contents

Perspectives

1

Point of view

HOLNets: learning from the whole networkThe same old new normal

Over the last two years, we’ve written extensively about the global financial crisis and the “new normal.” This has mainly been a new normal for capital markets and financing, with implications for the biotechnology industry because of the capital-intensive nature of biotech R&D. Investors and companies have responded with creative approaches to make R&D more efficient and sustainable. They have tweaked the existing drug development paradigm (e.g., fail fast approaches) and/or made reductions in operating costs and overhead (e.g., asset-centric models, outsourcing, virtual business models). These efforts continued over the last year. We have even seen the emergence of some new models (e.g., pharma/VC strategic partnerships — more on these later).

However, these creative approaches are making only marginal improvements to a funding and innovation business model that, while under unprecedented strain in the current environment, has long grappled with basic tensions. Gary Pisano of Harvard University, for instance, has pointed out that intellectual property (IP) is highly fragmented in the biotech industry, in part because the murky and complex nature of IP and IP law makes companies unwilling to share. This inevitably wastes resources as companies duplicate efforts. In prior issues of Beyond borders, we have similarly pointed to the timing mismatch between the investment horizons of venture funds and drug development time frames. Such tensions did not matter much as long as investors were willing to put up the large sums of capital required to fund drug development, and as long as they could earn returns high enough to keep them coming back. In the new normal — as the era of easy money and high leverage has ended

and as numerous pressures have squeezed VC multiples — both of those preconditions have come under increasing strain. In the aftermath of the financial crisis, therefore, the tensions that have always existed beneath the surface have bubbled to the top. The underlying inefficiency and redundancy of drug development have become particularly incongruous in the current financing climate — an extravagance we can no longer afford. The solutions we’ve seen so far, while very creative and innovative, are largely tinkering around the edges — refinements and adjustments to a long-standing drug development model. They lead to incremental improvements in efficiency but are unlikely to change the numbers in a fundamental way.

What we need, more than ever, is a new paradigm — something that radically rethinks the ways in which scientific insights are gained and translated into new products, and which creates new ways of assembling resources to fuel this important endeavor. In this year’s Point of view article, we present one such solution, something we call holistic open learning networks. It’s an idea that builds on trends already visible in the market and, more importantly, involves learning from beyond the life sciences industry and leveraging the strengths of a diverse range of entities — from providers and patient groups to social media networks and data analytics firms.

For much of the past, learning from the outside has been a particularly acute challenge for big pharma, as the “not invented here” mentality led large companies to dismiss innovative ideas that did not originate from their own labs. Pharma companies paid a steep price for this closed mindset, as emerging biotech companies stole the lead in developing new generations of game-changing platforms and efficacious new products. Today, pharmaceutical companies have a more outside-in approach. Not only has big pharma come to rely on biotech for a significant portion of its pipeline, but pharma companies are also boldly experimenting with new business models to prepare for a future in which success will be determined by not just drug sales, but also the ability to demonstrably improve health outcomes. To develop these models, pharma companies are beginning to experiment with partnerships with other life sciences firms as well as a range of companies from other industries: health care providers and payers, information technology companies, mobile telephony providers, retailers and others. (For a deep discussion of pharma’s “Pharma 3.0” business model innovation, refer to the 2010–12 issues of our sister publication, Progressions.)

In many ways, it is now time for the drug development side of the industry (including biotech) to do the same. Even as the health care ecosystem around us is being completely reinvented in response to unsustainable increases in health costs, the drug development paradigm has remained essentially unchanged. To understand where the opportunities lie for reinventing drug development, let’s start by revisiting how health care itself is changing.

Point of view HOLNets: learning from the whole network

Even as health care is being completely reinvented in response to unsustainable increases in costs, the drug development paradigm has remained essentially unchanged.

2

Outcomes, technology and big data: the new ecosystem

Even as biotech adjusts to its new normal, we are in the midst of other seismic shifts in the health care ecosystem, all of which have implications — both challenges and opportunities — for companies in the business of drug development.

The shift is being driven by two trends that are occurring simultaneously. The first — the need to make health care costs sustainable — is driving payers to change incentives. Through a range of health care reforms across key markets, payers are focusing increasingly on health outcomes. Systems are shifting away from paying for products and procedures and toward paying for performance. This is playing out in multiple ways: comparative effectiveness research, prevention and disease management

programs, payment regimes that shift financial risk to providers and in some cases drug companies, and more. The bottom line for life sciences companies is that they will increasingly find themselves in the business of changing patient behaviors and delivering health outcomes rather than purely in the historic business of selling products.

Accompanying the increasingly urgent need to bring health care costs under control is the emergence of the second driver of change — an explosion of new technologies that have the potential to make health care delivery radically more efficient. Electronic health records, which have existed in concept for decades but never really gained much traction, are being used in larger numbers than

Beyond borders Global biotechnology report 2012

Focusing on what you do best

Bruce Booth, PhDAtlas Venture, Partner

The simple answer to sustaining innovation is that each player in the ecosystem should focus on what it does best.

Academics should focus on basic research and early biologic target validation. Start-ups, with experienced talent, unleashed from the constraints of big-company behavior, should experiment with lots of approaches for high-value, emerging targets: biological variables (e.g., different drug modalities such as NCEs, mAbs, peptides, antisense and RNAi), clinical variables (e.g., patient subtypes, new translational designs, repurposing and indications discovery), organizational variables (e.g., virtual CRO-enabled models vs. fully integrated teams) and business model variables (e.g., drug platforms vs. single-asset companies). We should let a lot of start-up flowers bloom. Some will grow, some won’t.

Venture capitalists — traditional and corporate venture funds along with alternative capital providers such as angel investors and philanthropic foundations — should strive to allocate resources to winning experimental start-up models. Importantly, these capital providers need to be disciplined about reducing the costly false positives in drug research and reallocate to new opportunities more efficiently.

Big pharma companies should participate in this diverse research ecosystem through “open innovation” strategies that pair up their deep capabilities (e.g., chemical libraries, biologics technologies) and creative partnering power with the agility, specific expertise, and passion of the start-up culture. As valuable, high-impact medicines emerge from this research ecosystem into the later stages of clinical development, big pharma should bring its balance sheet and unparalleled global development and marketing capabilities to successfully drive new drug approvals and commercial launches.

Sharing value across these various elements from target validation through product sales would help foster a vibrant, healthy ecosystem. Of course, this is all great in theory. Unfortunately, things such as legacy infrastructure, cultural differences, decision-making inertia, frictional costs, resource misallocation, misperception of risk, and winner-take-all mindsets conspire to make this efficient ecosystem a challenge. But that doesn’t mean we shouldn’t keep trying.

3

ever before, as policy makers increase incentives for adoption. Mobile health technologies have taken off in a big way, as an incredible variety of smartphone apps are empowering patients with more transparent information and a greater ability to monitor and manage their own health. Health-specific social media platforms have emerged, allowing patients and physicians to interact with their peers and with each other to discuss their progress and side effects — and learn from each other in real time. A sea of sensors — embedded not just in new generations of medical technology products but even in everyday objects such as mobile phones, weighing scales, running shoes, sportswear and wristwatches — are providing real-time feedback to patients and their caregivers, allowing for better management of health and a greater focus on prevention.

Since all of these technologies are generating massive amounts of data, a significant corollary of the changing ecosystem is health care’s move to the era of big data. We are already seeing dramatic increases in the amount of data being generated from numerous sources — genomic research, clinical trials, electronic medical records, wireless devices, smartphone apps and social media platforms, to name a few — with the volume expected to grow exponentially. The 1000 Genomes Project — an initiative to analyze large amounts of genomic data to find genetic variants that affect at least 1% of the population — has already built a data set that is 200 terabytes in size, the equivalent of 16 million file cabinets worth of text. Across the US health care system, it is estimated that the amount of data crossed the 150 exabyte threshold (150 billion gigabytes) last year. But big data is not just about more information. It’s also about more types of information (e.g., health records, medical claims data, social media threads, imaging data, video feeds, data from sensors) from more diverse sources. While drug development companies have always been steeped in a culture of data (indeed, their very success has depended on the quality of the clinical trial data they generate), in the era of big data, most of this information will be generated in real time, will be controlled by others and will cut across the value chain, from R&D to health care delivery.

In the 2010 issue of Progressions, we discussed how big data is driving a new trend with tremendous implications for drug companies. Payers and others are mining electronic health records and other data to identify correlations and make assessments about interventions and standards of care. This development — something we termed “value mining,” or the use of data mining to make decisions about the relative value of products and interventions — means that other entities are making decisions about drug companies’ products using data that is outside the control of these firms. Even more compelling, value mining is much quicker and cheaper than the way drug companies have traditionally gained insights about the value of medical products — the extended process of hypothesis testing through clinical trials.

To date, value mining has only happened at the commercial end of the value chain, to assess the value of marketed products. But what if the power of big data could be harnessed to similarly develop quicker, real-time insights about candidates in the pipeline? How much power could we unleash by connecting the dots between the huge volumes of data scattered across the ecosystem? How do we achieve this potential and who could take the lead? We think these are compelling questions, and we turn to them next.

Point of view HOLNets: learning from the whole network

What if the power of big data could be harnessed to similarly develop quicker, real-time insights about candidates in the pipeline?

4 Beyond borders Global biotechnology report 2012

Reinventing R&D: learning from the ecosystem

Over the last few decades, as the emergence of the modern biotechnology industry introduced new technologies to the drug development process, there has been considerable innovation in the capabilities used to conduct R&D. Combinatorial chemistry and high-throughput screening have brought industrial-scale processes to drug development by allowing for the automated generation and testing of enormous numbers of potential drug candidates. Pharmacogenetics and other personalized medicine approaches have created the potential for developing therapeutics that are vastly more targeted and efficacious on individual patients. Meanwhile, the emergence of bioinformatics brought with it the promise of bringing drug development into the information era, by enabling the use of computers for understanding disease mechanisms, predictive modeling, drug synthesis, testing and more.

Yet, despite these innovations, R&D productivity has not improved — drug approvals have not increased to any appreciable degree, while development costs have escalated. Indeed, the process of developing drugs has remained unchanged in several key respects. Despite the new technologies that have been introduced, drug development is still linear, slow, inflexible, expensive and siloed:

• Linear. Drug R&D is conducted in a stepwise manner. Through a series of preclinical studies and clinical trials in sequentially larger populations, researchers seek to answer questions related to safety, ef cacy and dosages.

• Slow. The process of taking a compound or molecule from early research to approved product takes well over a decade. In essence, researchers come up with an idea and then wait years to nd out whether it works.

• Inflexible. The drug development process is also very rigid. This is particularly tragic given the length of the process. Over months and years of trials, valuable information is being gathered. Yet, the double blinding of trials effectively means that researchers can only learn at a few points along the process — when the current phase of clinical trials is completed and the data analyzed. There is little ability to learn continuously and adjust one’s approach based on real-time information.

• Expensive. An inevitable consequence of this slow and in exible process is that drug development has become increasingly expensive. On average, companies spend well over US$1 billion to bring an approved drug to market (a number that includes the cost of products that fail along the way).

• Siloed. Lastly, the R&D process is highly fragmented. Driven by the need to protect their intellectual property, companies fail to learn from experiences and the mistakes of others.

Of course, there is good reason for much of this, including regulatory requirements that define the approval process and the fact that firms have always succeeded or failed on the strength of their intellectual property. But we can no longer afford to keep doing things this way, particularly in today’s resource-constrained, escalating-cost environment. Instead of a drug development paradigm that is linear, slow, inflexible, expensive and siloed, we desperately need one that is iterative, fast, adaptive, cost-efficient and open/networked.

We are already seeing examples that are taking us in this direction. As discussed extensively in the last two issues of Beyond borders, a host of new approaches are attempting to make drug development faster and more cost-efficient, from fail-fast R&D paradigms to asset-centric funding models that attempt to get to a value-creating proof-of-concept milestone with minimal overhead. To make R&D more fast, iterative and adaptive, there has been a growing focus on adaptive clinical trials. In one particularly noteworthy example, the I-SPY2 trial, three drug companies are collaborating to screen multiple breast cancer drugs, each targeting a different pathway. The trial has an adaptive design under which patient outcomes are immediately used to inform treatment assignments for subsequent trial participants. The trial designers claim that I-SPY 2 can test new treatments in half the time of standard trials, at a fraction of the cost and with significantly fewer participants. Meanwhile, we’ve seen several examples of more open approaches, from an uptick in precompetitive collaboration to GlaxoSmithKline’s contribution of intellectual property for neglected tropical diseases.

To take such efforts to the next level, we now need mechanisms for breaking down silos more broadly. We need processes for sharing information and learning from the ecosystem in real time. We need to move to a world in which the division between the R&D and commercial ends of the value chain becomes increasingly meaningless because scientists and practitioners are continuously gaining insights from data being generated across the value chain and throughout the cycle of care. To achieve all of this, we propose the widespread use of holistic open learning networks (HOLNets).

The four characteristics embedded in this moniker don’t just define HOLNets — each one of them is also a critical requirement for the success of this approach:

• Holistic. The HOLNet approach represents a vastly different and inclusive approach to R&D. The boundaries between drug development, product commercialization and health care delivery are blurred. Rather than being con ned to the traditional siloed and sequential approach to drug development, HOLNets would share data and connect dots across the entire value chain of companies (from early research to marketing) and cycle of care of patients (from prevention to cure).

• Open. One of the biggest changes in the HOLNet approach is openness. While the speci c rules of each HOLNet will depend on the needs and preferences of its members, these networks will typically require that members pool their strengths and assets (e.g., talent and precompetitive data). They will also involve sharing any resulting output (e.g., creating open standards, making insights available to all members and often to non-members as well). This is one of the most powerful aspects of a HOLNet, since it has the potential to make R&D radically more ef cient and productive, by reducing redundant expenditures and allowing researchers to learn from each others’ insights and mistakes. But in an industry where companies have historically operated under shrouds of secrecy, this is also one of the biggest obstacles to the adoption of HOLNets by life sciences rms. Consequently, HOLNets will need to address intellectual property concerns by clearly de ning precompetitive information that is available for sharing as opposed to information that is proprietary. It is encouraging that the term “precompetitive” is being used more broadly in recent years, as companies grow willing to collaborate in areas once considered sources of competitive advantage. But we believe that the notion of the precompetitive space will have to expand even further, changing to some extent the very basis of competition. For example, while it is entirely appropriate for companies to compete based on the effectiveness of molecules they discover, is it essential that they compete on all underlying technologies (e.g., biomarkers) and even on processes such as clinical trial enrollment? Companies are growing increasingly comfortable with the notion of collaborating with competitors, and as we’ll see later, early examples of networks that are taking open approaches to intellectual property have had no problem attracting large and small life sciences members.

• Learning. Above all, HOLNets are about learning — their raison d’être. But while learning in the drug development process has historically been slow, sequential and siloed, HOLNets are about learning rapidly, in real time, by connecting data from across the ecosystem. Real-time learning allows constituents to quickly adjust their approaches — from clinical trials to standards of care — saving time and money and increasing success rates. But to learn from big data, we need standards that allow data to be combined as well as sophisticated analytics to mine insights — capabilities that HOLNets will need to enable and foster.

• Network. Last, but not least, a HOLNet has to be a network. Radically reinventing R&D and unleashing the transformative potential of big data requires the participation of diverse players from across the ecosystem. The network needs a common goal — a collective intent — around which all its members are aligned. Different entities don’t all need to do the same thing — indeed, given their diverse backgrounds and strengths, it would be better if they didn’t — but they do need to be pulling in the same direction. The optimal network size and participants will depend on the challenge being addressed.

5Point of view HOLNets: learning from the whole network

Collaborative innovation

David SteinbergPureTech Ventures, Partner

To sustain innovation, we could do two things. First, let’s reduce redundant research. There’s no reason every pharma has to study fundamental biology in every research area, wasting hundreds of millions of dollars in the process. Academics, NIH, pharma and entrepreneurs should work together to explore new biology areas and get them “drug development ready.” Pharma and biotech can access the assays, probes, etc., and do their own drug development. Second, let’s parallelize biotech entrepreneurship. Typically, solo entrepreneurs work for two years and then pitch to VCs, who then pivot, work for two to three more years, and pitch to pharma, who then discard all but the one program of interest. Let’s get entrepreneurs, VCs and pharmas working together, at the same time, to start and fund biotech start-ups around a common vision.


HOLNets in action

When all of this comes together — when an initiative is a truly holistic, open, learning network with a diverse set of stakeholders — it has the potential to tangibly transform the ways in which insights are gathered and new drugs developed. In practice, a HOLNet could play a critical role in:

• Pooling data. Because of their charter to be open and learn by connecting diverse data sets, HOLNets can enable the pooling of data in precompetitive spaces. This becomes particularly compelling given their diverse membership, since these networks could bring together genetic data from patients, claims data from payers, outcomes data from providers’ EHR systems, data on failed clinical trials from life sciences companies, insights from disease foundations and more. They can create common pools for their members (and perhaps non-members) to draw from, including shared libraries and tissue banks.

• Creating standards. The pooling of data raises a corollary question: standards. This is another area where HOLNets can play a much-needed role. After all, data sharing means nothing unless data can also be combined and studied holistically. Without uniform standards and the ability to collectively analyze this information, pooled data is not big data — it’s just a collection of smaller data sets. Developing standards will also play a big role in accelerating the creation of promising R&D tools, such as biomarkers and disease models. And once again, by putting these standards, assets and insights into the public domain, a HOLNet can help make drug R&D vastly more productive and ef cient across the breadth of the ecosystem.

• Engaging regulators. As articulated earlier, much of what life sciences companies and other health care entities do is de ned by regulatory regimes. To truly unleash the potential of the HOLNet approach, it will be essential that regulators adapt to a world in which insights can be gathered in real time through more exible approaches. As entities that represent a broad coalition of partners — often focusing on diseases that are becoming high priorities for policy makers — HOLNets will have the credibility to engage with regulators and/or to encourage new approaches to R&D and clinical trial design. The good news is that regulators recognize the need to move in this direction. Senior leaders from the FDA, for instance, have gone on record encouraging experimentation, and there is at least one compelling example of a exible, learning clinical trial paradigm — the I-SPY2 trial discussed earlier.

• Engaging patients. But regulators are not the only entities with which HOLNets will engage. The new ecosystem is, in essence, a patient-centric world, and HOLNets will need to engage with patients by identifying relevant populations (perhaps with the assistance of disease foundations), developing ongoing relationships with them and collecting their data with their informed consent. This has the potential to enable better outcomes through an increased focus on prevention and health management, but it also has tremendous bene ts for drug R&D. Based on these ongoing relationships and a deeper understanding of patients’ real-world experiences with their conditions and medications, HOLNets can provide new insights for the drug development process. In addition, it may be possible to substantially speed up clinical trial enrollment. The existing paradigm of clinical trials — in which a hypothesis is articulated rst, a trial protocol is developed next and only then do researchers start looking for appropriate patients to enroll — can be turned on its head. A world in which HOLNets have existing patient relationships and databases with comprehensive information — including contact information, genetic pro les, conditions, disease states and prior treatments — is one in which patients have in essence been pre-screened. With patients already identi ed (and perhaps consent to participate in trials obtained in advance) appropriate individuals can quickly and easily be enrolled once a suitable trial comes along.


