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THE “CONVERGENCE” WATCHLIST

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When it comes to biotechnology, artificial intelli-gence (AI) is changing the game.

Think about this – traditionally, it has taken the standard pharmaceutical company 3.5 years on average to discover a new drug candidate. From there it often takes another year or more to do all the prep work necessary to move the drug into preclinical trials. After that, the drug must go through several more years of clinical trials before the pharmaceutical company can apply for the drug’s approval.

In total, it takes an average of 12–15 years to get a therapy from the discovery phase to regulato-ry approval. And the Tufts Center for the Study of Drug Development estimates that it costs an average of $2.6 billion to complete this process.

It’s hard to wrap our heads around how expen-sive and time-consuming this traditional ap-proach is.

Fortunately, there’s a better way. That’s where AI comes into the picture.

In my special report, Convergence: The Small-Cap Company Using AI to Discover Drugs, I told the story of a drug that made it to preclinical trials in January 2020. What was remarkable was that the drug was discovered by an artificial intelligence. And this happened again in 2021.

A drug discovered by an AI from a company called Insilico advanced into preclinical trials in Febru-ary 2021. That’s another incredible milestone.

And get this – the AI accomplished this in just 19 months. That means it shaved at least two

– perhaps more than three – years off the devel-opment process. And that’s before the drug even gets into clinical trials.

What’s more, applying AI to the drug discovery process can help us find potential treatments for diseases that were previously untreatable. It does this by poring through massive datasets that would be very difficult for a human to ana-lyze. This allows the AI to “see” things and make connections that would not be possible using traditional methods.

Simply put, this is going to completely reshape the industry. The genie is out of the bottle.

The convergence of AI and biotechnology will be one of the most important trends of this decade. It is going to make the drug discovery and devel-opment process far more efficient. And we’ll see an explosion of new treatments for cancer and other diseases that plague humanity as a result.

We are no more than a decade away from being able to cure many diseases that were previously thought untreatable. I don’t think many people re-alize this yet. But it’s incredible news for all of us.

And, of course, such a massive trend will present us with some life-changing investment opportu-nities along the way. But only if we know where to look.

We already have exposure to this trend with our investment in Schrödinger (SDGR). But we won’t stop with just following public companies.

One of the things that give me an “edge” as an investment analyst is my experience with early

The “Convergence” WatchlistBy Jeff Brown, Editor, Exponential Tech Investor

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stage private investments. As an angel investor myself, I am constantly plugged into Silicon Val-ley and the world of exciting startup companies.

And I use this expertise to our advantage here in Exponential Tech Investor.

Unlike Wall Street, I track the most promising tech and biotech companies while they are still private. I first get to know their founders. Then I analyze each early stage funding round to see which venture capital firms are backing the com-pany. I also watch closely for any big develop-ments the company makes while it is still private.

As a result, I know as much as any analyst could possibly know about these companies by the time they go public. I know the team. I understand the work they are doing and how much progress they have made. And I have a strong feel for their val-uation. This enables me to recommend the best early stage companies well before they pop up on Wall Street’s radar.

And this special report is intended to be a peek behind the curtain into that world.

I’m going to outline the most promising compa-nies working at the intersection of AI and bio-technology. These are the companies that will provide explosive investment opportunities for us in the years to come after they go public.

This is a glimpse at the work I do behind the scenes when nobody is looking.

Please note that the companies highlighted in this report are not going to be automatic recom-mendations at the time of their IPO. We should always remember that valuation is still critical to understand no matter how excited we are about a promising company. Investing in assets that are grossly overvalued is never a good investment strategy and almost always ends badly.

So when these companies do go public, we may not jump on them right away. We’ll need to be very strategic and wait until we can establish positions at a favorable valuation. That’s how we reap outsized investment returns year after year in Exponential Tech Investor.

This is the list that Wall Street would love to get their hands on…

Founded: 2018Headquarters: South San Francisco, CAWebsite: www.insitro.com

The traditional approach to drug discovery and therapeutic development is antiquated. It’s driv-en largely by trial and error. At a very high level, we can think of this method as manual “tinker-ing.” It’s slow, resource-intensive, and inefficient.

As I mentioned, it takes on average 12–15 years to bring a new therapy to market. And it takes roughly $2.6 billion on average to go from drug discovery to commercial launch. This is a long and expensive process.

Insitro was founded in 2018 to solve this prob-lem. The company’s stated objective is to “be-come the first truly data-driven, integrated, drug discovery and development company.”

There are two key elements to Insitro’s approach. First, it uses high-quality genetic, phenotypic, and clinical data. Then Insitro pairs this information with artificial intelligence (AI) and machine learn-ing (ML) to make sense of the vast amount of data.