To achieve their full potential, HOLNets will need an organization at the center to orchestrate all these activities and to balance the needs and priorities of members. The organization needs dedicated human resources, which could be a combination of full-time employees and talented individuals on secondment from member organizations.

We are seeing examples that do much, but not all, of this. At the R&D end of the value chain, the charge is being led by disease foundations and other nonprofits, often focused on brain diseases. For instance, the Alzheimer’s Disease Neuroimaging Initiative (ADNI), an early example of this sort of collaboration, was set up in the early 2000s to identify biomarkers that show the progression of Alzheimer’s. The initiative — a public-private-partnership with funding from the National Institutes of Health as well as private partner support from various companies and associations — deliberately took an open approach to information. All data coming out of its studies are immediately released to the public over the internet. NewDrugs4BadBugs, a new European initiative to combat antibiotic-resistant bacteria, is bringing together several entities, including the Innovative Medicines Initiative, GlaxoSmithKline, Sanofi, AstraZeneca, Janssen and Basilea. The initiative plans to share data openly, develop better networks of researchers and create more fluid trial designs. Two other initiatives in the neuroscience space — One Mind for Research and the Coalition Against Major Diseases — are profiled in greater depth in the accompanying articles by Marc Cantillon and Magali Haas on pages 8 and 9. These initiatives and numerous other examples — the CommonMind Consortium, the Biomarkers Consortium, the Structural Genomics Consortium, the Multiple Myeloma Research Consortium and others — are seeking to assemble a diverse network of actors to pool data, develop common standards and accelerate research, often with the requirement that data and insights be shared openly.

More pharma spinoffs?

Ron Cohen, MDAcorda Therapeutics, President and CEO

We’re already seeing the ecosystem trying to adapt to the challenge of sustaining innovation. For example, some VCs are now emphasizing single-product plays, designed to be advanced to a value-creating clinical endpoint with minimal infrastructure and cost, relying heavily on outsourcing to CROs and with the aim of selling to a pharma company once milestones are attained. Some are entering into funds together with pharma companies to leverage both capital and expertise — though this may not be truly novel, since many pharma companies have had their own venture arms for years. In the recently announced partnership between Johnson & Johnson, GlaxoSmithKline and Index Ventures, the pharma companies will get a first look at early-stage projects funded by the Index fund. Sanofi and Third Rock Ventures have an arrangement that is focusing on single product plays. Several pharma companies are trying to inject a biotech-like risk-taking ethos into their discovery/development programs, by creating smaller, more focused units, often with a mandate to partner with outside academic and biotech groups as needed (e.g., GlaxoSmithKline’s Discovery Performance Units).

One could imagine more variations. Pharma might actually create mechanisms for some of its talent to propose ideas for spinoff companies based on ideas or products in development, giving the pharma right of first offer after certain milestones are attained. The companies could be funded by the pharma company or in partnership with a VC fund.

continued on page 10

When all of this comes together — when an initiative is a truly holistic, open, learning network with a diverse set of stakeholders — it has the potential to tangibly transform the ways in which insights are gathered and new drugs developed.

Marc Cantillon, MD Former Executive Director and R&D Consultant

Case study

Coalition Against Major Diseases (CAMD)


Behavior originates in needs and signals from the environment. So my decision to be a founding member of the Coalition Against Major Diseases (CAMD) in 2008 was guided by my needs. At the time, I was head of neuroscience clinical development at Schering-Plough and was seeking a neutral venue for the precompetitive sharing of development tools. As a collaborative effort to accelerate the translation of scientific discoveries into treatments, CAMD — a part of the Critical Path Institute — provided such a venue. The coalition, which focuses on diseases in which the efforts of individual pharma actors have made little headway, took on Alzheimer’s disease (AD) and Parkinson’s disease (PD) as its first challenges.

CAMD members are scientists from pharma, biotech, universities, government organizations (e.g., FDA and NIH) and patient/voluntary health organizations. All members must abide by a uniform charter, which requires them to share data and contribute time and energy. To avoid even a perceived conflict of interest, CAMD doesn’t accept money from the pharma industry, relying instead on competitive grants. A uniform charter requires that any IP developed by the consortium is shared — creating a pool of knowledge and assets that could truly accelerate R&D — while allowing members to protect material that they developed independently of their collaborative efforts. Yet, IP concerns have in no way hampered the ability to attract life sciences members. To the contrary, these companies see a net benefit from joining. The advantages of being a member of CAMD span the three areas in which the coalition is focused: data sharing, disease modeling and biomarkers.

• Data sharing. CAMD, working with the Clinical Data Interchange Standards Consortium, has done groundbreaking work in creating common AD data standards — something no company could achieve alone. Indeed, different standards even within companies prevented rms from combining their own clinical trials, much less those of multiple entities, in a common database. For instance, there was no consistent way of recording answers to questions on memory, recall, etc., that are part of the Alzheimer’s Disease Assessment Scale-Cognitive subscale (ADAS-cog, the main benchmark for measuring outcomes). In June 2010, CAMD solved this problem when it created a standard database combining the placebo arms of members’ Alzheimer’s trials. Data sharing and common standards could drive faster drug development and faster review by the FDA. Today, we are in the early stages of an explosive increase in the amount of health data, and it’s happening faster than most people probably would have anticipated. But again, unless these data are collected in a standardized way, their true potential will not be realized.

• Disease modeling. Standardizing and sharing data will allow for the development of disease models to understand differences in progression in different categories of patients (e.g., by age, ethnicity and medication). This does not need to be limited to traditional research settings. With large volumes of secure anonymized data, there’s no reason we couldn’t use these assets to better understand when memory problems begin, identify early warning signs and track the course of the disease — which could help develop new treatments and also boost prevention. To be used in the regulatory context, these disease models need to be widely accepted. It can be a tough sell for a drug company to get the FDA to accept proprietary disease models when the agency hasn’t had a say in vetting these models. But all of that changes in a coalition like CAMD, where the FDA is a member and actively involved in developing disease models.

• Biomarkers. Biomarkers have tremendous potential for helping us understand disease mechanisms and subtypes and selecting patients in clinical trials. Once again, we need standards — biomarkers that are validated, standardized and quali ed for use — and a single company will have less credibility and resources to establish standards than a collaborative effort.

Approaches such as CAMD are not just for large pharma; they are equally relevant and useful for R&D-stage biotech firms. While small companies may sometimes see biomarker identification as a source of competitive advantage, the truth is that they stand to benefit from establishing standards in such areas. In addition, members can gain early access to the FDA — potentially working to create review standards and gaining early visibility into standards as they are being created. For too long, our industry has resisted sharing. Today, we are seeing a rethinking of where companies should compete and where they might join forces. Collaborations such as CAMD can be critical in sharing data, establishing standards and accelerating the development of much-needed cures.

Magali Haas, MD, PhDIncoming Chief Science & Technology Officer

Case study

One Mind for Research


One Mind for Research was founded by Patrick Kennedy (son of the late Senator Ted Kennedy) and Garen Staglin (co-founder of the International Mental Health Research Organization). They launched the One Mind Campaign on 25 May 2011, the 50th anniversary of President John F. Kennedy’s famous “moon-shot” speech.

One Mind’s mission is to accelerate neuroscience research so that, within a decade, all humanity can experience a lifetime free of brain disease. Like President Kennedy’s moon shot, this is a bold, audacious goal, but we feel that without an ambitious target, we will not get the urgency, resources and alignment that’s needed.

A collaborative approach is critical for this challenge. The brain is the most complex organ in the human body and also one of the most inaccessible. To date, neither academia nor the pharmaceutical industry has fully understood the mechanisms of the brain. We will need the holistic involvement of all stakeholders — industry, governments, patients, academic organizations, advocacy groups — each of which holds a piece of the puzzle.

Historically, the level of investment in brain research has not been proportionate to the burden this disease imposes on society — something we are only starting to appreciate. Last year, for the first time, the European Brain Commission estimated the aggregate burden imposed by 19 brain disorders on that society. The total they came up with was a staggering US$1 trillion. For the first time, Europe recognizes that this is the number one priority for their health care agenda.

We have yet to do such a comprehensive assessment in the US, where we still look at brain disorders disease by disease instead of thinking of the brain as one organ system. However, a preliminary independent study conducted for the US came up with a similar estimate for the economic burden in this country.

When you add to that the social stigma still associated with these conditions, one can appreciate why we haven’t focused on how burdensome brain disorders are and how much the loss of mental capital constrains our society.

Compounding the challenge, we are now seeing a reduction in investment in brain research. Investors have become frustrated by relatively low returns on investment, driven by the poor understanding of brain disease mechanisms and the inability to translate basic science to advance the drug pipeline.

To really change things, we have to change the way we work. That is what One Mind is attempting to do, by gathering resources, aligning stakeholders, prioritizing an agenda, promoting a culture of sharing, transforming public policy and eliminating stigma. We see ourselves as a central trusted third-party organization whose single mission is to accelerate the development of preventions and cures and eliminate the silos that have slowed our progress.

We are going about this in three ways. First, we are raising awareness about the impact and burden of these disorders. This is critical for building public support among policy makers and the public and making brain disorders a top priority on the health care agenda.

Second, we are seeking to de-risk the model to stimulate investment. To do this, we will need to accelerate research by generating a knowledge base across disorders, understanding mechanisms of action, conducting large-scale trials, identifying biomarkers and developing disease models. All of this requires combining data from various stakeholders — not just clinical trial data, but also real-time information from patients about their conditions.

Third, we are trying to alter the policy landscape. This encompasses everything from incentive models to motivate cooperation and sharing, to regulatory constructs, IP patent constructs and more. These are all issues that need to be systematically addressed.

Our corporate partners are essential to this effort. It will take the combined capabilities of companies from numerous industries — pharma, biotech, information technology and others — to advance this field. Depending on their strengths, companies can contribute different assets — data, platforms, imaging capabilities and, of course, financial investments. We hope that many companies will allow representatives from their organizations to work with us in workshops or even do rotational fellowships with us.

The One Mind model is every bit as relevant for early-stage R&D companies, and we have a number of small biotech companies as members. At a time when the FDA is revising its guidelines for medical device companies and biomarker platforms, companies in these areas need evidence that their platforms provide valid clinical insights. This typically requires larger studies than small companies can afford. But in this cooperative model, small companies can test their platforms against the large datasets, which is far quicker and more cost-effective than if they tried to generate their own large datasets. Similarly, a small therapeutic company will benefit from the disease models One Mind is building, which will allow them to pursue personalized medicine approaches more efficiently.

One Mind is already reshaping the boundaries between competitive research and precompetitive collaboration. For example, we are developing disease models that we plan to put into the public domain. Not too long ago, this was an area where companies would have wanted their own unique IP protected models. To accelerate the development of new cures, such shifts are long overdue.


One organization that is playing a central role in driving for more open drug development is Sage Bionetworks, a Seattle-based nonprofit organization that was founded in 2009. One of the organization’s first initiatives, the Sage Commons, has created an “open source community where computational biologists can develop and test competing models built from common resources.” The Sage Commons platform allows for integrating large data sets from various health ecosystem constituents and making them freely available for genomics analysis and predictive disease modeling.

Earlier this year, Sage announced the creation of Portable Legal Consent (PLC), a potentially game-changing standard that reverses the way in which consent is typically obtained from patients. Anyone participating in a clinical trial or having their genome sequenced would now have the option of making their data available to any researcher who accepts the terms of the PLC approach (including the requirement that any discoveries from this data must also be put in the public domain). The data is anonymized and Sage has gone to considerable lengths to make sure that consent is truly informed (e.g., through online tutorials that cannot be bypassed). With PLC, researchers would save time, because they do not have to obtain consent from subjects every time they initiate a new study, while patients could have greater confidence that any use of their data will comply with a standard set of rules. Perhaps the most promising implication of the PLC approach, though, is that having a widely adopted standard for consent could allow for data sets to be combined and analyzed in aggregate — unleashing the power of big data.

At the same time, we are also seeing examples at the other end of the value chain — health care delivery. For instance, Sanofi has recently partnered with the Baltimore County Department of Aging, the John A. Hartford Foundation and the National Coalition on Aging on a pilot program to help doctors connect older diabetics with evidence-based education and wellness support. Merck & Co. has partnered with the Camden Coalition of Healthcare Providers to create the Camden Citywide Diabetes Collaborative to implement comprehensive diabetes prevention and management programs in the city of Camden, New Jersey. Similarly, Eli Lilly and Company is partnering with Anthem Blue Cross Blue Shield and five Indiana-based health care providers to achieve better health outcomes for diabetes patients. (For more on how collaborative network approaches are transforming health care delivery, refer to the article by Sanjeev Wadhwa on page 12.)

Many of these initiatives — at both ends of the value chain — have key aspects of HOLNets. They are networks that bring together a diverse set of actors. They are often open, insisting that information be shared openly to facilitate greater learning. For the most part, though, they are not holistic, in that they are still confined to traditional definitions of R&D and commercial delivery.

Over time, we believe there is a case for more of these initiatives to expand across the value chain, to truly unleash the power of data being generated throughout the ecosystem. In particular, as discussed below, we think that pharma companies could play a big role in driving the widespread adoption of these networks.

Leveraging our strengths

Samantha DuSequoia Capital China, Managing Director

By leveraging our strengths, biotech firms, investors and pharma companies can effectively increase R&D productivity and efficiency. Biotech’s strengths are its entrepreneurship, operational efficiency (much less bureaucracy) and focus, while pharma can contribute high-quality late development and commercialization excellence. Biotech start-ups need to think very early about partnering with pharma companies to access their domain expertise. Investors will continue to be critical in today’s challenging business climate. For a resource-constrained biotech start-up, it is crucial to work with investors that can provide not just capital but also appropriate knowledge and

networks. Lastly, non-dilutive capital from governments and foundations can be very helpful in today’s resource-constrained environment.

A key part of the solution will be robust and relevant regulatory regimes. In a highly regulated industry such as ours, regulators (e.g., the FDA, EMEA and SFDA) are key ecosystem stakeholders. Without efficient and progressive regulators, no amount of effort from biotech and pharma will change the productivity and capital efficiency of the drug development model.


Getting there

While the HOLNet is a compelling vision of a future state that could make drug development vastly more efficient and productive, it has always been easy to imagine utopian health care systems. The challenge in this business is inevitably in how we get there. The health care ecosystem is so complex and intertwined — with so many competing constituencies and interests — that aligning incentives and structures is no mean task.

The good news is that health care has never been more primed for this sort of collaborative approach. The unprecedented pressures that many of its denizens now face — from payers wrestling with runaway costs and rapidly aging populations, to big pharma’s pipeline challenges, to emerging biotech startups and investors grappling with a strained innovation model — are starting to change mindsets and dismantle long-standing barriers. This is being further catalyzed by changing incentives, new technologies and new sources of data — all of which play a key role in driving the shift to HOLNets.

Now, more than ever, the approach we describe above is feasible because it is in the self-interest of the entities that would need to be part of it:

Big pharma

We think that the pharmaceutical industry is well positioned at this point in time to play a major role in making this approach more mainstream and widespread, for several reasons. For pharma companies, the biggest challenge, of course, is the patent cliff over which they are now plunging and the fact that their pipelines are not robust enough to fill the significant revenue gaps that will inevitably follow.

Pharma companies have been reacting to these challenges by restructuring and sharpening their strategic focus. As it becomes increasingly clear that companies cannot do everything, everywhere that they have in the past, pharma firms are evaluating which diseases, product segments and geographic markets are most strategic for them — leading companies to sell or spin off entire divisions while moving more aggressively into other segments.

As their strategies move in different directions — against a backdrop of an ecosystem where innovation is under pressure — pharma companies recognize that it is in their strategic interest to sustain a robust ecosystem of innovative biotech companies and investors. It is not surprising, therefore, that we have seen a dramatic uptick in transactions in which pharma companies are partnering with VCs to send more capital in directions that are strategic to them. In the last few months alone, we have seen such partnerships between Shire and Atlas Venture (to invest in rare diseases), GlaxoSmithKline, Johnson & Johnson and Index Ventures (targeting early-stage investments), Merck and Flagship Ventures and others.

But the ripple effects of pharma companies’ patent expirations extend beyond their walls. As more and more products become subject to generic competition, pharma will have less aggregate capacity to engage in activities such as corporate venture capital, strategic alliances and M&A transactions — all of which have provided a continuing source of funding for biotech companies even as financial investors (VCs and public markets) have become more stringent. For this year’s Beyond borders, Ernst & Young’s Transaction Advisory Services professionals have built a model to estimate the reduction in big pharma’s “firepower” to support the innovation ecosystem. By our calculations, the capacity of the top 28 biopharmaceutical companies has already declined by about 30% between 2006 and 2011. Much of pharma’s remaining capacity will also be targeted for building their presence in higher-growth emerging markets, rather than supporting innovation in mature ones. With more patent expirations ahead, and continuing pressures from investors (who expect continued high dividends and stock repurchases), we don’t anticipate that this situation will appreciably improve in the foreseeable future.

continued on page 14


Making it happen: building collective intent care networks to change health care delivery

Sanjeev WadhwaErnst & Young

While holistic open learning networks (HOLNets) have the potential to reinvent drug R&D for biotech and pharma companies — making drug development more efficient and productive and enabling real-time learning — these networks also have tremendous potential to reinvent both the delivery of health care and the ways in which drug companies go to market (their commercial models). After all, HOLNets are holistic by definition, and as already articulated, they are expected to make old demarcations, such as the distinction between the R&D and commercial phases of product development, increasingly irrelevant. And, in a construct that is open by design and built for real-time learning, it stands to reason that there would be opportunities for health care delivery to benefit from these networks as well.

In other spaces, we have discussed the need for “collective intent care networks” (CICNs) that would bring together providers, payers, pharmacies, academic medical centers, pharmaceutical industry researchers and non-traditional partners to deliver health care in more patient-centric and outcomes-driven ways. CICNs will be jointly accountable for delivering improved health outcomes and will align the behaviors of all participants around outcomes through financial and other incentives. These networks will transform health care delivery by increasing patient engagement, enabling remote health monitoring, expanding access and building prevention into care.

CICNs are similar to HOLNets but with a focus on care delivery. To realize their full potential, CICNs need to follow the four basic principles of HOLNets, by being holistic in scope, being open by design, encouraging real-time learning and building a network of diverse participants. In fact, we expect that, even though such a network starts with participants from the health care delivery end of the value chain, over time it would find benefits in expanding to include a more holistic set of participants, and would in turn deliver benefits across the ecosystem.

The move to such networks is being driven, of course, by the increasingly urgent need to make health care costs sustainable — manifested in developments such as the passage of the Patient Protection and Affordable Care Act in the US and the move toward comparative effectiveness research in several major markets. These trends are fundamentally changing health care delivery. Payer incentives (and hence provider behaviors) are driving the move to patient-centric health care organizations that are fully aligned around patient outcomes and value.

Achieving better patient outcomes will, in turn, require that providers get closer to patients and build long-term relationships with them. Over time, we will move to a paradigm in which patients enroll in lifelong protocols of care with specific payers and/or providers. Having such enduring relationships will be critical for improving health outcomes, since they will enable an increased focus on preventive care and allow all stakeholders to take a more holistic view of patients’ health and diseases.

In the next decade, patient-doctor relationships and health care delivery will be radically different from how they are today. We will move from a world in which care is delivered in just two types of locations (hospitals and doctors’ offices) to a paradigm in which care is delivered in the communities where patients live. The emphasis will move toward virtual care and remote health delivery with the majority of patients using integrated CICNs staffed by collaborative teams of drug researchers, clinical development scientists and health care providers. Seeking to provide better care at lower cost, primary care teams will join with community partners to address factors that affect a community’s health. To achieve the triple aim of health care initiatives (i.e., enhancing patients’ experience of care, reducing per-capita health care costs and improving population health) patient-centricity will inevitably need to be transformed into community-centricity. Advanced knowledge technologies, along with multi-comorbidity epidemiology, behavioral interactions, ethnographic commercial interventions, predictive patient profiles (“health avatars”) and disease opportunity maps identifying undiagnosed patients will allow people to take over many functions of primary care for themselves.

As already articulated in this year’s Point of view article, HOLNets promise to make drug development vastly more efficient and productive, by allowing for R&D paradigms that are adaptive and have the ability to learn from real-time data and the insights and missteps of others. But such networks also provide opportunities for payers and providers to learn from real-time data. By connecting the dots between datasets that are currently owned by individual entities, these networks will provide better information on benefits, risks and relative effectiveness of new therapies. They will enable greater access to affordable treatments and more effective ways to measure unmet needs.


Drug companies can play a relevant role in CICNs by adopting communities with the goal of improving health outcomes, often within a specific disease. BMS, for instance, launched a program in South Africa called Secure the Future to support the development and evaluation of cost-effective, sustainable and replicable models for providing care and support to people living with HIV/AIDS in Africa. The program sought to supplement the half hour of care that patients received at the clinic with “23 ½ hours” of disease management, and ongoing support was provided in patients’ homes and communities. Similarly, the Merck Foundation has committed US$15 million to fund the Alliance to Reduce Disparities in Diabetes, a public/private partnership encouraging evidence-based collaborative approaches to improve care, improve health outcomes and reduce care disparities in low-income, underserved populations in Camden, New Jersey. This approach will have implications for the commercial models of drug companies. Successfully launching products in such networks will require an altogether different focus on understanding and articulating the value proposition to a community of patients and the network of participants.

Building a network of this magnitude, and with this much disruptive potential, is no trivial task. For organizations interested in moving in this direction, a good starting point might be to create disease networks which leverage the creative models that many health care systems are now piloting — from

accountable care organizations and patient-centered medical homes in the US to primary care trusts in the UK. By focusing on outcomes, patient-centric approaches and preventive care, such programs already provide some of the key building blocks of a HOLNet approach. HOLNets could supplement such models by bringing a broader spectrum of constituents from across the ecosystem. They could also bring a disease-specific focus and, more important, create a bold collective intent to cure or radically improve outcomes within that disease.

At Ernst & Young, we are actively engaging with a broad spectrum of health care stakeholders to build CICNs. People see the need for change and recognize the tremendous transformative potential of a holistic network approach.Getting there won’t be easy, but we’re moving in the right direction. Stay tuned.

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Despite these pressures, pharma companies are acutely aware that more needs to be done to sustain the ecosystem of innovative emerging companies — not least because their own future growth depends on it. This is a subject that large companies are giving serious consideration. How can they do more to boost R&D productivity and support the ecosystem of emerging companies at a time when their own resources are growing relatively constrained?

One solution that has been proposed by some industry veterans is that pharma companies should band together to create a fund to purchase biotech IPOs. In the 9 January 2012 issue of BioCentury, for instance, Moncef Slaoui, John Maraganore and Stelios Papadopoulos argue that such an approach could validate companies and their approaches for other investors and give a boost to the market for biotech public offerings. (For more on this approach, see the article by Moncef Slaoui on page 21; John Maraganore’s views on making R&D more sustainable and productive can be found on page 17.) While this is certainly an innovative idea that might be worth trying (assuming that governance and other challenges could be appropriately addressed), it is not clear that catalyzing several more IPOs every year would be sufficient to truly address the strains on biotech funding and the overall drug innovation model.

More important, pharmaceutical companies have much more to offer than just financial capital. Even more valuable than funding are the other assets that pharma could contribute — data, knowledge (including valuable lessons about what has not worked) and human capital. If each large pharma shared some of these assets and allocated a tiny fraction of what it spends each year on in-house R&D to set up a HOLNet with other constituents around a particular area of interest, it might well have more impact on the efficiency and economic return of drug development than a business-as-usual approach. Pharma companies that take the lead in establishing

HOLNets could also benefit by attracting the most innovative biotech and academic collaborators. This would represent a clear departure from the current business development model, which is focused on securing technology/product rights and maintaining control of key decisions and data.

In Progressions, we talk about the challenge that pharma companies face when trying to serve as “aggregators” in their experiments with outcomes-focused approaches and partnerships. Pharma companies are often viewed with suspicion in these coordinating roles because they are perceived to have several conflicts of interest in the outcomes business (e.g., increasing the use of generics and focusing on prevention could save health systems large sums of money but would cannibalize pharma product sales). But HOLNets are an area where they could play a central role in developing a new business model, while establishing their credibility by contributing their own assets, bringing together a wide range of participants (including, where appropriate, competitors) and setting up rules for open sharing and access. Unlike their experiments with outcomes-focused business models, this would be much closer to their traditional business of drug development. It would also be consistent with their corporate missions’ focus on bringing meaningful new medicines to patients. And the payoff could be bigger: a way to truly jump-start innovation, accelerate the development of new products and improve health care delivery. By embracing and developing HOLNets, pharma companies would be helping themselves, helping the ecosystem of emerging biotech companies and, ultimately, helping patients.

Pharmaceutical companies have much more to offer than just their fi nancial capital.


Biotech companies and investors

As we’ve been discussing in these pages for the last few years, the biggest challenge for biotech companies and their investors is sustaining innovation at a time when the long-standing business model for investment and R&D is under unprecedented strain. Sustaining innovation will inevitably involve some combination of drastically reducing development costs and time frames on the one hand and significantly boosting pipeline output on the other.

These pressures have led to much soul-searching by biotech leaders and investors. Already, we have seen challenges to long-established ways of operating and increasingly creative approaches to partnering, financing and conducting R&D that attempt to adjust the risk/reward equation. Yet, these initiatives are not enough — even in aggregate — to truly make the biotech innovation model sustainable and fuel the leaps in productivity and efficiency that are needed.

Against this backdrop of challenges, companies and investors are more likely to be receptive to new approaches than at any point in the industry’s past, and HOLNets have many advantages for biotech companies as well. As part of such a consortium, biotech firms could contribute their own innovative strengths but, importantly, would also gain insights from other members, including into previously unsuccessful approaches for target selection, clinical trial design and the like. In addition, biotech firms may gain access to regulators in a way that an individual company would be unlikely to achieve — in effect getting an early view at new standards as they are being developed and even playing a role in shaping them.

Getting personal, getting networked

Christian Itin, PhDMicromet, Former President, CEO and Director

As demographic trends and increasing prosperity increase health care costs, innovators need solutions that truly address underserved medical needs while also reducing overall costs. To do this, constituents across health care will need to avoid unnecessary treatments — making personalized medicine approaches increasingly relevant. Yet, biotech and pharma companies face several challenges in accomplishing this goal. For most diseases, we lack diagnostic markers for selecting appropriate patients. The economics are challenging, with smaller market segments, clinical trials and ongoing post-approval commitments to ensure safety.

To truly achieve the potential of personalized medicine, we will need more collaboration. We are in early days of identifying molecular biomarkers correlated with disease progression and outcomes. Today, the search for biomarkers in clinical trials and development of companion diagnostics is done by individual companies. But to really succeed, we need larger databases and uniform standards. Creating this knowledge base systematically for all key disease areas is a huge undertaking in terms of scope, time and resources and can only be tackled through a broad common effort. Payers, pharmaceutical companies, regulators and clinicians have a common interest and will need to work together to generate such data sets, building on initiatives under way in the US and Europe. Policy makers may need to create stronger incentives for biomarker studies. We will need strong protections for patients’ privacy and other rights. It will be critical to get a broad spectrum of entities to join these networked efforts and we will need to negotiate access to their data — from the massive claims databases of payers to R&D data developed by the life sciences industry and government. Pooling such data and making it publicly available would provide a key starting point for new innovations in diagnostics, therapeutics and patient care.

For small companies in particular, such access is both hard to come by and increasingly valuable at a time of heightened regulatory uncertainty and risk.

For small companies, participation will likely be a trade-off between the perceived need to hold on to information and the benefits of participation, such as access to regulators and earlier insight into new standards before they are publicly disclosed. As Marc Cantillon and Magali Haas articulate in their articles, early

examples of open learning networks have had no problem attracting small companies. In an environment where the existing model is under strain and companies and investors are looking for ways to reduce the regulatory and other risks associated with drug development, we think that others may similarly see a net benefit in participating. Over time, if this approach gains traction and shifts the very paradigm of drug development, companies may find that investors see participation in a HOLNet as a significant risk-reduction strategy.


Providers

For providers, a key challenge in the new ecosystem will be figuring out how to succeed in an outcomes-driven, patient-centric world. In the US, physicians will increasingly find themselves moving from a fee-for-service model to one in which they are rewarded based on episodes of care or their ability to improve outcomes. Indeed, the emphasis on outcomes is likely to affect providers everywhere, as payers across the world look at ways to manage costs.

To succeed in this environment, providers will need to improve patient outcomes — and to do that, they will invariably need to get closer to patients. While one could argue that providers are already closer to patients than most other potential HOLNet members, the interactions they currently have with patients are a far cry from what success will increasingly require — enduring relationships and a deep understanding of individuals’ needs, conditions and behaviors. Health care delivery will need to move from a world in which patients only meet their doctors sporadically — typically for an annual checkup or when they fall sick — to one in which new technologies and more sophisticated data allow providers to monitor patients’ conditions on an ongoing basis and develop real-time insights into the progression of their diseases.

This is one reason we are seeing an acceleration in EHR adoption and the use of data to better define standards of care. Over time, providers will also need to develop enduring relationships with patients to truly provide holistic care.

Providers would have much to contribute — EHR data, patients for clinical trials, etc. — and would also gain much in return, including the ability to improve outcomes by learning in real time from research and from a richer pool of data that makes connections between EHRs, genetic profiles, claims data and much else.

Payers and policy makers

The interests of payers and policy makers, perhaps more than those of any other entities, are perfectly aligned with the move to HOLNets. Indeed, the changes they are making to incentives to address their biggest challenges — the need to tame health care costs while simultaneously covering more unmet medical needs due to demographic changes and expansions in coverage — are accelerating the shift.

As already discussed, these entities have so far been addressing these challenges by moving toward outcomes-based models such as adopting some form of health technology assessment and negotiating pay-for-performance or episode-of-care reimbursement arrangements. With HOLNets, they have the opportunity to take this to the next level. Payers might contribute claims data and would benefit significantly if these networks are able to drive down costs across the spectrum of health care. Additionally, HOLNets provide an opportunity to increase the focus on developing cures for diseases where there is significant unmet social need — a big gap between the costs a disease imposes on society and the resources currently devoted to R&D. It is no coincidence that early examples of this approach are often focusing on diseases where this gap is large, such as Alzheimer’s disease and Parkinson’s disease.

Non-traditional entrants

The move to an outcomes-focused ecosystem is attracting a host of “non-traditional” entrants. Firms from a broad range of industries — information technology, telecommunications, retail trade and others — are drawn by the opportunity to apply their skills to the challenge of making health care costs sustainable. Developing new offerings that are patient-centric and outcomes-driven will involve combining a wide variety of capabilities. And at a time when finding new sources of growth is often challenging, the sheer size of the opportunity in health care is an attractive target. It will often be necessary to include some of these companies in HOLNets, since the skills and assets they bring (e.g., data mining, analytics, mobile technology to interact with patients) could be very valuable. They might participate as full partners or on a more limited, fee-for-service basis.


Patients and disease foundations

Last, but certainly not least, patients will need to be part of the HOLNet approach. Indeed, as already discussed, patients are at the center of the new ecosystem, with more control over their data and health care. Certainly, they have much to gain by participating — no one has a bigger interest in improving health outcomes than patients themselves. And, as discussed above, HOLNets are often likely to focus on intractable diseases where there are significant unmet needs — something that patients in those disease groups should be happy to encourage, particularly at a time when there is increased competition for relatively scarce R&D budgets.

To make this happen, patients will need to contribute their data — genetic information, social media threads, data about their conditions, disease progression, side effects, etc. As we move to a world where patients have more control over their data, it will be important for HOLNets and their member entities to be transparent about how this data will be used, clearly articulate the benefits to patients and ensure compliance with their data usage policies. Privacy remains a sensitive issue — particularly in an area as personal as health — but with appropriate protections (such as separating medical data from personally identifiable information), informed consent and a full understanding of the benefits, patients can be motivated to participate. As “trusted brokers,” disease foundations could help encourage patient participation.

So far, disease foundations have led the charge on behalf of patients by driving academic researchers, companies and regulators to focus on the urgent needs of patients with a particular condition. These organizations will continue to play a critical role, since they have the trust of patients and can serve as an important intermediary. In some cases, however, it may also become imperative to broaden the focus beyond individual diseases as we currently define them. We turn to this aspect next.

Partnering for specialization

John Maraganore, PhDAlnylam Pharmaceuticals, CEO

If big pharma’s pipelines are any indication, the drug industry is starving for innovation. While pharma needs to access biotech’s innovation, biotechs and their investors are resistant to cede its value. This is a recipe for stalemate. The industry needs different partnership structures which fully pay biotech firms for innovation and leave early-stage development in their hands, while allowing pharma to conduct later-stage development and commercialization.

The question is whether pharma can rely fully on biotech for its innovation and whether biotech can rely fully on pharma for its late-stage development and global commercialization. For too long, the industry has been splintered into camps, each focused on building value within its own organizations the only way it knows: by maintaining control over the entire value chain. But drug R&D and commercialization are now far too complex for any one company to be good at all of those disparate activities.

The solution is increasingly obvious: partnership structures in which the discovery innovator gets paid for, and maintains control of, higher-risk stages — and where the pharma partner provides downstream expertise. But this solution in turn requires a fundamental rethinking of transaction and company structure. No biotech will forfeit the value of its innovation without a considerable rethink of the economics. Nor will it readily give up control of early development, for fear of being buried in a large company’s bureaucracy or sidelined in favor of an in-house candidate. Only when companies cede authority over those areas in which they aren’t competitive will we see an industry whose productivity is commensurate with its investment, an industry best prepared to harness the remarkable pace of biomedical discovery and capable of meeting its obligations to patients.

It may become imperative to broaden the focus beyond individual diseases as we currently defi ne them.


Beyond disease

It is not surprising that many of the early examples of R&D networks are focused on brain diseases. After all, these are conditions where there is a large (and, thanks to aging populations, growing) unmet medical need coupled with insufficient R&D investment relative to the cost imposed on society. The brain is perhaps the most complex system in the human body, but because of our limited ability to access this organ, it is also one of the least understood. These challenges have made it exceedingly difficult to develop treatments in this area — leading investors and companies to pull back because of the high risk involved.

While this investment gap — between the societal cost and level of investment — might be most significant in brain diseases, similar gaps exist for other ailments. Chronic diseases, for instance, are expected to impose a very large and rapidly escalating societal cost as populations age and emerging markets grow increasingly prosperous. While we have proven drugs to manage these conditions, very little has been done to apply personalized medicine approaches to better classify these diseases into subtypes and develop treatments that are more targeted and efficacious. At the same time, the economics of developing drugs for these diseases has become increasingly difficult, as drug developers have to compete with newly generic versions of their own past successes and an exceedingly cautious regulatory environment has escalated safety concerns in these indications. Chronic diseases would therefore be another prime candidate for a HOLNet approach, to close the gap between the high societal cost/medical need and relatively low levels of investment.

It is equally noteworthy that most of the efforts to close such gaps are being led by disease foundations and other nonprofits. Yet, HOLNets may at times also need to rethink traditional boundaries and definitions of disease. This has already been happening in personalized medicine, as insights from genetic data have redirected how we think about disease. In cancer — the area where personalized medicine approaches have made greatest headway — it has become increasingly apparent that what’s relevant is not where the disease is manifested (“breast cancer” or “blood cancer”) but the mechanism that causes it (e.g., a specific genetic mutation). By the same token, a disease foundation focused on a particular type of cancer may be too narrow if it seeks to develop a HOLNet purely for this ailment. It is therefore appropriate that organizations such as One Mind for Research are focusing on all brain diseases holistically rather than focusing only on individual diseases such as Alzheimer’s or Parkinson’s. Over time, such groups may find that even a widening of disease boundaries is too limiting an approach. After all, the human body is a very complex and interconnected system.

The bottom line is that, while many of the early examples are being led by disease foundations, it will be imperative to ensure that the focus is not overly narrow. Today’s networks have often been referred to as “disease networks,” but we think this name is too narrow and have intentionally chosen a broader term to emphasize that what’s important is not the focus on a specific disease but the creation of a framework that allows for continuous learning from real-time information sharing and openness.


Conclusion

Today, the health care ecosystem and its constituents face historic challenges. At a time when key stakeholders — payers, pharma companies, biotech firms and their investors — are increasingly resource-constrained, we need R&D paradigms that are several shades more efficient and productive. With aging populations and rapidly growing middle classes in emerging markets, societies need ways to accelerate cures for ailments that are expected to impose huge societal costs, such as neurodegenerative and chronic conditions. And as health care moves to a new patient-centric, outcomes-focused ecosystem, its constituents need ways to develop deeper relationships with patients to demonstrably improve their outcomes.

HOLNets provide some answers to all of these challenges. At a time when traditional approaches have become increasingly untenable, the HOLNet is a boldly different paradigm that seizes the opportunities latent in the changing health care ecosystem — big data, real-time insights, the diverse strengths of a wide range of players.

Getting there will take some adjustments. If HOLNets are about openness and learning, health care’s constituents will often need to be open to new approaches and learn new ways of doing things. For life sciences companies, this will involve different ways of thinking about intellectual property and recognizing that in some situations, sharing information may create more value than protecting it. Regulators will need to adapt frameworks to allow for drug development paradigms that are flexible and learn in real time. And ultimately, patients will need to willingly share their personal health data, with the recognition that they might reap some of the biggest dividends from this approach: better health outcomes, better drugs and cures for long-intractable diseases.