The insights learned from the AI enable the com-pany to “see” things and make connections that

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are not possible using traditional methods, which are slow-moving and labor-intensive.

In essence, Insitro “unleashes” an AI on the task of drug discovery. This shortens the timeline and cuts costs dramatically.

Our “convergence” theme means we want to target companies at the intersection of biotech-nology and artificial intelligence and machine learning. Insitro fits that profile perfectly.

Backing

Insitro got off to a fast start by raising $79.4 mil-lion in a Series A financing round led by a mar-quee group of investors in December of 2018. Notable investors that currently sit on the board are ARCH Venture Partners, a16z, GV (formerly Google Ventures), and Third Rock Ventures. The company also saw funding from Two Sigma Ven-tures and Bezos Expeditions.

This is a who’s who of the venture capital (VC) community. And if the best VC firms are making larger and larger investments in a private compa-ny, we know they’ve got something good. That’s what we have here. This same list of investors showed up in 2020 and 2021 when Insitro did its Series B and Series C financing rounds.

In 25 months, Insitro went from raising $79 mil-lion in its Series A to raising $400 million this March. These backers believe in the technology and approach, and they’re ensuring the team has adequate capital to accelerate development.

It should not come as a surprise that we’re al-ready seeing late-stage money come in from BlackRock, T. Rowe Price, and the Canada Pen-sion Plan Investment Board. When we see late-stage financing from these investors, it is a clear indicator Insitro is gearing up to go public.

And with major multiyear deals with biopharma giants Gilead and Bristol Myers Squibb, this com-pany is a must-add to our early stage watchlist.

We’ll follow Insitro closely going forward. At the right valuation as a public company, it could make an incredible investment target.

Founded: 2012Headquarters: San Francisco, CAWebsite: www.atomwise.com

For every molecule – or combination of mole-cules – that becomes a drug, millions might be tested and found to be unsuitable for further development.

In preclinical drug development, this is known as an “attrition rate.” And over time, this high failure rate leads to higher costs in developing drugs. This is known as Eroom’s law, a phenom-enon all too familiar in the pharmaceutical space.

On the next page is a chart highlighting this law.

Eroom’s Law observes that drug discovery has become slower and more expensive over time. Put simply, $1 billion in drug development – even adjusted for inflation – simply doesn’t yield as many new drugs as it used to.

Eroom’s Law can be contrasted with Moore’s Law, which observes the exponential growth in transistor density and computing capabilities in semiconductors over the past several decades. This contrast is well-known… And “Eroom’s” is “Moore’s” spelled backward.

Eroom’s Law is unfolding at a time when bacteria

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are becoming increasingly re-sistant to existing antibiotics. And the world is now contend-ing with emerging pandemic viruses around the world.

(The “void of discovery” in new antibiotics was a key rea-son we invested in Spero Ther-apeutics [SPRO]. For readers who missed that report, catch up right here.)

In essence, at a time when the world needs robust drug dis-covery more than ever, fewer drugs are reaching the market.

Thankfully, we are starting to see a small cohort of companies in the biotech-nology space respond. Their answer is AI, and it is empowering an innovative approach to drug discovery. Atomwise, the next company on our watchlist, is one of them.

Atomwise uses a technology called AtomNet. The company describes its technology as a “key and lock” model. This model focuses on designing molecules that are complementary in shape and charge to the intended biomolecular target. This gives scientists an edge in developing molecules more likely to have the desired effect on the body.

Atomwise does this by leaning on specific AI algorithms to guide predictions. And as I men-tioned before, this kind of technology is set to cut down on early stage drug development time and improve the success rate of new drugs.

Scientists can spend less time taking stabs in the dark, improve attrition rates, and reduce costs. It is how Atomwise plans to produce more profit from each dollar spent on research and development.

Backers

Early backers in Atomwise put up $6 million in its seed round in May 2015. The funding round was led by Data Collective. Other early backers were Khosla Ventures, Draper Associates, and AME Cloud Ventures.

Three years later, Atomwise went through a Series A round with $45 million in financing. Data Col-lective, Khosla Ventures, and Threshold Ventures returned this round. It also included major back-ers such as Y Combinator, Bayer Growth Ventures, Baidu Ventures, Tencent Holdings, Monsanto Growth Ventures, and Dolby Family Ventures. Atomwise also received a grant worth $2.3 million from the Bill and Melinda Gates Foundation to support its drug development platform.