The HOLNet is a boldly different paradigm that seizes the opportunities latent in the changing health care ecosystem — big data, real-time insights, the diverse strengths of a wide range of players.


Patient-centric innovation: networked and personalized

N. Anthony Coles, MDOnyx PharmaceuticalsPresident, CEO and Member of the Board

Over the past decade, the traditional “one-size-fits-all,” chemistry-based approach to pharmaceutical drug development has become increasingly untenable. It now takes an average of more than US$1 billion and 12 years to bring new products to patients, and only 10% of promising compounds become new medicines. Spurred by the need to make drug development more cost-effective and by advances in genomics and genetics, a new paradigm has emerged that balances traditional chemical approaches with biological and genomic techniques to identify a new generation of targeted therapies. These “smart drugs” can be given to the right patient at the right time and can treat the individual basis of disease.

Meanwhile, our industry’s long-standing “go-it-alone” approach, in which companies attempt to single-handedly discover and develop new medicines, is being challenged for its scientific productivity and efficiency, and for the absence of scale in an age of rapid innovation. We have to — and are starting to — find new ways to accelerate the development of even better therapies for unmet medical needs. Underpinning this new approach is the opportunity to collaborate with key groups and stakeholders to, in effect, “network” innovation. By partnering with networks of academicians, scientists, regulators, policy makers and patient communities, we can create more breakthroughs that patients desperately need.

First, and most important, our focus must remain on the patient. As clinicians, we understand that no two patients are alike. For industry to embrace the individual differences between patients, we will need an intense focus on personalized medicine. By taking a holistic, patient-centered approach and integrating patients’ genetic information with genomic research, we can partner with patients to move beyond one-size-fits-all pills and create new approaches to personalized health. Access to electronic medical records, biometric data and emerging technologies from the digital revolution leads to the assimilation and utilization of state-of-the-art clinical knowledge, which can allow us to move even closer to patients to meet their needs.

At the same time, we must work even more closely with governments and regulators around the world. It currently takes too long to bring a new drug to market, particularly when one considers the benefit and life extension many therapies provide. Efforts are currently under way by both regulators and lawmakers, in collaboration with industry, to shorten the time from bench to bedside. But more work must be done to incorporate the latest thinking about new clinical trial approaches and the acceptable trade-offs between risk and benefit in order to race forward with much-needed improvements to our existing crop of therapies. Despite the progress we have made in several disease areas, several others — cancer, Parkinson’s disease and Alzheimer’s disease, to name a few — still need new and effective treatments.

Finally, we must be creative and open-minded about new partnerships — with other companies, academic institutions, government and nonprofit organizations — and need to move beyond the standard technology licensing approach. This means more unique collaborations, such as the one between Ford Motors and Medtronic to create an in-car glucose monitor, or between Novartis and Nintendo to raise disease awareness and educate patients through the use of online gaming. In an effort to create one of these new approaches, Onyx has recently initiated an innovative research alliance with the University of Texas MD Anderson Cancer Center to accelerate the discovery and translation of new knowledge about cancer from the laboratory to patients.

The biopharmaceutical environment grows ever more complex and potentially more prolific as new technologies give us fresh insights into biology and the genome and as new digital tools make it possible for researchers, patients and providers to collaborate in ways that would have been impossible even a decade ago. This fundamental shift in thinking and activity creates the potential for tremendous upheaval, and with this disruption comes unparalleled opportunity to experiment with new models of collaboration. With so many people pulling toward a common goal, our challenge now is to all pull in the same direction.

21Moncef Slaoui Protecting the biotech ecosystem

Protecting the biotech ecosystem

Moncef Slaoui, PhDGlaxoSmithKlineChairman, Research & Development

At GlaxoSmithKline, we have about 14,000 scientists and spend almost US$6.4 billion a year on R&D. With such vast resources, one could easily believe — and many large companies did as recently as a decade ago — that having a healthy ecosystem of emerging biotech companies is not terribly material to our success.

In fact, we believe the opposite. We have 14,000 scientists, but there are probably a million life science scientists in the world — which suggests that we will generate only 0.1% of the good ideas. So, everything we do is built on the premise that we need a strong ecosystem of biotech companies.

Yet, today this ecosystem is threatened. The biotech industry has historically thrived because investors could earn high returns commensurate with the huge risks involved in drug R&D. In recent years, investors’ willingness to make such high-risk bets has declined, for two reasons. First, as pharma companies’ resources got squeezed, they started looking for lower-risk approaches and investments. Second, returns from IPOs have declined — putting the VC investment model under strain.

As a result, GSK is beefing up its venture arm, SR One. We have also announced deals with at least three other VCs — Europe’s Index Ventures, Boston’s Longwood Fund and North Carolina-based Hatteras Venture Partners — where we are investing as limited partners. And we continue to look for similar opportunities elsewhere with the right VCs.

We are also very active in business development, with alliances with about 50 different biotech companies. Almost all of these are strategic in the sense that they are not focused on a single project but rather on an entire segment of the company’s portfolio. This is critical, because it creates multiple exit opportunities for investors.

Beyond these efforts, I’ve also proposed — with a couple of other industry veterans, John Maraganore and Stelios Papadopoulos — that pharma companies should consider creating investment funds with the purpose of buying biotech IPOs. Acquisitions do not currently represent a sustainable exit strategy, since they have very high hurdles and are relatively infrequent events beyond the control of small companies and their venture investors. Pharma-supported investment funds could boost the IPO market by validating companies — after all, pharma buyers have the most sophisticated technical capabilities for assessing technology risks and the value of companies.

Another way in which pharma companies could do more to support the ecosystem is through precompetitive collaboration. In target validation, for instance — the process of figuring out whether a certain target can affect a particular biology and physiology for a disease — about 60%–70% of the targets we are working on are also being pursued by our competitors. This is expensive and wasteful, because target validation is not where we ultimately compete. The competitive play really comes after a target has been validated — for instance, in the kinds of chemistry we develop to create a drug.

This is particularly relevant in neurodegenerative diseases such as Alzheimer’s, where target validation is tremendously slow and expensive for numerous reasons. Animal models have proven ineffective, so validation has to happen in the clinic. Cognition is a subjective measure, and you need very large patient populations to truly understand it. Lastly, neurodegeneration is a very slow process — it takes 10–20 years to express itself clinically.

Precompetitive collaboration may not be universally applicable. In disease areas where target validation is fairly quick and straightforward, companies may not have much incentive to collaborate, and many biotech companies, in particular, view target validation as a source of competitive advantage. But in certain disease areas, precompetitive collaboration could be a game changer.

Now, more than ever, we need game changers. Sustaining the biotech ecosystem is not an act of charity or corporate social responsibility — it is in the self-interest of big pharma companies. The good news is that through approaches such as the ones described here, we can use our extensive resources to really make a difference.


To boost R&D, stop flying blind and start observing

Joshua Boger, PhDVertex Pharmaceuticals Founder and Board Director

Drug development is often described as a linear process: formulating a hypothesis and then testing it in a series of experiments. That’s accurate as far as it goes, but it minimizes another pillar of science, observation. Science is an inherently iterative process: hypotheses are refined based on observations and learning from prior experiments. Yet in our industry, drug development has become less and less about observation and more and more about a rigid approach to hypothesis testing. This is particularly true in Phase II clinical trials, the central — and arguably most important — phase of the development process.

The purpose of Phase II is to identify and begin to frame a drug’s possible benefits — how it improves health outcomes and the risks it might carry — which involves observing benefits and risks and assembling data to determine dosage amount and schedule. While this definitely requires hypotheses based on previous observations, the process of observation and hypothesis generation needs to continue in Phase II, as well.

Unfortunately, today’s Phase II trials often pay lip service to observation and exploration, breezily truncate dose selection and do not welcome hypothesis generation — often before a drug candidate’s effects and side effects have been well characterized. In too many cases, we blow past experimental learning and go straight to confirmation. So what’s wrong with that? Doesn’t that get you to a drug sooner? Well, no, almost never.

In an era of scientific breakthroughs, almost every important new drug will be forging new paradigms, breaking ground on endpoints and mechanisms and may even be the first therapy targeting a disease. At the start of Phase II, there may be some anecdotal clinical observations and even considerable biochemical evidence thought to be predictive of benefit, but all of these data are usually based on assumptions and analogies with other approaches. One of the many guarantees of clinical research is that you are going to be surprised, with both downside and upside surprises. If you’ve locked in your hypotheses before you get to Phase II, you’re going to miss much of that upside, and you won’t be agile enough to cope with the downside.

Over the last couple of decades, Phase II trials have often grown from exploratory observational experiments at one or two clinical centers to quite large “mini-Phase-III” trials at tens of clinical sites, often on multiple continents, with tightly defined primary endpoints and structures designed to obtain the holy grail: p-value. This drive to obtain a p-value of “significance” (i.e., below the arbitrary and religious cutoff of 5%) on a primary endpoint thought to be “approvable” (i.e., acceptable for Phase III and for drug approval) often leads to overreaching. In many cases, more modest endpoints would be more appropriate for the state of the drug candidate and the known data. The result is Phase II trials that are larger, longer and more expensive than should be necessary to advance the drug into Phase III.

Exacerbating the problem is the perceived need to “blind” Phase II trials, keeping all but the most catastrophic observations under wraps until the process is completed and the data locked. Ironically, Phase II trials of this kind often generate a wealth of information about rich secondary endpoints (in addition to the primary endpoints) and about other scientific and mechanistic questions, but none of these data are available for examination in real time, due to the desire to “preserve the integrity” of the precious primary endpoint and its p-value. This strict blinding of Phase II trials imposes significant costs, including: lengthening the development process; losing the ability to quickly incorporate lessons from the trial into subsequent, even overlapping, trials; and losing the ability to manage overall R&D resources in a more rational and timely fashion. For sure, there are disease areas where, because of the lamentable lack of objective endpoints, blinding of trials may be required. But increasingly, efficacy endpoints for modern trials are (or should be) beyond subjective influence. Safety reports, many of which are self-reported by patients, might be unduly influenced by inappropriate dissemination of ongoing data, but even here, there are procedures available to minimize this bias.

So if running Phase II trials in a more open and exploratory manner has so many possible advantages, who is against it? Why doesn’t it happen more often? The interests of many constituencies maintain this p-value-worshipping status quo. Investors and analysts crave simplicity, and there is no simpler discriminator than “What’s the p-value?” Complex, multi-endpoint, dose-range-finding trials are punished on Wall Street. Investors ask, “Why are your trials so hard to understand?” (The answer — that they were not designed to be easy for investors to understand — is usually not welcomed.) In addition, regulators often insist on p-value trials. In the last couple of decades, the FDA has taken a far more directive role in the design of Phase II trials. Ironically, as the opportunities for

23Joshua Boger To boost R&D, stop flying blind and start observing

drug breakthroughs have increased, many in the FDA have taken a more conservative and dogmatic approach to mid-stage clinical development. Under the mandate of safety, detailed control of Phase II clinical plans by regulators has become the norm. The implicit message from too many medical reviewers is: “design it my way or face a clinical hold.” In new therapeutic areas or in existing areas witnessing paradigm shifts, this often drives doctrinaire exploratory trials, which prematurely slot a new drug development plan into the closest precedent, rather than letting new insights drive new hypotheses and testing. Science by consensus is rarely innovative. Lastly, management at drug development companies are often overly cautious. Who can criticize the crisp thumbs-up or thumbs-down of a definitive Phase II trial? Lost opportunity and missed serendipity are invisible losses, and the hyperbolic escalation of costs and time continues with no finger-pointing.

The best clinical experiments gather the most (and most relevant) information in the shortest possible time and with the least possible resources. Phase III awaits with its immutable endpoints and black-and-white success criteria. Meanwhile, let’s preserve Phase II as the place in development to learn every day, not just in fits and starts separated by months — or even years — of self-imposed blindness. Time and money are wasting, and our patients need us faster than any definitive Phase II “shortcut” will allow.

In my experience, drugs that do not work and drugs that substantially exceed minimal expectations are easy to spot. While there are exceptions, if you need a statistician to measure benefit in Phase II, then the drug didn’t work that well. In a world of profound opportunity to change medicine, maybe we shouldn’t be working on those middling cases. Identify as fast as possible the drugs that don’t work (and learn from them), and identify as fast as possible the upside surprises. Get on with the breakthroughs and leave the rest behind.

Financial performance

25Financial performance The big picture

Financial performance

Recovery and stabilizationThe big picture

The aggregate financial performance of publicly traded biotechnology companies in the four established clusters — the United States, Europe, Canada and Australia — was encouraging in 2011, as the industry built on the recovery that had started a year earlier. To fully appreciate this, one needs to view the year’s numbers not just against the performance in 2010, but also in the context of the situation in 2009, when the industry was hit hard by the financial crisis and initiated a wave of cost cutting unlike anything it had seen before. This resulted in a truly remarkable development — the industry reached aggregate profitability for the first time in its history, not because of the success of its commercial leaders, but because of steep cost cutting by a broad swath of companies.

To get a true picture of the year’s performance, we also need to adjust for the fact that three large US-based companies were acquired by non-biotech buyers, effectively removing them from the biotech pool in 2011. The loss of these three firms —

Genzyme Corp., Cephalon and Talecris Biotherapeutics — which collectively had revenues of US$8.5 billion in 2010, made a significant dent in the industry’s 2011 performance. To get a sense of the organic “apples-to-apples” growth of the industry, we have therefore calculated normalized growth rates that remove these three firms from the 2010 numbers.

With these adjustments, it becomes apparent that the biotech industry continued its return to pre-crisis levels of normalcy in 2011. The revenue growth of public companies in the four established clusters returned to double-digit territory for the first time since the advent of the crisis. The sector’s top-line growth of 10% compares favorably to the 8% growth rate in both 2010 and 2009 (adjusted for the Genentech acquisition). While this is still a far cry from the high double-digit growth rates the industry delivered through much of the last decade, companies are also operating in a new reality now, with more cautious regulators and increased pricing pressure from payers.

Growth in established biotechnology centers, 2010–11 (US$b)

Source: Ernst & Young and company financial statement data.Numbers may appear inconsistent because of rounding.

2011 2010 % change% change

(normalized for large acquisitions)

Public company data

Revenues 83.4 84.1 -1% 10%

R&D expense 23.1 22.6 2% 9%

Net income 3.8 5.0 -24% -5%

Market capitalization 376.0 401.1 -6% 0.2%

Number of employees 163,630 177,100 -8% 4%

Number of companies

Public companies 617 629 -2% -1%


Perhaps the strongest measure of the industry’s increasingly stable financial picture is R&D expenses. The industry, which had slashed R&D by 21% in 2009 (the only time in its history that this research-driven sector has cut R&D spending in aggregate), had seen a cautious return to positive territory in 2010, when R&D grew by a modest 2%. In 2011, the picture strengthened further, as R&D increased by 9% (on a normalized basis). Even more telling is evidence that the growth in R&D spending was broad-based, not driven by the activities of a few large firms. In the US, 62% of public companies increased R&D spending in 2011, which is roughly in line with historic trends. This represents a significant improvement from 2010, when 51% of companies had increased R&D spending, and a dramatic reversal of the situation in 2009, when an almost identical percentage — 64% — had decreased R&D spending. The situation in Europe was similarly encouraging, with 58% of companies increasing R&D spending in 2011 (up from 55% in 2010).

On the other hand, the industry’s net income fell in 2011, even after adjusting for the three large acquisitions mentioned earlier. Among the commercial leaders that experienced a decline in net income in 2011 were Amgen (which incurred a US$780 million charge for a legal settlement), Amylin Pharmaceuticals (which incurred a US$431 million charge related to the termination of a strategic alliance) and Actelion (which incurred a US$407 million charge related to a lawsuit). To a considerable extent, however, the fall in net income was driven not by events at a few companies as much as broader trends across the industry. Companies that were in deep cost-cutting mode in 2009 and cautiously optimistic in 2010 may have become somewhat more willing to loosen their purse strings in 2011. After all, while the huge aggregate profits of the last two years have been a noteworthy event, this is an industry that has been in the red for the vast majority of its history. A decline in profitability may simply be a sign that things are indeed starting to return to normal.

US Europe Canada

2011 2010 2011 2010 2011 2010

More than 5 years of cash 22% 24% 27% 39% 10% 18%

3–5 years of cash 9% 7% 10% 6% 10% 6%

2–3 years of cash 10% 13% 10% 14% 7% 7%

1–2 years of cash 20% 21% 21% 19% 24% 16%

Less than 1 year of cash 39% 35% 32% 34% 49% 53%

Source: Ernst & Young and company financial statement data.Chart shows percentage of biotech companies with each level of cash. Numbers may appear inconsistent because of rounding.

Ernst & Young survival index, 2010–11

27Financial performance United States

US biotechnology at a glance, 2010-11 (US$b)

United States

As always, since the US accounts for a large majority of the industry’s revenues, the US story is very similar to the global one. The revenues of US publicly traded biotech companies declined in 2011, but this was driven by the acquisitions of Genzyme, Cephalon and Talecris by non-biotech acquirers. After normalizing for these large acquisitions, the US industry’s revenues increased by 12%, outpacing the 10% growth rate seen in 2010 and

2009 (adjusted for the Genentech acquisition). R&D increased by 9% on a normalized basis, after having declined sharply in 2009 and increasing by a modest 3% in 2010. The industry’s net income position weakened, even after normalizing for the three megadeals mentioned above. The number of companies held steady and employees grew by 5% on a normalized basis — identical to the increase in headcount in 2010.

2011 2010 % change% change

(normalized for large acquisitions)

Public company data

Revenues 58.8 61.1 -4% 12%

R&D expense 17.2 17.2 0% 9%

Net income 3.3 5.2 -36% -21%

Market capitalization 278.0 292.1 -5% 4%

Number of employees 98,560 113,010 -13% 5%

Financings

Capital raised by public companies 25.4 17.1 49% 49%

Number of IPOs 10 15 -33% -33%

Capital raised by private companies 4.4 4.4 -1% -1%

Number of companies

Public companies 318 320 -1% 0%

Private companies 1,552 1,594 -3% -3%

Public and private companies 1,870 1,914 -2% -2%



US commercial leaders, 2008-11

As mentioned earlier, the US biotech industry lost three of its “commercial leaders” (firms with revenues in excess of US$500 million) in 2011 due to the purchase of Genzyme, Cephalon and Talecris. But biotech has always been a dynamic industry, and even as these big companies were taken out, a fresh crop of

companies graduated into the ranks of the commercial leaders. Specifically, the revenues of Salix Pharmaceuticals, Vertex Pharmaceuticals and ViroPharma crossed the US$500 million threshold, leaving the total number of commercial leaders unchanged at 16.

Source: Ernst & Young and company financial statement data.Commercial leaders are companies with revenues in excess of US$500 million.