Most recently in August 2020, Atomwise held its Series B and received $123 million. We saw sim-ilar names return in this round such as Y Combi-nator, Data Collective, Baidu Ventures, Tencent Holdings, and Dolby Family Ventures. Atomwise

Eroom’s LawNew Drugs Per Billion USD Spent on R&D (Log Scale)

0.1

100

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Over time, the high failure rate leads to higher costs in developing drugs

Source: Benchtalk

1950 1970 19801960 1990 2000 2010 2020

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also received a grant worth $2.3 million from the Bill and Melinda Gates Foundation to support its drug development platform.

Previous backers investing again in the latest funding round means they believe in Atomwise’s progress. And we can take note of this as smart money worth following.

These private investors are the closest to the project and clearly see a great opportunity to grow their capital. This makes Atomwise another biotechnology company leveraging AI that we can place on our convergence watchlist.

Founded: 2012Headquarters: Oxford, United KingdomWebsite: www.exscientia.ai

Only one in a thousand molecules identified as a potential treatment by pharmaceutical com-panies makes it to human clinical trials. Drug discovery is a field littered with failed attempts.

Time compounds the issue even further.

It takes anywhere from approximately three to six years to reach human trials, which cre-ate more room for failure. In fact, 90% of drug candidates never make it out of trials. And even fewer ever gain Food and Drug Administration (FDA) approval.

The statistics surrounding drug discovery make it appear like a lottery ticket. The odds a drug therapy ever makes it to market are tiny. The only reason companies take a chance on new drug therapies is because the rewards can be in-credible. A successful commercial drug can result

in tens of billions of dollars in sales every year.

But imagine if a technology could improve the odds that a therapeutic candidate will make it to market and decrease the time taken during clinical trials. That is precisely what Exscientia aims to do.

Like our other convergence companies, Exsci-entia leverages AI and data sets to remove the guesswork involved in drug discovery. And the results are already coming through…

In my Convergence special report, I showed how Japanese pharmaceutical company Sumitomo Dainippon Pharma had announced that it would be taking its new compound, DSP-1181, to human clinical trials for obsessive-compulsive disorder.

But that wasn’t the real story.

The breakthrough was that the compound was entirely invented by Exscientia’s artificial intel-ligence. Exscientia cut the process of discovery down from three years or more to just 12 months. That type of improvement is measured in orders of magnitude, not simply percentage terms.

This is the type of growth we home in on when finding exponential technologies. That’s because saving time in a notoriously slow industry trans-lates to better earnings and higher valuations.

With the industry spending nearly $2.6 billion on average to get a new drug through to FDA ap-proval, saving years on drug discovery can create billions of dollars of competitive advantage.

These are the types of events we look back on years from now and say, “That’s when it all changed.” A decade from now, Exscientia’s ac-complishment will be spoken of in the same way as the reveal of the first iPhone or the moment

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we reached quantum supremacy.

And that earns Exscientia a spot on our conver-gence watchlist.

Backers

Exscientia has had several financing rounds to date. From 2019 to 2021, it held three funding rounds, raising $26 million, $100 million, and $225 million, respectively.

The company has raised $397.3 million to date when you include its early venture round. While the company’s ability to raise substantial funds so quickly is great, we should also pay attention to its backers.

Exscientia backers include the venture arm of $168 billion pharmaceutical giant Novo Nordisk, two venture entities that are housed within the $147 billion Bristol Myers Squibb conglomerate, and the $122 billion asset manager BlackRock. These are some of the largest companies in the world taking an interest.

When major entities like this are circling, we know the company is about to go public.

And Exscientia proved this to be the case. It confidentially filed for an IPO in late June 2021, which means we are getting very close to seeing it reach the public markets.

Founded: 2012Headquarters: Redwood City, CAWebsite: www.synthego.com

There are more than 6,000 diseases that are caused by genetic mutations. We often refer to

these as genetic “typos.” These mutations can cause diseases like cystic fibrosis, sickle cell dis-ease, and predispositions to certain cancers.

And CRISPR (clustered regularly interspaced short palindromic repeats), a genetic editing technology, has the potential to cure every one of them. It allows us to “edit” the typos (genetic mutations) that cause many of these diseases.

Ultimately, CRISPR will help us cure all human disease of genetic origin.

CRISPR will be a familiar topic for longtime readers. I have been following the progress of CRISPR technology from the very beginning. And in the pages of Exponential Tech Investor, we have invested in – and profited from – several great CRISPR companies.

Notably, we saw a 332% realized return with CRISPR Therapeutics (CRSP) and a 308% real-ized return with Intellia Therapeutics (NTLA). We’re also showing a 267% unrealized return on Editas Medicine (EDIT) and a 344% unrealized gain on Beam Therapeutics as I write this.

Congratulations to all readers who took part in these investments. And I’d encourage new sub-scribers to navigate to our model portfolio to learn more about these incredible companies. Simply click on a company to read about our investment thesis.

New readers may think the promise of CRISPR sounds too good to be true. However, we’ve al-ready seen its potential.

Not too long ago, a scientist made headlines by “snipping” out a genetic error that can cause heart disease in dozens of human embryos. And the technology has already been used success-fully in human trials to treat beta thalassemia

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and sickle cell disease, both conditions caused by a single genetic mutation. It is only a matter of time before we see this kind of precision medi-cine being used widely.

This is one reason the market for CRISPR ther-apies is expected to grow from $846 million in 2019 to $10.8 billion by the end of the decade. That’s massive growth.

However, designing a CRISPR therapy is still a very laborious and time-consuming process. Synthego is leveraging gene editing and pairing it with AI to accelerate research and development. This is a powerful combination that puts it at the forefront of innovation by automating biological research.

Synthego, the next company on our watchlist, is a full-stack genome engineering company.

In April of 2020, Synthego launched Eclipse, a cell engineering platform designed to make the discovery of new CRISPR therapies faster and more cost efficient. Eclipse applies machine learning to a trove of data from genome edits in order to develop CRISPR therapies to address specific genetic diseases.

Put simply, Synthego’s Eclipse uses machine learning to make the CRISPR discovery process easier, faster, and cheaper. And that makes it an-other great company to add to our convergence watchlist.

Backers

Synthego is stacked with great backers that can push it toward becoming a publicly traded company.

To date, we’ve seen Founders Fund, Intel Capital, Menlo Ventures, and Eight Partners VC pile into multiple funding rounds. These companies are

making sure Synthego has sufficient capital to keep things moving.

Like I mentioned above, when investors commit more capital to an investment, it means they know this company has legs.

Synthego is a company that has raised $266.7 million to date and will likely raise more. This is another company on the bleeding edge of biotech innovation for our watchlist.

Founded: 2019Headquarters: Boston, MAWebsite: www.valohealth.com

The pharmaceutical business is one of the most capital-intensive industries in the U.S. economy. It spends the most dollars on research and de-sign as a percentage of sales.

This designation is not restricted to the U.S. From 2015 to 2020, pharmaceutical R&D global spend-ing has surpassed $1 trillion. And these costs are expected to keep rising. In fact, by 2025 spending is expected to surpass $225 billion annually.

It’s a daunting figure.

But most analysts are oblivious to the conver-gence taking place with AI and biotechnology. As we mentioned before, the combination will not only speed up drug discovery but convert prior costs into profits, as companies will push more drugs toward FDA approval and commercial launch faster than they have ever been able to do before.

These outsized costs at present mean the con-

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vergence of AI and biotech is creating one of the largest opportunities to date. And pharmaceutical companies will take advantage of this opportunity – in large part – thanks to the help from our last watchlist company, Valo.

Similar to other companies on our list, Valo has a new ap-proach to target drug discov-ery and development based on human-centric data and AI.

In 2018, Valo launched the Opal Computational Platform. Opal is a drug discovery platform that predicts how molecules will interact with a disease and the patient’s body. Like our other watchlist com-panies, Valo’s Opal “unleashes” AI onto vast data sets that show how particular treatments for a disease have impacted patients.

Valo is targeting cardiovascular disease, which accounts for about one in every four deaths in the United States. It is also targeting different types of colon and brain cancers as well as neuro-degenerative diseases that impact more than five million Americans.

These are some of the biggest areas ripe for the innovative work being performed by Valo.

Backers

Valo is an incubator project led by Dr. David Ber-ry, who was the founder and now is CEO. He’s no stranger to leading a company. Dr. Berry comes in with substantial experience, having founded over 25 companies. He also brings strong back-ing as a general partner at the biotech-focused venture capital firm Flagship Pioneering.

Flagship Pioneering backed the now $173 billion biotechnology giant Moderna, which helped cre-ate a COVID-19 vaccine in record time.

This high-pedigree backing of Velo has attract-ed $300 million in its Series B offering. Notable names in this round included Koch Disruptive Technologies, Public Sector Pension Investment Board, HBM Partners, the Invus Group, and Flagship Pioneering.

With such large names jumping in on its Series B earlier this year, the company entered into an agreement to go public via a reverse merger with Khosla Ventures Acquisition on June 9. It will become a publicly traded company as soon as that deal closes.

The strong backers and innovative approach to some of the largest problems in medicine make it a must-add to our watchlist.

Regards,

Jeff Brown Editor, Exponential Tech Investor

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