2008

13 companies

2009

13 companies

2010

16 companies

2011

16 companies

Organic growth Alexion Alexion

Amgen Amgen Amgen Amgen

Amylin Amylin Amylin Amylin

Biogen Idec Biogen Idec Biogen Idec Biogen Idec

Bio-Rad Laboratories Bio-Rad Laboratories Bio-Rad Laboratories Bio-Rad Laboratories

Celgene Celgene Celgene Celgene

Cephalon Cephalon Cephalon Acquired by Teva

Organic growth Cubist Cubist Cubist

Organic growth Gen-Probe Gen-Probe

Genentech Acquired by Roche

Genzyme Genzyme Genzyme Acquired by Sanofi

Gilead Sciences Gilead Sciences Gilead Sciences Gilead Sciences

Illumina Illumina Illumina Illumina

Life Technologies Life Technologies Life Technologies Life Technologies

Organic growth Salix Pharmaceuticals

Sepracor Acquired by Dainippon Sumitomo

IDEXX Laboratories IDEXX Laboratories IDEXX Laboratories IDEXX Laboratories

IPO Talecris Biotherapeutics Talecris Biotherapeutics Acquired by Grifols

Organic growth United Therapeutics United Therapeutics

Organic growth Vertex Pharmaceuticals

Organic growth ViroPharma


US biotechnology: commercial leaders and other companies, 2010-11 (US$b)

Even though the number of commercial leaders remained unchanged at 16, the big firms that were acquired were much larger than the three companies that replaced them. As a result, these mega-acquisitions had a significant impact on the performance of the industry’s commercial leaders. On a normalized basis (i.e., removing the three acquisitions and the three new commercial leaders from the 2010 and 2011

numbers), the revenues of the commercial leaders grew by 9% and R&D expenses grew by 4%. However, net income decreased by 7% even after normalization.

The performance of the other companies — the vast majority of the publicly traded US biotech industry — was relatively flat, with very small changes in revenues, R&D expense and net loss.


2011 2010 US$ change % change

Commercial leaders

Revenues 48.0 50.3 (2.3) -5%

R&D expense 9.2 9.4 (0.2) -2%

Net income (loss) 10.0 11.5 (1.5) -13%

Market capitalization 190.6 193.4 (2.7) -1%

Number of employees 64,050 79,000 (14,950) -19%

Other companies

Revenues 10.8 10.8 (0.0) 0%

R&D expense 7.9 7.7 0.1 2%

Net income (loss) (6.6) (6.2) (0.4) 6%

Market capitalization 87.0 97.1 (10.1) -10%

Number of employees 34,510 34,010 500 1%


The market capitalization of the US biotech industry slightly outperformed leading stock market indices during 2011 and the first five months of 2012. Micro caps did significantly better than companies of other sizes during this period, continuing the trend observed in last year’s report.

The US biotech industry outperformed the overall market in most of 2011 and early 2012

-20%

-15%

-10%

-5%

0%

+5%

+10%

+15%

+20%

+25%

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May

2011 2012

EY biotech industryNASDAQ Composite Index

Dow Jones Industrial Average S&P 500 Index

Source: Ernst & Young and finance.yahoo.com.EY biotech industry represents the aggregate market cap of all US public biotech companies as defined by Ernst & Young.

US micro caps led the industry’s stock market performance in 2011 and early 2012

Source: Ernst & Young and finance.yahoo.com.EY biotech industry represents the aggregate market cap of all US public biotech companies as defined by Ernst & Young.

-30%

-20%

-10%

0%

+10%

+20%

+30%

+40%

+50%

+60%


2011 2012

Mid-cap (US$2b–US$10b)Largest cos (market cap above US$10b) EY biotech industry

Small-cap (US$200m–US$2b) Micro-cap (below US$200m)


Selected US biotechnology public company financial highlights by geographic area, 2011 (US$m, % change over 2010)

Region

Number of public

companies

Market capitalization

31.12.2011 Revenue R&DNet income

(loss)

Cash and equivalents

plus short-term investments Total assets

San Francisco Bay Area 68 5%

61,1084%

14,376 7%

3,95411%

1,412 -31%

16,698129%

30,691 55%

New England 46 -2%

64,994 2%

10,326 -17%

3,473-17%

842207%

6,685-10%

18,935-29%

San Diego 33 -3%

21,215 -31%

6,73311%

1,3836%

(810)148%

4,25246%

16,65527%

New Jersey 24-4%

42,723 29%

5,57026%

1,5413%

96456%

3,836-2%

11,908-1%

New York State 23 10%

7,607 17%

1,164 19%

770 18%

(336)-28%

1,18860%

2,47917%

Southeast 20 5%

3,2119%

209-29%

200-17%

(238)11%

52829%

82836%

Mid-Atlantic 18-5%

6,658-45%

1,3999%

81610%

(400)74%

1,720-17%

4,4653%

Los Angeles/Orange County 13 0%

51,791-3%

15,7874%

3,3589%

3,320-23%

20,71618%

49,16512%

Pacifi c Northwest 13 0%

3,916-48%

501137%

43116%

(701)-8%

585-23%

756-40%

Pennsylvania/Delaware Valley

11-21%

5,021-48%

907-76%

378-51%

(186)-157%

994-58%

2,104-70%

Texas 100%

1,4635%

21434%

14328%

(112)22%

398 74%

73887%

North Carolina 9 -25%

3,564 -55%

739-67%

310 14%

25 -71%

711-42%

1,816-44%

Midwest 9 -10%

406-32%

29 -10%

129 37%

(227)48%

162139%

272155%

Colorado 814%

825 8%

14866%

16746%

(206)7%

35449%

42034%

Utah 30%

1,861-17%

40211%

48-4%

60-42%

453-16%

735-2%

Other 1025%

1,638109%

29579%

10112%

(71)-36%

394159%

676201%

Total 318-1%

278,000-5%

58,800-4%

17,2020%

3,334-36%

59,67624%

142,6445%

Source: Ernst & Young and company financial statement data.Percent changes refer to change over December 2010. Some numbers may appear inconsistent because of rounding.New England: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, VermontMid-Atlantic: Maryland, Virginia, District of ColumbiaSoutheast: Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Tennessee, South CarolinaMidwest: Illinois, Michigan, Ohio, WisconsinPacific Northwest: Oregon, Washington

Europe


European biotechnology at a glance, 2010–11 (US$m)

In Europe, as in the US, publicly traded biotechnology companies increased their top lines by 10%, compared to 12% in 2010 and 8% in 2009. R&D expense, which had declined by 2% in 2009 and increased modestly by 5% in 2010, grew by a much more robust 9% in 2011. A significant difference from the US performance, however, was on the bottom line. While US companies’ net profit decreased in 2011, European companies went in the other direction, essentially bringing the industry to the brink of aggregate profitability for the first time in its history. However, this was essentially driven by a single event at a commercial leader: Elan’s sale of its drug technology to US-based Alkermes for US$500 million. The number of employees increased by 4%, compared to 1% in 2010 and 2009 — another positive indication.


2011 2010 % change

Public company data

Revenues 18,911 17,233 10%

R&D expense 4,921 4,513 9%

Net income (loss) (0.3) (568) -100%

Market capitalization 71,519 78,639 -9%

Number of employees 48,330 46,450 4%

Financings

Capital raised by public companies

1,570 2,407 -35%

Number of IPOs 6 10 -40%

Capital raised by private companies

1,321 1,371 -4%

Number of companies

Public companies 167 170 -2%

Private companies 1,716 1,758 -2%

Public and private companies 1,883 1,928 -2%

33Financial performance Europe

European biotechnology: commercial leaders and other companies, 2010-11 (US$m)

In the US, the list of commercial leaders has been quite dynamic, with some companies being acquired and others crossing the US$500 million threshold through organic growth. In Europe, however, the list of commercial leaders — Actelion, Elan Corporation, Eurofins Scientific, Ipsen, Meda, Novozymes, Qiagen and Shire — has not changed since 2007.

In 2011, the performance of these commercial leaders stood in stark contrast to that of the rest of the industry. The revenues of commercial leaders increased by 19%, while those of the other companies decreased by an identical percentage. The same pattern was repeated across all the major indicators, with the health of a few large companies increasing as the rest of the industry saw its performance worsen.


2011 2010 US$ change % change

Commercial leaders

Revenues 15,522 13,042 2,480 19%

R&D expense 2,641 2,100 541 26%

Net income (loss) 2,024 1,429 595 42%

Market capitalization 51,667 48,697 2,970 6%

Number of employees 33,570 30,970 2,600 8%

Other companies

Revenues 3,389 4,191 (802) -19%

R&D expense 2,280 2,413 (133) -6%

Net income (loss) (2,024) (1,997) (27) 1%

Market capitalization 19,852 29,942 (10,090) -34%

Number of employees 14,760 15,480 (720) -5%


Europe’s largest biotech companies outperformed the rest of the industry in 2011 and early 2012

As one might expect from the analysis of commercial leaders and other companies, the market capitalization of the largest companies outperformed that of the rest of the industry in 2011 and the first five months of 2012. Small- and micro-cap stocks performed worst during this time frame.

-50%

-40%

-30%

-20%

-10%

0%

+10%

+20%

+30%

+40%


2011 2012

Largest cos (market cap above US$2.5b) EY biotech industry Mid-cap (US$1b—US$2.5b)

Small-cap (US$200m—US$2.5b) Micro-cap (below US$200m)

Source: Ernst & Young and finance.yahoo.com.EY biotech industry represents the aggregate market cap of all European public biotech companies as defined by Ernst & Young.

35Financial performance Europe

Selected European biotechnology public company financial highlights by country, 2011 (US$m, % change over 2010)

Source: Ernst & Young and company financial statement data.Percent changes refer to change over December 2010. Some numbers may appear inconsistent because of rounding.

Country

Number of public

companies

Market capitalization

31.12.2011 Revenue R&DNet income

(loss)

Cash and equivalents

plus short-term investments Total assets

United Kingdom 36-10%

23,1737%

4,96713%

1,0730%

62654%

1,3460%

8,66214%

France 19-14%

5,985-26%

3,37112%

588-5%

(80)925%

1,09814%

4,9898%

Sweden 249%

4,964-22%

2,61214%

676 121%

1244,943%

438-7%

7,79817%

Israel 2111%

1,604-11%

82-8%

92-20%

(176)26%

202-26%

4547%

Denmark 90%

10,737-2%

2,19512%

5293%

(12)-172%

422-56%

3,6575%

Germany 140%

1,458-28%

29534%

24914%

(151)-6%

208-53%

1,1233%

Switzerland 90%

4,664-37%

2,1285%

76232%

(425)-214%

1,8611%

3,6365%

Norway 90%

1,5811%

1172%

7830%

(44)-2%

219-16%

3611%

Netherlands 5-29%

3,329-56%

1,185-31%

150-55%

40109%

290-79%

3,839-31%

Belgium 60%

1,617-22%

232-12%

2567%

(209)142%

367-1%

7680%

Other 1515%

12,40736%

1,72751%

4673%

307-132%

83416%

3,87918%

Total 167-2%

71,519-9%

18,91110%

4,9219%

(0)-100%

7,285-13%

39,16612%


Canada

Canadian biotechnology at a glance, 2010-11 (US$m)

The financial performance of Canadian publicly traded biotech companies continued to decline in 2011. Revenues decreased 21% to US$998 million. R&D expenditures fell for the third consecutive year, to US$431 million, driven largely by continued cost-cutting measures. This drive to achieve efficiencies and cut costs also resulted in a fall in employment in the sector.

There are, however, some signs of hope. After the financial crisis in 2008, the Canadian biotech sector responded with cost-cutting and efficiency measures. The drive to do more with less has in turn led to some successes on the product development front, and many Canadian biotech companies announced positive clinical news in 2011 — a trend we haven’t seen for a while. Some companies obtained clinical and regulatory successes and others announced that they successfully advanced their products. These promising results were rewarded with an overall 53% increase in financing in 2011. However, despite this significant increase in financing over 2010, the sector is still below financing levels of 2005, 2006 and 2007.


2011 2010 % change

Public company data

Revenues 998 1,271 -21%

R&D expense 431 449 -4%

Net income (loss) (344) (358) -4%


Number of employees 3,600 4,880 -26%

Financings

Capital raised by public companies 574 396 45%

Number of IPOs 0 0 0%

Capital raised by private companies 166 87 91%

Number of companies


Private companies 146 153 -5%

Public and private companies 217 225 -4%

37Financial performance Australia

Australia

Australian biotechnology at a glance, 2010-11 (US$m)

The performance of Australian publicly traded biotechnology companies showed robust improvement in 2011. Revenues grew by 6%, R&D expenses by 13% and the collective bottom line improved by 15% relative to 2010. As always, these results are strongly affected by CSL, the colossus of Australia’s biotech sector, which continued to post healthy product sales and revenue growth. In addition, the 2011 numbers were affected by transaction-related events at a couple of other Australian firms. Melbourne-based Mesoblast saw a significant improvement in its top and bottom lines thanks to a US$263 million up-front payment from US-based Cephalon as part of a strategic alliance in which Cephalon acquired global rights in three treatment areas to products derived from Mesoblast’s adult mesenchymal precursor stem cell technology. Similarly, results at Acrux were considerably boosted by a milestone payment of US$87 million from US-based Eli Lilly and Co. after the FDA issued marketing approval for Axiron.


2011 2010 % change

Public company data

Revenues 4,712 4,465 6%

R&D expense 583 517 13%

Net income 822 717 15%


Number of employees 13,140 12,760 3%

Number of companies


Financing

39Financing The big picture

Financing

Innovative capital

At first glance, 2011 might appear to be an impressive year for biotech fund-raising. Companies in the industry raised a staggering US$33.4 billion during the year, second only to 2000, when the genomics bubble was at its height. Venture capital held

steady at US$5.8 billion — essentially unchanged from last year and comparable to amounts raised by the industry in the years preceding the global financial crisis.

But the overall numbers do not tell the real story, and the true picture is very different. The dramatic increase in capital raised can be explained in one word — debt. Specifically, a handful of “commercial leaders” (companies with revenues in excess of US$500 million) took advantage of low interest rates to raise large sums of debt, propelling debt totals to US$17 billion — the highest amount in the last decade, by a wide margin. As mature, cash-flow-positive entities, these companies do not need to raise capital to fund R&D. Instead, they raised these large sums for other purposes, such as financing acquisitions or stock buybacks. The debt-to-equity and debt-to-market-capitalization ratios of some big biotech companies now rival — and in some cases, exceed — those of their big pharma counterparts.

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

IPOs 602 484 2,157 1,781 1,806 2,263 116 840 1,316 857

Follow-on and other 3,885 12,894 12,968 10,235 19,972 14,246 5,360 11,270 8,497 9,780

Debt 2,628 92 33 2,958 561 6,249 4,758 4,078 10,117 16,915

Venture 3,623 4,096 5,682 5,417 5,379 7,638 6,184 5,743 5,867 5,838

Total 10,738 17,566 20,840 20,391 27,719 30,396 16,418 21,931 25,797 33,389

Source: Ernst & Young, BioCentury, BioWorld and VentureSource.Numbers may appear inconsistent because of rounding. Convertible debt instruments included in “follow-on and other.”

Capital raised in North America and Europe by year (US$m)

Source: Ernst & Young and company financial statements.Ratios based on financial results as of 31 December 2011.

Debt to equityDebt to market

capitalization

Big biotech

Amgen 113% 42%

Gilead Sciences 111% 25%

Celgene 33% 5%

Biogen Idec 17% 4%

Big pharma

Pfizer 47% 24%

Johnson & Johnson 34% 11%

Merck & Co. 30% 15%

Debt ratios of selected companies: big biotech reaches maturity

The big picture


Innovation capital: enough to sustain innovation?

Conversely, the amount of capital raised in 2011 by the vast majority of firms that are not mature commercial leaders — what we term “innovation capital” — remained relatively unchanged at US$16.8 billion. Indeed, the amount of innovation capital has remained remarkably flat over the last four years, averaging US$16.2 billion — about US$2 billion below the average amount of innovation capital raised between 2004 and 2007. In addition, there is a haves-and-have-nots story even within the ranks of those that raised innovation capital. These funds were not evenly distributed, and a relatively small number of companies garnered a significant portion of the total innovation capital invested in any given year.

The differing realities for biotech’s haves and have-nots are likely to persist for the foreseeable future. Investors have moved beyond buying dreams of better, faster and cheaper drug development. Instead, in today’s market, an increasingly concentrated and sophisticated group of investors sets the terms of most fund-raising transactions. (See the 2011 issue of Beyond borders for a discussion of the skills leaders of earlier-stage companies need to thrive in this environment.)

0

5

10

15

20

25

30

35

40

20112010200920082007200620052004

US$

b

Innovation capitalCapital raised by commercial leaders

Enough to sustain innovation? Innovation capital in North America and Europe by year

Source: Ernst & Young, Capital IQ, BioCentury and VentureSource.Innovation capital is the amount raised by companies with revenues of less than US$500 million.

41

Since innovation capital is the lifeblood of the biotech industry, let’s take a closer look at where these funds are going. Some facts:

• Private companies raised US$5.8 billion in venture capital in 2011 — an amount that has remained remarkably steady despite all the turmoil over the last several years. Indeed, venture capital totals during 2004–12 have averaged US$5.9 billion annually. Within the US and Europe, the number of venture rounds larger than US$5 million decreased by 33 (or 12%) from 2010, while the average amount raised per round increased by 15% to US$22.1 million. This increased concentration re ects an ongoing trend: investors are being more selective, but once they decide to back a technology, they are willing to provide signi cant capital to fund at least the initial value-creating activities. Despite expectations that a multiyear decline in fund-raising by venture rms would negatively impact new company formations, the number of rst-round transactions larger than US$5 million actually increased modestly in 2011 to 63 (from 55 in 2010) and the average amount invested per round increased a robust 24%. As we have pointed out in prior years, the announced values in rst rounds are typically invested in tranches over many months, or even years, as companies achieve development milestones. The 2011 average gures were also affected by three large initial rounds in the US that ranged between US$60 million and US$100 million. Overall, these gures show a more positive picture for venture nancing than is often re ected in the conventional wisdom about the industry. That said, less than 10% of the 3,000-plus companies operating across North America and Europe garnered over 70% of the aggregate venture capital invested.

• The amount of innovation capital arising from initial public offerings remains a modest part of overall capital raised. In 2011, there were 16 IPOs in the US and Europe with aggregate proceeds of US$857 million. Of this amount, US$227 million was raised by the industrial biotech company Solazyme, reducing the take for therapeutic and diagnostic biotech companies.

• The decline in IPOs has been well documented in many forums, including a recent cover story in The Economist which noted that the number of IPOs across all industries in the US declined from an average of 311 per year between 1980 and 2000 (a period that was also the heyday of biotech IPOs) to an average of 99 per year between 2001 and 2011. The article further points out that companies with revenues under US$50 million (the typical biotech IPO) have been hardest hit, declining from an annual average of 165 IPOs during 1980–2000 to only 30 per year in the 2001–09 period. The most commonly cited reasons for this decline are the increased regulatory burden and related ling costs. For biotech companies, however, the decline in IPOs is not attributable to increased compliance costs, but rather to market realities. Many VCs and management teams now prefer to exit by selling the company to a strategic investor rather than pursue an IPO. In addition, generalist funds often avoid biotech IPOs because of liquidity considerations or an inability to evaluate emerging technologies or regulatory/reimbursement risks. As a result, companies going public must meet the standards of an increasingly savvy group of specialist investors who can, and do, set transaction terms. This is one reason why most biotech IPOs in recent years priced below their desired offering ranges.

• The bulk of innovation capital comes from equity and convertible debt nancings of publicly traded biotech companies. This has also held reasonably steady over the past few years, though the list of companies accounting for most of the capital raised varies somewhat from year to year. In 2011, these offerings raised a total of US$9 billion, a 14% increase from 2010. Of this amount, approximately US$6 billion was raised in just 45 deals larger than US$50 million each. In 2010, there were 46 offerings larger than US$50 million, which raised US$4.8 billion in aggregate. The US was home to the vast majority of these offerings in both years.

Financing The big picture


Trend watch: evolving structures, exits and paths

The biotech industry has, by necessity, been at the forefront of novel business and financing structures over its history. Recently, many of the novel structures have centered on efficient exits for venture investors who are seeking quicker and more reliable paths to exit in the absence of an IPO market. In previous reports, we have described venture investors pursuing capital-efficient project financing structures, typically around a single asset (see, for example, the article by Francesco DeRubertis of Index Ventures in the 2009 issue of Beyond borders). More players have adopted this approach (e.g., Atlas Venture through its Atlas Development Corp.) for the right types of assets. Beyond capital efficiency, the goal is to balance the overall portfolio between assets that will “fail fast” (and fail cheaply) and those that will provide a quicker exit through a sale.

Tax minimization has not been a significant consideration for much of the history of biotech, since taxable income was a distant concept for most companies. However, as investors and companies adapt to the financing environment and seek ways to provide liquidity to investors sooner, we have seen a proliferation of tax-efficient limited liability company (LLC) structures. These structures have the advantage of allowing a company (or holding company) to sell or license multiple assets and return capital to shareholders without incurring corporate-level tax. Meanwhile, companies retain the flexibility of converting to a traditional corporate structure at a later date if an IPO becomes a real possibility. Examples of companies that have used the LLC approach include firms with licensing models such as antibody company Ablexis and Resolve Therapeutics, as well as holding company structures such as Forma Therapeutics (which reorganized itself under an LLC parent and may seek different buyers for individual programs that are held in discrete subsidiaries).

Reverse mergers have offered an alternative path to the public market, with 6–10 such transactions occurring in each of the last several years. However, regulators have tightened the listing requirements for reverse mergers, leading some companies to consider other alternatives. In 2011, Coronado Biosciences became the first biotech to take a different path. The company voluntarily registered its securities (without a public offering of stock), then sought permission to trade over the counter and subsequently pursued a listing on a national exchange. In early 2012, OvaScience initiated a similar process. This approach may become a viable alternative for companies that require a path to liquidity but want or need to avoid the time, expense and execution risk of a traditional IPO.

For a small-cap public company seeking to access the public market, announcement (or leak) of its intent to conduct a follow-on offering inevitably drives down the stock price before the deal. In the past, PIPE deals allowed companies to address this problem by conducting a privately negotiated transaction, but PIPEs have fallen out of favor with investors, who are unwilling to wait for liquidity in a volatile market. A new innovation has therefore emerged to fill the gap — the at-the-market, or ATM, offering. Under this arrangement, a company engages an investment bank to sell up to a certain number of shares in the open market (to fulfill buy orders that arise in the ordinary course of business) at prices that fall within a pre-established range. While it may take several weeks to complete the full fund-raising, depending on the daily volume of trading in the company’s stock, if managed correctly a company may achieve a better overall result.

43

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2011201020092008200720062005200420032002

5%

15%

80%

8%

17%

76%

4%

22% 22% 22%

74%

5%

73%

7%

71%

3%

26%

71%

3%

16%

3%

17%

81%79%

2%9%

89%

2%

15%

83%

US Europe Canada

Distribution of total capital raised in North America and Europe by year

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

20112010200920082007200620052004

4%

24% 24% 24%

72%

6%

71% 71%

10%

27%

15%

63%

5% 3%

82%

3%

16%

3%

22%

81%

75%

4%

15%

80%

US Europe Canada

Distribution of innovation capital raised in North America and Europe by year

Financing The big picture

Source: Ernst & Young, BioCentury, BioWorld and VentureSource.Percentages may not total to 100% due to rounding.

Source: Ernst & Young, BioCentury, BioWorld and VentureSource.Percentages may not total to 100% due to rounding. Innovation capital is the amount raised by companies with revenues of less than US$500 million.


US biotechnology financings by year (US$m)

As the US goes, so goes the world in terms of biotech financing. Capital raised in the US rose by an impressive 38%, to US$29.8 billion. However, the increase was driven by debt issuances by commercial leaders, principally Amgen (which issued debt in excess of

US$10.5 billion), Gilead Sciences (US$4.7 billion) and Illumina (US$800 million). Amgen also repaid US$2.5 billion of debt, repurchased US$8.3 billion of its common stock and paid its first-ever dividend of US$500 million.

United States

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

IPOs 456 448 1,618 626 944 1,238 6 697 1,097 814

Follow-on and other 3,442 9,986 10,337 8,110 15,242 8,944 4,250 8,745 6,313 8,199

Debt 2,564 53 9 2,857 282 5,930 4,641 3,421 9,717 16,395

Venture 2,164 2,826 3,551 3,328 3,302 5,464 4,445 4,556 4,409 4,352

Total 8,626 13,313 15,515 14,922 19,770 21,576 13,342 17,419 21,537 29,760


45Financing United States

US innovation capital flatlines, even as total funding rises sharply

0

5

10

15

20

25

30

35

20112010200920082007200620052004

US$

b


Innovation capital, while increasing slightly in 2011, has reached a plateau of approximately US$14 billion annually in the US — virtually unchanged from the levels seen before the financial crisis, with the exception of 2007. Significant transactions in 2011 included convertible debt issuances by Dendreon (US$620 million), Human Genome Sciences (US$495 million) and Regeneron Pharmaceuticals (US$560 million) as these companies ramped up commercial operations. The industry also saw 11 follow-on equity offerings of greater than US$100 million each, led by the US$258 million raised by Ariad Pharmaceuticals and four venture

rounds of around US$100 million each (Tesaro, Ascletis, Intrexon Corp. and Portola Pharmaceuticals). Ascletis, which received an initial US$50 million tranche, is a particularly interesting story, as the company’s business plan is built around operating in both the US and China, and the majority of the investment came from investors in China. As noted previously, the largest IPO of the year was the US$227 million raised by industrial biotech Solazyme, while Clovis Oncology had the largest IPO by a therapeutics company (US$139 million) as well as a subsequent follow-on offering of US$75 million.



Source: Ernst & Young, BioCentury, BioWorld, Windhover and VentureSource. Figures in parentheses are number of financings. Numbers may appear inconsistent because of rounding.

Quarterly breakdown of US biotechnology financings (US$m), 2011

First quarter Second quarter Third quarter Fourth quarter Total

IPOs $295(5)

$287(2)

$49(1)

$182(2)

$814(10)

Follow-on and other $3,374(56)

$1,923(57)

$720(29)

$2,183(40)

$8,199(182)

Debt $1,176(23)

$3,514(17)

$457(17)

$11,248(23)

$16,395(80)

Venture $966(79)

$1,200(72)

$819(78)

$1,366(83)

$4,352(312)

Total $5,811(163)

$6,924(148)

$2,046(125)

$14,979(148)

$29,760(584)

Macroeconomic trends are evident in the pattern of capital raised during 2011, as growing confidence in the economy prompted increasing investment in the latter half of 2010 and the first half of 2011. However, that forward momentum slowed significantly in the second half of the year (with the exception of debt offerings by commercial leaders) as public market investors sought lower-risk investments in the wake of the debt ceiling debate in the US Congress and the growing economic challenges in the Eurozone. Venture capital — with its inherently longer-term view of the world — held steady through 2011.

47

Capital raised by leading US regions, 2011There is a haves-and-have-nots story even within the ranks of companies raising innovation capital. The equivalent chart in prior years’ reports has presented total capital raised and venture capital raised on the two axes. This year, we replaced total capital raised with innovation capital raised — effectively removing the skewing effect of the large financings of commercial leaders. This had a dramatic impact on Los Angeles/Orange County, which was typically an outlier on the top left hand corner of the chart because of Amgen’s debt transactions. New England, San Francisco Bay Area and San Diego retain their positions as the three leading clusters for venture capital raised.

Source: Ernst & Young, BioCentury and VentureSource.Size of bubbles represents number of financings per region. Innovation capital is the amount raised by companies with revenues of less than US$500 million.

Inno

vati

on c

apit

al r

aise

d (U

S$b)

Venture capital raised (US$m)1,200 1,400 1,600 1,800 2,0000 200 400 600 800 1,000

0

1.0

0.5

1.5

2.0

2.5

3.0

3.5

4.0

Pacific Northwest

San Diego

New JerseyNew York State

Mid-Atlantic

San Francisco Bay Area

Los Angeles/Orange County

New England

Financing United States


US biopharmaceutical venture capital as a share of total venture capital by year

US biotechnology IPOs by year

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

2011201020092008200720062005

While the amount of innovation capital and venture capital raised by biotech has held steady in recent years, the industry’s share of total venture capital raised has fallen over the last two years. In 2011, biopharmaceutical companies attracted 12% of US venture capital, down from 13% in 2010 and 17% in 2009. This represents the lowest share that the industry has garnered in the last seven years. The share of venture capital raised by health care companies showed a similar decline, from 28% in 2010 to 26% in 2011.

In 2009 and 2010, the US IPO market rebounded from its 2008 financial-crisis depths. In 2011, however, the market retreated both in terms of the number of completed deals and the aggregate proceeds raised. The median amount raised in 2011 was US$55 million (similar to the prior year’s US$52 million) and the smallest transaction was US$40 million. 0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

Capi

tal r

aise

d in

IPO

s (U

S$b)

Num

ber o

f dea

lsCapital raised Number of deals

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 20110

5

10

15

20

25

30

Source: VentureSource.

Source: Ernst & Young, BioCentury, BioWorld and VentureSource.

49

The vast majority of 2011 US IPOs priced below their desired ranges

Only Solazyme drew enough investor interest for its IPO to price above the expected range in 2011, while Fluidigm Corp. and Clovis Oncology priced within their expected ranges. In the remaining transactions, investors required companies to reset their expectations of value and in some cases issue additional shares so that proceeds would be sufficient to fund operations to the next meaningful development milestone.

$0

$5

$10

$15

$20

PC

RX

ECY

T

BG

MD

AC

RX

FLD

M

TZY

M

SZY

M

HZ

NP

NLN

K

CLV

S

Source: Ernst & Young, finance.yahoo.com and media reports. Vertical lines indicate IPO filing ranges; horizontal dashes indicate offer prices.

Financing United States


2011 US IPO performance

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

+10%

+20%

+30%

CLVSNLNKHZNPSZYMTZYMFLDMACRXBGMDECYTPCRX

31 D

ecem

ber 2

011

clos

ing

pric

e re

lativ

e to

offe

r pric

e

Despite lower-than-expected IPO prices on debut, most new listings declined significantly by the end of 2011, further dampening investor enthusiasm for more new listings. Overall, the IPO class of 2011 traded down 22% through the end of 2011. However, this has improved to just a 1% decline as we go to press at the end of May 2012. Two-thirds of companies that went public over the last three years are now trading below

their IPO prices, and 40% lost more than half of their value by the end of 2011 (the overall performance is a decrease of 25%). The companies suffering the biggest declines fall into two categories: commercial-stage companies that have missed revenue growth expectations and development-stage companies that have had clinical setbacks on their lead, and in some cases only, product candidate.

Source: Ernst & Young and Capital IQ.

51Financing Europe

European biotechnology financings by year (US$m)

In contrast to the US, financing in Europe has not regained the levels seen prior to the financial crisis. A retreat in the public markets in 2011 resulted in overall financing levels that are back to those seen in 2008 — the height of the global financial crisis — reflecting the continuing struggles of the Eurozone countries over the sovereign debt of some member countries. While the biotechnology sectors of these countries are relatively small, the uncertainty has driven investors across the continent to seek lower risk. One bright spot is that, similar to the US, Europe has seen venture capital hold relatively steady.

Across Europe, there were 56 venture rounds of greater than US$5 million (down from 65 in 2010). The most significant venture capital transactions included US$139 million raised by Symphogen (Denmark), US$99 million raised by Biocartis (Switzerland) and US$96 million raised by Circassia (United Kingdom). In aggregate, biotech accounts for approximately 15% of total venture capital investment across Europe, a slightly higher percentage than in the US in 2011. European companies issued US$393 million in debt, about two-thirds of which came from Switzerland-based Actelion.

Europe

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

IPOs 136 36 454 995 853 1,021 111 143 219 43

Follow-on and other 126 1,769 2,196 1,587 3,141 4,600 872 1,892 1,792 1,134

Debt 63 39 24 100 279 319 108 654 396 393

Venture 1,259 1,064 1,860 1,776 1,872 1,821 1,531 1,091 1,371 1,321

Total 1,585 2,908 4,534 4,459 6,146 7,761 2,622 3,779 3,778 2,891



European innovation capital by year

Reflecting the fact that Europe has fewer large commercial stage companies, the vast majority of all capital raised meets our definition of innovation capital. Capital raised by commercial leaders in 2011 includes a US$265 million debt transaction by Actelion Pharmaceuticals.

0

1

2

3

4

5

6

7

8

9

20112010200920082007200620052004

US$

b



53

The year began strong for Europe, as capital raised in the first quarter of 2011 represented an increase of approximately 18% over the fourth quarter of 2010. However, concerns about overall economic conditions caused a precipitous decline in funding beginning in the second quarter. This was particularly marked in the public markets, where investors became more risk averse in the face of mounting concerns about recession and debt defaults. These conditions had less of an impact on venture capital investing, since VCs can take a longer-term view and increasingly expect to achieve returns from strategic sales rather than the equity markets.

European biotechnology IPOs by year

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Capi

tal r

aise

d in

IPO

s (U

S$b)

Num

ber o

f dea

ls

Capital raised Number of deals

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 20110

5

10

15

20

25

30

The IPO market has been virtually closed in Europe since the financial crisis, with no improvement expected in the near term. Many of the transactions that have been completed in recent years were listed on alternative market exchanges with lower listing standards. The 2011 IPOs took place on such exchanges in Sweden and Israel and raised less than US$15 million each.

Financing Europe


IPOs $30(4)

$12(2)

$0(0)

$0(0)

$43(6)

Follow-on and other $606(31)

$284(21)

$139(20)

$105(19)

$1,134(91)

Debt $72(3)

$50(5)

$2(2)

$268(2)

$393(12)

Venture $455(40)

$190(39)

$252(37)

$423(37)

$1,321(153)

Total $1,164(78)

$537(67)

$394(59)

$796(58)

$2,891(262)

Quarterly breakdown of European biotechnology financings (US$m), 2011

Source: Ernst & Young, BioCentury, BioWorld, Windhover and VentureSource.Figures in parentheses are number of financings. Numbers may appear inconsistent because of rounding.

Source: Ernst & Young, BioCentury, BioWorld and VentureSource.


Capital raised by leading European countries, 2011

As in prior years, the UK led Europe in number of financing rounds and venture capital raised. The venture amount raised in 2011 rose slightly from 2010. Switzerland retains its perennial strength in venture capital and rose up the rankings due to the debt offering of Actelion. The size and position of the remaining countries is heavily dependent on whether a single large investment occurs in any particular year.

Source: Ernst & Young, BioCentury and VentureSource.Size of bubbles represents number of financings per country.

Tota

l cap

ital

rai

sed

(US$

b)

Venture capital raised (US$m)250 3000 50 100 150 200

0

0.1

0.2

0.3

0.4

0.5

0.6

Sweden

Netherlands

Denmark

France

Germany

Austria

Switzerland

United Kingdom

55Financing Canada

Canadian biotechnology financings by year (US$m)

Canada

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

IPOs 10 0 85 160 9 5 0 0 0 0

Follow-on and other318 1,139 435 537 1,589

703 238 633 392 447

Debt 0 9 3 4 127

Venture 199 206 271 313 205 352 207 97 87 165

Total 527 1,345 791 1,010 1,803 1,060 453 733 482 739

Source: Ernst & Young, Canadian Biotech News and company websites.Numbers may appear inconsistent because of rounding. Separate subtotals for “follow-on and other” and “debt” are not available prior to 2007.

In 2011, Canadian public biotech companies raised US$574 million, a US$178 million increase over 2010. Fifteen public companies raised 80% of the total public financing take, including Atrium Innovations, which conducted a large debt transaction. This represents an improvement over 2010, when most of the public company financing went to just eight companies. Private companies raised more than US$165 million, which represents a 91% increase over 2010. In addition, 2012 is already off to a strong start with just over US$50 million in investments announced.

The Canadian government, along with several of the provinces, announced various programs to help stimulate innovation in the sector. Some big pharma companies have also partnered with the public sector to create investment funds that should result in increased investments in private companies. Similar to trends in the US, there has been an increase in venture financings of single-product companies with lean operations that focus on advancing a technology or molecule in the most capital-efficient manner possible. With a complete dearth of IPOs over the last five years, the focus of venture investors is clearly on positioning companies and their technologies for acquisition.


Capital raised by leading Canadian biotech clusters, 2011

The relative position of leading clusters changed in 2011. Quebec moved into first place in total capital raised on the strength of Atrium Innovations’ large debt financing. On the venture capital front, Montréal and Vancouver switched places relative to their 2010 standings, with Montréal taking the lead.

Tota

l cap

ital

rai

sed

(US$

m)

Venture capital raised (US$m)40 50 60 70 800 10 20 30

0

100.0

50.0

150.0

200.0

250.0

Québec

Calgary

Toronto

Ottawa

Montréal

Vancouver

Source: Ernst & Young, BioCentury and VentureSource.Size of bubbles represents number of financings per country.

57

Quarterly breakdown of Canadian biotechnology financings (US$m), 2011

On a quarterly basis, the total amounts raised in 2011 were relatively consistent for three of the four quarters and approximated quarterly amounts in 2010. Financings in the third quarter in 2011 were double those of the other three quarters. Based on a preliminary review of the first quarter of 2012, the upward trend observed in 2011 appears to be continuing.


IPOs $0(0)

$0(0)

$0(0)

$0(0)

$0(0)

Follow-on and other $121(23)

$125(17)

$105(15)

$97(19)

$447(74)

Venture $40(7)

$2(4)

$102(10)

$21(5)

$165(26)

Debt $4(1)

$1(1)

$116(4)

$6(4)

$127(10)

Total $165(31)

$128(22)

$323(29)

$124(28)

$739(110)

Source: Ernst & Young, BioCentury, BioWorld and Venture One.Figures in parentheses are number of financings. Numbers may appear inconsistent because of rounding.

Financing Canada

59Deals The big picture

Deals

Pharma recalibratesThe big picture

Mergers and acquisitions

Based on the overall numbers, merger and acquisition (M&A) activity in the biotech industry looked robust in 2011. The number of pharma-biotech and biotech-biotech M&As in the US and Europe increased from 49 in 2010 to 57 in 2011, while their total value grew from US$20 billion to about US$25 billion over the same time period (after normalizing the numbers by removing US$31 billion of megadeals from the 2011 totals). The US$25 billion in megadeal-adjusted M&A transactions represents the second-highest total in the last six years, second only to 2008, when the industry announced US$28 billion of M&A deals.

But the overall numbers mask some troubling trends. In particular, big pharma was conspicuously absent from the buyer’s table in 2011, with many of the largest

deals being driven by non-big pharma acquirers (e.g., Teva Pharmaceutical Industries, Grifols and Forest Laboratories). Given the critical role that big pharma could play in supporting the biotech innovation ecosystem (discussed in this year’s Point of view article) and the fact that the expected exit for most venture investors is an acquisition, this lack of activity is unsettling. With big pharma in the midst of crossing the long-awaited patent cliff, many observers assumed that we would witness a more pronounced upsurge in transactions — particularly for targets with product revenue or very late-stage product candidates. In this light, it’s remarkable how few pharma-biotech acquisitions actually occurred in 2011. Only Sanofi’s acquisition of Genzyme (which really played out in 2010 but did not get finally negotiated and closed until 2011) entered the ranks of the year’s 10 largest deals. Even more noteworthy, big pharma was the buyer in only 7 of the year’s 57 M&A transactions.

We are unlikely to see many (if any) additional megadeals involving big pharma in the foreseeable future, as most companies have announced their intention to focus on smaller “tuck-in” deals (acquisitions of products and technologies) valued below US$5 billion, and quite often below US$1 billion (e.g., Merck & Co.’s acquisition of Inspire Pharmaceuticals and Novartis’ purchase of Genoptix in 2011). This trend continued to be visible in early 2012 with GlaxoSmithKline taking a run at Human Genome Sciences with a US$2.6 billion offer, and Bristol-Myers Squibb Co. buying Inhibitex for US$2.5 billion and reportedly offering US$3.5 billion for Amylin Pharmaceuticals (which, according to media reports, subsequently attracted the interest of other bidders as well.)

The reasons for big pharma’s focus on more modest-sized deals are varied. Many big players have taken on more debt thanks to large mergers in prior years (e.g., Pfizer/

0

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30

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Biotech-biotechPharma-biotech Pharma-biotech megadeals Biotech-biotech megadeals

Pote

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S$b)

Num

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of d

eals

2006 2007 2008 2009 2010 2011

Number of deals

0

10

20

30

40

50

60

70

US and European M&As, 2006-11

Source: Ernst & Young, Capital IQ, MedTRACK and company news.Chart excludes transactions where deal terms were not publicly disclosed.


Wyeth, Merck/Schering-Plough, Novartis/Alcon, Roche/Genentech). In addition, all of the big pharmas are focused on rationalizing their operations and seeking new markets for growth (including pursuing deals in emerging markets). As mentioned in the Point of view article, this increased debt load combined with slowing revenue growth and the need to maintain dividends and stock buybacks has resulted in a decrease in acquisition firepower of the pharma industry by as much as 30%, according to an internal Ernst & Young analysis. And of course previous consolidation in the industry has reduced the absolute number of buyers with the scale to execute a large transaction.

Meanwhile, the market caps of biotech commercial leaders (companies with revenues in excess of US$500 million — essentially the only firms that are likely to move the needle on big pharma revenues) are high enough to ensure that there are no

bargains to be had. Gilead Sciences, Biogen Idec and Celgene Corp. all have market caps of more than US$30 billion, while Amgen’s value rivals that of several big pharma companies. Such valuations effectively place these companies out of reach of most big pharma acquirers, especially when one factors in a premium and accounts for pharma’s reduced firepower. The next tier of commercial leaders valued above US$5 billion includes Alexion Pharmaceuticals (an orphan-drug-focused company with one product on the market), with a value in excess of US$17 billion, up nearly 100% over the last 12 months; and Vertex Pharmaceuticals, valued above US$13 billion, a nearly 20% rise from the previous year. These market values likely reflect optimism regarding a takeover, but given that only Genentech and Genzyme have been purchased for values above US$15 billion in the history of the industry, deals of this magnitude cannot be considered likely. In Europe, Shire also has a value above

US$16 billion, although its stock price has remained relatively flat over the last year. Actelion Pharmaceuticals, with a market cap of US$5 billion, has seen its stock under pressure over the last year. Other European firms with significant market caps include Elan Corp., Novozymes and Qiagen.

So who was active in M&A deals? In the relative absence of big pharma, acquirers included: big biotech firms (Amgen, Gilead Sciences, Cephalon, Alexion and Shire); generic/specialty pharma players (the previously mentioned Teva and Forest); Japanese pharma companies (Daiichi Sankyo, Kyowa Hakko Kirin and Takeda Pharmaceuticals) seeking technologies and sources of growth beyond the domestic market where they have traditionally been strong; diagnostic companies (Quest Diagnostics); and even a food company (Nestlé).

Company Country Acquired or merged company

Country Total potenial value (US$m)

CVRs/milestones (US$m)

Sanofi France Genzyme US 20,100 3,800

Gilead Sciences US Pharmasset US 11,200 –

Teva Pharmaceutical Industries Israel Cephalon US 6,200 –

Grifols Spain Talecris Biotherapeutics US 4,000 -

Forest Laboratories US Clinical Data US 1,200 –

Alexion Pharmaceuticals US Enobia Pharma Canada 1,080 470

Alkermes US Elan Drug Technologies Ireland 1,000 –

Amgen US BioVex US 1,000 575

Daiichi Sankyo Japan Plexxikon US 935 130

Shire UK Advanced Biohealing US 750 ND

Quest Diagnostics US Celera US 657 ND

Gilead Sciences US Calistoga Pharmaceuticals US 600 225

Cephalon US Gemin X Pharmaceuticals US 525 300

Bristol-Myers Squibb US Amira Pharmaceuticals US 475 150

Selected M&As, 2011

Source: Ernst & Young, Capital IQ, MedTRACK and company news.“Total potential value” includes up-front, milestone and other payments from publicly available sources. “ND” refers to deals where CVR/milestone amounts were not publicly disclosed.


Premiums, multiples and risk sharing

Gilead Sciences made a huge splash with its fourth-quarter offer for hepatitis C virus company Pharmasset for a startling US$11.2 billion — an 89% premium over the value the company was trading at prior to the deal announcement, and well above the industry’s average deal premium. By contrast, the other significant transactions of 2011, Sanofi/Genzyme and Teva/Cephalon, had premiums of 48% and 39%, respectively. After a protracted negotiation, Sanofi paid a premium of five times Genzyme’s sales. While this is in the range of other biotech tie-ups, it is substantially higher than the multiples seen in big pharma mergers such as Pfizer/Wyeth (3x) or Merck/Schering (2.2x), indicating higher growth expectations for the Genzyme business.

In last year’s report, we noted the increased use of post-close milestones to help bridge valuation gaps between buyers and sellers. It is interesting to note that all of the largest acquisitions of private companies included in the chart on page 60 and two of the public-company acquisitions (Sanofi/Genzyme and Forest Labs/Clinical Data) used milestones.

Not afraid

In last year’s report, we also commented on the emergence of hostile takeovers in biotech, beginning with the Astellas acquisition of OSI Pharmaceuticals (which ultimately became friendly after a period of negotiation). While Sanofi and Genzyme were ultimately able to negotiate a deal that was acceptable to both parties, the prospect of Sanofi taking the offer directly

to Genzyme’s shareholders was certainly present during the deliberations. In 2011, Cephalon negotiated a deal to be acquired by Teva Pharmaceuticals in the year’s third-largest transaction after defending against a hostile bid from Valeant Pharmaceuticals. In early 2012, GlaxoSmithKline took its appeal directly to shareholders after Human Genome Sciences rejected its bid. In the past, biotech M&As were rarely hostile because of the fear of losing key scientists or other employees — some of the target’s most valuable assets — during an extended battle. The newfound willingness to go hostile suggests that suitors are often placing most of the value of the transaction on commercialized products.


Strategic alliances

Fewer deals, smaller deals

By now, every large pharma company has embraced a strategy that involves externalizing more of its R&D as part of an effort to reverse the multiyear decline in pipeline productivity. These strategies include many elements: direct alliances with smaller biotechs, corporate venture capital, enhanced relationships with leading academic institutions, outsourcing of non-core activities, and even arrangements with payers to access patient-level “real-world” data. While the ultimate payoff of these efforts will not be known for many years, the early pipeline progress appears to be encouraging.

With all the attention on externalization, one might expect the volume and value of strategic alliances with biotech companies to be increasing. In reality, the opposite has occurred. The number of strategic alliance transactions declined for the second straight year, and the potential “biobucks” value of these deals hit a six-year low.

Of course, biobucks numbers may not be the best marker of deal trends, given the “creative accounting” that occurs in many deal announcements. It is therefore even more distressing that 2011

saw a significant fall-off, for the second year running, in announced up-front payments. Up-fronts fell to US$2.1 billion in 2011, approximately 64% below the level in 2009. Abbott’s US$400 million up-front payment to Reata for a portfolio of preclinical compounds comprised 19% of the total up-front payments for the year. In aggregate, up-front payments made by pharma companies to biotech companies as part of strategic alliance transactions have declined from a high of US$5.3 billion in 2009 to US$1.6 billion in 2011.

Clearly, strategic alliances are still important to both pharma and biotech companies, but the overall trends indicate that pharmaceutical buyers are being more selective in their deal interests and are focused on negotiating up-front payments that reflect only the value that has been proven to date – presumably with more consideration reflected in downstream, success-based milestones. For biotechs, while an alliance transaction is still considered to be a validation of the company’s technology, the reduced capital flows from licensing increase the importance of capital efficiency.

Num

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2006 2007 2008 2009 2010 2011

Number of dealsPharma-biotech Biotech-biotech

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Source: Ernst & Young, Capital IQ, MedTRACK and company news.Chart shows potential value, including up-front and milestone payments, for alliances where deal terms are publicly disclosed.

US and European strategic alliances based on biobucks, 2006-11


Company Country Partner Country Total potential value (US$m)

Up-front payments (US$m)

Vertex Pharmaceuticals US Alios BioPharma US 1,525 60

Astellas Pharma Japan Aveo Pharmaceuticals US 1,425 125

Les Laboratoires Servier France miRagen Therapeutics US 1,000 ND

Johnson & Johnson US Pharmacyclics US 975 150

Amgen US Micromet US 967 14

Les Laboratoires Servier France Xoma US 885 35

Roche Switzerland Evotec Germany 830 10

Takeda Pharmaceutical Japan Intra-Cellular Therapies US 750 ND

Roche Switzerland Array BioPharma US 713 28

Merck KGaA Switzerland F-star Austria 692 ND

GlaxoSmithKline (GSK) UK Epizyme US 650 20

Pfizer US Theraclone Sciences US 632 ND

Pfizer US Santaris Pharma Denmark 614 14

Johnson & Johnson US Aveo Pharmaceuticals US 555 15

Big biobucks alliances, 2011

Source: Ernst & Young, MedTRACK and company news.“Total potential value” includes up-front, milestone and other payments from publicly available sources. “ND” refers to deals where up-front amounts were not publicly disclosed.


Alliances with big up-front payments, 2011

Source: Ernst & Young, MedTRACK and company news.“Total potential value” includes up-front, milestone and other payments from publicly available sources.

Company Country Partner Country Up-front payments (US$m)

Abbott Laboratories US Reata Pharmaceuticals US 400

Johnson & Johnson US Pharmacyclics US 150

Astellas Pharma Japan Aveo Pharmaceuticals US 125

Celgene US Elan Corp. Ireland 78

Valeant Pharmaceuticals Canada Meda Sweden 76

Astellas Pharma Japan Optimer Pharmaceuticals US 68

Salix Pharmaceuticals US Progenics Pharmaceuticals US 60

Allergan US MAP Pharmaceuticals US 60

Vertex Pharmaceuticals US Alios BioPharma US 60

Human Genome Sciences US Five Prime Therapeutics US 50

Mundipharma International UK Allos Therapeutics US 50


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Pharma-biotech Biotech-biotech Up-fronts/biobucks

2006 2007 2008 2009 2010 20110%

2%

4%

6%

8%

10%

12%

14%

16%

US and European strategic alliances based on up-front payments, 2006–11

Source: Ernst & Young, Windhover Information, MedTRACK and company news.


Breakups

While alliance transactions are frequently terminated early, and the product candidate returned to the biotech, this is usually because of a clinical setback or a strategic portfolio review after a change in ownership or management. Often the end of the alliance does not mean the end of the product, and several biotechs have regrouped, reinvested and even re-partnered a returned asset. One of the largest transactions of 2011, however, involved a termination related to an approved product. Amylin Pharmaceuticals and Eli Lilly and Company terminated their long-standing deal related to the diabetes drugs Byetta and Bydureon (which won FDA approval shortly after the breakup). Amylin agreed to pay US$250 million up-front, including royalties of 15% and other future consideration.

Similar territory — new deals for a new market

The regulatory pathway for biosimilars and the time and cost to obtain marketing approval is still uncertain in many markets, including the US. Nevertheless, in 2011, companies began staking out their biosimilar alliances. Biotech commercial leaders Amgen and Biogen Idec struck deals that take advantage of their biologic development and manufacturing expertise while leveraging the financial resources of other companies (Watson Pharmaceuticals and Samsung, respectively). Baxter’s alliance with Momenta Pharmaceuticals was motivated by the desire to access the biotech company’s cutting-edge analysis technology, which allowed Momenta to assist partner Sandoz in obtaining approval for a generic version of Lovenox (a complex mixture drug) without the need for extensive clinical trials to prove equivalence.

67Deals United States

US M&As, 2006-11

While the headlines were captured by the year’s megadeals — the Sanofi/Genzyme saga, which concluded with a negotiated agreement in the first quarter, and the offer by Gilead Sciences to acquire Pharmasset in the fourth quarter — 2011 was very strong on the US M&A front, even without these large transactions. The number of M&A deals rebounded to 37 from a low of 26 in 2010. The increase in megadeal-adjusted aggregate deal values was driven by the acquisitions of biotech commercial leaders Cephalon and Talecris Biotherapeutics, as well as Forest Laboratories’ acquisition of Clinical Data for US$1.2 billion. In 2011, the median value of acquisitions of US-based biotech companies was US$370 million (including the potential value of post-close milestones), compared to US$135 million in 2010 and only US$95 million in 2009.

United States

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US strategic alliances based on biobucks, 2006-11

The number of alliances with announced deal terms decreased by 10% in 2011, building on a 14% decline the prior year. Even more striking, aggregate potential deal values plummeted to a level not seen for at least the last five years. It is probably reasonable to assume that biobucks were calculated and disclosed in a similar manner over the last six years, and this decline reflects fewer large transactions (nine deals with US biotechs in 2010 had biobuck values above US$1 billion) as well as lower up-front payments, as can be seen in the next chart.

Licensors in strategic transactions have clearly become more price sensitive in recent years, with the aggregate value of up-front payments declining for the third year running from the high-water mark in 2008. The up-fronts received by US biotechs on the sell side of strategic alliance transactions declined by approximately US$1.5 billion compared to 2009, a sum which has not been made up by increased funding from the capital markets, as discussed in the financing section of this report.

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2006 2007 2008 2009 2010 20110

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US strategic alliances based on up-front payments, 2006-11

Valu

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69Deals Europe

European strategic alliances based on biobucks, 2006-11

The number of strategic alliances involving European biotechs fell to a six-year low in 2011, as did the aggregate biobucks values of those transactions. The 29% decline in number of deals is in contrast to a 16% increase in the number of deals in 2010. Merck KGaA and France-based Ipsen Pharmaceuticals closed three deals each with European biotechs, while a number of big pharma companies did two transactions each.

Despite the decline in the number of strategic alliances, announced up-front payments were largely unchanged in 2011 as compared to 2010. European companies on the sell side of alliances, however, garnered up-front payments of US$461 million, a significant decline from the US$621 million received in 2010 and the US$2.5 billion received in 2009 (which included nearly US$900 million received by Elan Corp. in a transaction with Johnson & Johnson).

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Pharma-biotech Biotech-biotech Number of deals

2006 2007 2008 2009 2010 20110

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European strategic alliances based on up-front payments, 2006-11

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European M&As, 2006-11

M&A activity in Europe also improved in 2011 for the second straight year. There were 22 transactions with announced deal terms, an increase from the 17 seen in each of the two previous years. The improvement in aggregate deal values was largely driven by Grifols’ acquisition of US-based Talecris Biotherapeutics. Only one of the 19 acquisitions of European biotechs was by a big pharma company. The median deal size of biotech companies sold was US$84 million, up from US$65 million in 2010. Only four transactions involving the sale of a European biotech included meaningful post-closing milestone payments, which is in contrast to the high percentage of private-company acquisitions in the US that included milestones.

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201120102009200820072006

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71

CanadaIn 2011, Canadian M&A activity remained consistent with the levels seen in recent years. Significant transactions included those by Paladin Labs, which acquired Laval-based Labopharm for US$20 million, and Valeant Pharmaceuticals, which outbid Paladin Labs to purchase Edmonton-based Afexa Life Sciences for US$76 million.

Two private Canadian companies were also acquired in 2011, providing very significant sums to their early investors at closing and the prospect of even higher returns if downstream milestones are achieved. Gemin X Pharmaceuticals was acquired by Cephalon (just prior to Cephalon itself being acquired by Teva Pharmaceutical Industries) for US$225 million up-front and up to US$300 million

in milestones. Meanwhile, Montreal-based Enobia Pharma was acquired by Alexion Pharmaceuticals for US$610 million up-front and up to US$470 million in milestones. Given the lack of an IPO market, these exits were certainly welcome news for Canadian venture capital investors.

Contrary to 2010, there were only a few licensing agreements in 2011 involving Canadian biotech companies. For instance, both Paladin Labs and Bioniche Life Sciences in-licensed product rights for specific territories.

Deals Canada

Products and pipeline

73Products and pipeline


Promising signsThe big picture

For much of its history, biotechnology has attracted researchers, entrepreneurs, investors and strategic partners because of its promise — the game-changing potential of innovative platforms and targeted, vastly efficacious therapies. In recent years, however, investors have been less allured by biotech’s promise and more concerned about paths to commercialization and returns on investment. This has, at least in part, been driven by concerns about an uncertain regulatory environment.

In 2011, there were signs of a different kind of promise. The US Food and Drug Administration (FDA) approved more new drugs than at any time since 2004, when the recalls of Vioxx and other COX-2

inhibitors spawned the current environment of heightened concerns about drug safety. The agency also reported progress on the speed with which these new medicines were approved — all but one of the drugs approved in fiscal year 2011 were approved on or before their target dates, and 70% of them were approved in the US before they received approval anywhere else in the world.

These are certainly encouraging developments, and continued progress on this front will be a critical part of the answer to the challenge of sustaining biotech innovation. While the FDA pointed out that “over half” of the drugs approved in FY2011 were approved on the first cycle of review (i.e., without requests for additional information) the industry remains

concerned about the unpredictability of the requests for additional information, adding to the cost, time and risk of drug development.

Ultimately, an approval process that is more transparent, predictable and timely is not just important for sustaining biotech innovation. With aging populations and large unmet medical needs, an efficient regulatory regime will be required to develop cures for neurodegenerative diseases such as Alzheimer’s disease and Parkinson’s disease and more targeted and efficacious treatments for chronic ailments such as diabetes. By making such changes, regulators will help the industry fulfill another promise — its commitment to bring patients better treatments and cures to address their most critical ailments.


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2011201020092008200720062005200420032002200120001999199819971996

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New molecular entities Biologic license applications

Source: Ernst & Young, FDA.US product approvals are based on CDER approvals only.

FDA product approvals, 1996–2011

The FDA approved 24 new molecular entities and 6 biologic license applications in 2011 — the second-highest total in the last dozen years.

75

Selected FDA approvals, 2011Company Brand name Generic name Type of approval Indication Month

Centocor Ortho Biotech (Johnson & Johnson)

ZYTIGA Abiraterone acetate New molecular entity Late stage prostate cancer April

Human Genome Sciences BENLYSTA Belimumab New biologic license

applicationSystemic lupus erythematosus March

Merck & Co. VICTRELIS Boceprevir New molecular entity Hepatitis C May

Vertex Pharmaceuticals INCIVEK Telaprevir New molecular entity Hepatitis C May

Optimer Pharmaceuticals DIFICID Fidaxomicin New molecular entity Clostridium difficile-

associated diarrhea May

Johnson & Johnson XARELTO Rivaroxaban New molecular entity Non-valvular atrial fibrillation July

Regeneron Pharmaceuticals EYLEA Aflibercept New biologic license

applicationNeovascular “wet” age-related macular degeneration November

Source: Ernst & Young, FDA and company websites.

There were a number of noteworthy drugs approved in 2011, including two new medications for hepatitis C, a viral infection that affects an estimated 130 million–170 million people, or approximately 3% of the world’s population. Massachusetts-based Vertex Pharmaceuticals’ much-anticipated Telaprevir was approved in May, and sales of the new product soon catapulted Vertex into the ranks of the industry’s

commercial leaders. (See the Financial performance section.) Earlier that same month, Merck & Co. gained approval for its competing drug, Victrelis (boceprevir), setting up a contest between the two products.

Reflecting the strength of the industry’s pipeline in oncology, a number of the new approvals were for various types of cancer. One of the promises of applying

genetic engineering techniques in this area is, of course, the potential for personalized medicine approaches that are many shades more efficacious in specific cancer subtypes. In this regard, it is worth noting that two of the year’s cancer approvals were approved with companion diagnostics: Genentech/Roche’s Zelboraf (vemurafenib) for late-stage melanoma and Pfizer’s Xalkori (crizotinib) for late-stage lung cancer.



Selected orphan drug approvals by the FDA, 2011Company Brand name Generic name Type of approval Indication Month

Bristol-Myers Squibb YERVOY Ipilimumab New biologic license application Metastatic melanoma March

IPR Pharmaceuticals CAPRELSA Vandetanib New molecular entity Advanced medullary thyroid cancer April

Bristol-Myers Squibb NULOJIX Belatacept New biologic license application

Prevent organtransplant rejection June

Seattle Genetics ADCETRIS Brentuximab vedotin New biologic license application

Hodgkin lymphoma and systemic anaplastic large cell lymphoma

August

Roche ZELBORAF Vemurafenib New molecular entity Metastatic melanoma August

Shire FIRAZYR Icatibant acetate New molecular entity Hereditary angioedema August

Pfizer XALKORI Crizotinib New molecular entity Late stage lung cancer August

ApoPharma Ferriprox Deferiprone New molecular entity Thalassemia October

Lundbeck ONFI Clobazam New molecular entitySeizures associated with Lennox-Gastaut syndrome

October

Incyte Jakafi Ruxolitinib New molecular entity Myelofibrosis November

EUSA Pharma ERWINAZE Asparaginase Erwinia chrysanthemi

New biologic license application

Acute lymphoblastic leukemia November

Source: Ernst & Young, FDA and company websites.

It is also noteworthy that 11 of the year’s drug approvals were approved with orphan designations. The economics of orphan drugs are changing dramatically as the focus in the health care ecosystem shifts to health outcomes. Even at a time of escalating pricing pressures, payers have so far been willing to pay high prices for life-saving treatments, particularly in disease areas where no cures have previously existed and where the prevalence of very small patient populations means there is little impact on overall costs.

77

Source: Ernst & Young, MedTRACK and company websites.

Cancer32%

Neurology13%

Infectious disease7%

Metabolic and endocrine

7%

Autoimmune4%

Cardiovascular3%

Respiratory3%

Other31%

US Phase III pipeline by indication, 2011

US clinical pipeline by indication, 2011 As in prior years, cancer continues to dominate the US clinical pipeline. Not surprisingly, cancer is the area where science has made the greatest progress in understanding and classifying disease into subtypes based on specific genetic mutations. Cancer also remains attractive because the relatively small patient populations imply smaller clinical trials and the large unmet medical needs can give companies more traction in the market. Neurology, which ranks second, will become increasingly important in the years ahead, as aging populations increase the need for cures for a number of neurodegenerative diseases.



Cancer44%

Neurology10%



6%

Autoimmune4%

Cardiovascular4%

Respiratory4%

Other19%



Cancer33%

Neurology12%



7%

Autoimmune14%

Cardiovascular6%

Respiratory3%

Other15%

European clinical pipeline by indication, 2011


Cancer29%

Neurology11%

Infectious disease6%Metabolic and

endocrine9%

Autoimmune16%

Cardiovascular8%

Respiratory3%

Other18%

European Phase III pipeline by indication, 2011

The European pipeline by indication looks fairly similar to that of the US, with cancer on top and neurology in second place.

2008 2009 2010 2011

0

100

200

300

400

500

600

700

Phase IIIPhase IIPhase I

Num

ber

of p

rodu

ct c

andi

date

s in

stu

dies


European clinical pipeline by year The clinical pipeline of European biotechnology companies continues to grow on an overall basis. Growth in the Phase II pipeline, which had been proceeding at a very fast clip in recent years, essentially flatlined in 2011, but growth in Phase III continues unabated.

79Products and pipeline

0 50 100 150 200 250

Finland

Norway

Ireland

Netherlands

Belgium

Spain

Austria

Israel

Italy

Sweden

France

Switzerland

Denmark

Germany

United Kingdom

Phase I Phase II Phase III

Number of product candidates


European clinical pipeline by country, 2011

On a country-by-country basis, the distribution of European clinical assets remains very similar to that in 2010. The relative position of the top five countries did not change. Countries that showed strong growth in their clinical pipelines included Italy (which overtook Israel to move into 7th place), Austria (which moved from 11th place to 9th place) and Belgium (which moved from the 14th to the 11th spot).


Acknowledgments

81Acknowledgments

Project leadership

Glen Giovannetti, Ernst & Young’s Global Life Sciences Leader, provided overall strategic vision for this project and brought his years of experience to the analysis of industry trends. Glen’s perspective and insights helped define many of the themes we explore in the book. Beyond leadership, Glen brought a hands-on approach, writing articles and helping to compile and analyze data.

Gautam Jaggi, Managing Editor of the publication, directed the project, wrote or edited all of the articles and helped manage the data analysis.

Siegfried Bialojan, Germany Biotechnology Leader, led and managed the development of the global data. His team’s high-quality analysis was invaluable in producing this book.

Strategic direction

Special thanks to Scott Morrison and Jürg Zürcher, who continued to play a key role in the development of this publication, by providing invaluable strategic insights based on their long experience and a feel for the pulse of the industry. Sanjeev Wadhwa’s insights played an integral role in guiding and informing the development of this year’s point of view.

Data analysis

The research, collection and analysis of global financial,financing, deals and pipeline data was conducted by Ulrike Trauth,Eva-Marie Hilgarth and Claudia Pantke. The Canadian financing data was collected by Paul Karamanoukian. Additional analysis was conducted by Gautam Jaggi, Glen Giovannetti and Paul Karamanoukian.

Jason Hillenbach, Kim Medland, Ulrike Trauth and Samir Goncalves conducted fact checking and quality review of numbers throughout the publication.

Writing and editing assistance

The Canada section was written by Paul Karamanoukian.

Russ Colton was the copy editor and proofreader for this project. Russ also played an integral role in managing the workflow of edits and ensuring that edits were implemented correctly.

Design and layout

Christian Gonswa was the lead designer for this project.Assisting Christian were David Eshenbaugh (chart design) and Robert Fernandez, Brittney Cline and Chris Grapa (designand text layout).

Logistics and marketing

Alison DeCourcey served as Project Manager. Jason Hillenbachand Rebekah Craig helped with various logistical aspects of the project.

Public relations efforts related to the book and its launch were led by Sue Lavin Jones, Dan Cusworth and the PR firm of Feinstein Kean Healthcare, led by Greg Kelley and Dan Quinn.


Data exhibit indexGrowth in established biotechnology centers, 2010–11 (US$b) ......................................25

Ernst & Young survival index, 2010–11 .........................................................................26

US biotechnology at a glance, 2010-11 (US$b) .............................................................27

US commercial leaders, 2008-11 .................................................................................28

US biotechnology: commercial leaders and other companies, 2010-11 (US$b) ...............29

The US biotech industry outperformed the overall market in most of 2011 and early 2012 ........................................................................................................30

US micro caps led the industry’s stock market performance in 2011 and early 2012 ........................................................................................................30

Selected US biotechnology public company nancial highlights by geographic area, 2011 (US$m, % change over 2010) ..................................................................31

European biotechnology at a glance, 2010–11 (US$m) ..................................................32

European biotechnology: commercial leaders and other companies, 2010-11 (US$m) .....................................................................................................33

Europe’s largest biotech companies outperformed the rest of the industry in 2011 and early 2012 ............................................................................................34

Selected European biotechnology public company nancial highlights by country, 2011 (US$m, % change over 2010) .............................................................35

Canadian biotechnology at a glance, 2010-11 (US$m) ..................................................36

Australian biotechnology at a glance, 2010-11 (US$m) .................................................37

Capital raised in North America and Europe by year (US$m) ...........................................39

Debt ratios of selected companies: big biotech reaches maturity ....................................39

Enough to sustain innovation? Innovation capital in North America and Europe by year ..................................................................................................40

Distribution of total capital raised in North America and Europe by year ..........................43

Distribution of innovation capital raised in North America and Europe by year .................43

US biotechnology nancings by year (US$m) ................................................................44

US innovation capital atlines, even as total funding rises sharply ..................................45

Quarterly breakdown of US biotechnology nancings (US$m), 2011 ..............................46

Capital raised by leading US regions, 2011 ....................................................................47

US biopharmaceutical venture capital as a share of total venture capital by year .............48

US biotechnology IPOs by year .....................................................................................48

The vast majority of 2011 US IPOs priced below their desired ranges .............................49

83Data exhibit index

2011 US IPO performance ...........................................................................................50

European biotechnology nancings by year (US$m) ......................................................51

European innovation capital by year .............................................................................52

Quarterly breakdown of European biotechnology nancings (US$m), 2011 ....................53

European biotechnology IPOs by year ...........................................................................53

Capital raised by leading European countries, 2011 .......................................................54

Canadian biotechnology nancings by year (US$m) .......................................................55

Capital raised by leading Canadian biotech clusters, 2011 ..............................................56

Quarterly breakdown of Canadian biotechnology nancings (US$m), 2011 ....................57

US and European M&As, 2006-11 ................................................................................59

Selected M&As, 2011 ..................................................................................................60

US and European strategic alliances based on biobucks, 2006-11 ..................................62

Big biobucks alliances, 2011 ........................................................................................63

Alliances with big up-front payments, 2011 ..................................................................64

US and European strategic alliances based on up-front payments, 2006–11 ...................65

US M&As, 2006-11 ......................................................................................................67

US strategic alliances based on biobucks, 2006-11 ........................................................68

US strategic alliances based on up-front payments, 2006-11 .........................................68

European strategic alliances based on biobucks, 2006-11 ..............................................69

European strategic alliances based on up-front payments, 2006-11 ...............................69

European M&As, 2006-11 ............................................................................................70

FDA product approvals, 1996–2011 .............................................................................74

Selected FDA approvals, 2011......................................................................................75

Selected orphan drug approvals by the FDA, 2011 ........................................................76

US clinical pipeline by indication, 2011 .........................................................................77

US Phase III pipeline by indication, 2011 .......................................................................77

European clinical pipeline by indication, 2011 ...............................................................78

European Phase III pipeline by indication, 2011 .............................................................78

European clinical pipeline by year .................................................................................79

European clinical pipeline by country, 2011 ..................................................................80

Global Life Sciences Leader Glen Giovannetti [email protected] +1 617 585 1998

Global Pharmaceutical Leader/EMEIA Life Sciences Leader Patrick Flochel [email protected] +41 58 286 4148

Global Life Sciences Assurance Leader Scott Bruns [email protected] +1 317 681 7229

Global Life Sciences Advisory Leader Thomas Sileghem [email protected] +32 2 774 9536

Global Life Sciences Tax Leader Neil Byrne [email protected] +353 1 221 2370

Global Life Sciences Transaction Advisory Services Leader Jeff Greene [email protected] +1 212 773 6500

Managing Editor of Beyond borders Gautam Jaggi [email protected] +1 617 585 3509

Australia Brisbane Winna Brown [email protected] +61 7 3011 3343

Melbourne Denise Brotherton [email protected] +61 3 9288 8758

Sydney Gamini Martinus [email protected] +61 2 9248 4702

Austria Vienna Erich Lehner [email protected] +43 1 21170 1152

Isabella Schwartz-Gallee [email protected] +43 1 21170 1072

Belgium Brussels Thomas Sileghem [email protected] +32 2 774 9536

Brazil São Paulo Frank de Meijer [email protected] +55 11 2573 3383

Canada Montréal Paul Karamanoukian [email protected] +1 514 874 4307

Lara Iob [email protected] +1 514 879 6514

Edmonton Trevor Lukey [email protected] +1 780 638 6644

Toronto Darrell Jensen [email protected] +1 416 943 2475

Mario Piccinin [email protected] +1 416 932 6231

Vancouver Nicole Poirier [email protected] +1 604 891 8342

Winnipeg Tanis Petreny [email protected] +1 204 933 0251

Czech Republic Prague Petr Knap [email protected] +420 225 335 582

Denmark Copenhagen Benny Lynge Sørensen [email protected] +45 35 87 25 25

Finland Helsinki Timo Virkilä [email protected] +358 207 280 190

France Lyon Philippe Grand [email protected] +33 4 78 17 57 32

Paris Brigitte Geny [email protected] +33 1 46 93 6760

Germany Mannheim Siegfried Bialojan [email protected] +49 621 4208 11405

Munich Elia Napolitano [email protected] +49 89 14331 13106

Greater China Beijing Stanley Chang [email protected] +86 10 5815 3628

India Mumbai Murali Nair [email protected] +91 22 61920000

Hitesh Sharma [email protected] +91 22 61920620

Ajit Mahadevan [email protected] +91 22 61920000

Ireland Dublin Aidan Meagher [email protected] +353 1221 1139

Israel Tel Aviv Yoram Wilamowski [email protected] +972 3 623 2519

Italy Milan Lapo Ercoli [email protected] +39 02 7221 2546

Global biotechnology contacts


Japan Tokyo Hironao Yazaki [email protected] +81 3 3503 2165

Yuji Anzai [email protected] +81 3 3503 1100

Netherlands Amsterdam Jules Verhagen [email protected] +31 88 407 1888

New Zealand Auckland Jon Hooper [email protected] +64 9 300 8124

Norway Trondheim/Oslo Willy Eidissen [email protected] +47 918 63 845

Poland Warsaw Mariusz Witalis [email protected] +48 225 577950

Singapore Singapore Swee Ho Tan [email protected] +65 6309 8238

South Africa Johannesburg Sarel Strydom [email protected] +27 11 772 3420

Sweden Uppsala Björn Ohlsson [email protected] +46 18 19 42 22

Switzerland Basel Jürg Zürcher [email protected] +41 58 286 84 03

United Kingdom Bristol Matt Ward [email protected] +44 11 7981 2100

Cambridge Cathy Taylor [email protected] +44 12 2355 7090

Rachel Wilden [email protected] +44 12 2355 7096

Edinburgh Mark Harvey [email protected] +44 13 1777 2294

Jonathan Lloyd-Hirst [email protected] +44 13 1777 2475

London/Reading Ian Oliver [email protected] +44 11 8928 1197

United States Boston Michael Donovan [email protected] +1 617 585 1957

Bruce Bouchard [email protected] +1 617 585 6890

Chicago Jo Ellen Helmer [email protected] +1 312 879 5262

Dallas Kenneth Bernstein [email protected] +1 214 969 8903

Houston Carole Faig [email protected] +1 713 750 1535

Los Angeles Abdul Lakhani [email protected] +1 213 977 3070

Don Ferrera [email protected] +1 213 977 7684

New York/New Jersey Tony Torrington [email protected] +1 732 516 4681

Tony Masherelli [email protected] +1 732 516 4719

Kim Ramko [email protected] +1 615 252 8249

Sanjeev Wadhwa [email protected] +1 732 516 4183

Orange County Dave Copley [email protected] +1 949 437 0250

Kim Letch [email protected] +1 949 437 0244

Redwood Shores Scott Morrison [email protected] +1 650 496 4688

Chris Nolet [email protected] +1 650 496 1620

Philadelphia Steve Simpson [email protected] +1 215 448 5309

Howard Brooks [email protected] +1 215 448 5115

Raleigh Michael Constantino [email protected] +1 919 981 2802

San Antonio David King [email protected] +1 210 242 7108

San Diego Dan Kleeburg [email protected] +1 858 535 7209

Seattle Kathleen Smith [email protected] +1 206 654 6305

Washington, D.C. Rene Salas [email protected] +1 703 747 0732

85Global biotechnology contacts

Ernst & Young

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