Sunday fillet lipinski

THANK YOU!

Funding for this conference was made possible in

part by

Cooperative Agreement U13AG031125-05 from

the

National Institute on Aging.

The views expressed in written conference materials or publications and by speakers and moderators do not necessarily reflect the official policies of the Department of

Health and Human Services; nor does mention by trade names, commercial practices, or organizations imply endorsement by the U.S. Government.

Thank You!MEETING SPONSORS

BRONZE SPONSORS

SCIENTIFIC ADVISORY COMMITTEEKurt R. Brunden, PhD, University of Pennsylvania

Neil S. Buckholtz, PhD, National Institute on Aging

Rebecca Farkas, PhD, National Institute of Neurological Disorders and Stroke

Howard Fillit, MD, Alzheimer’s Drug Discovery Foundation

Brian Fiske, PhD, Michael J. Fox Foundation for Parkinson’s Research

Mark Frasier, PhD, Michael J. Fox Foundation for Parkinson’s Research

Abram Goldfinger, MBA, New York University

Lorenzo Refolo, PhD, National Institute on Aging

Suzana Petanceska, PhD, National Institute on Aging

Diana Shineman, PhD, Alzheimer’s Drug Discovery Foundation

Edward G. Spack, PhD, Fast Forward, LLC

D. Martin Watterson, PhD, Northwestern University

SCIENTIFIC ADVISORY COMMITTEE

ADDF Staff

• Diana Shineman, PhD – Assistant Director, Scientific Affairs

• Rachel Lane, PhD – Scientific Program Manager

• Filomena Machleder – Assistant Director, Institutional Partnerships

• Natalie Romatz – Partnerships Assistant, Institutional Partnerships

• Niyati Thakker – Grants Assistant

• World Events Forum – Conference Secretariat

NOTES

Please remember to complete and submit the meeting survey!

CME Certificates available at the Registration Desk

A webcast of the conference will be available soon on our website:

www.alzdiscovery.org

13th International Conference on Alzheimer’s Drug Discovery

September 10-11, 2012 • Jersey City, NJacross from NYC on the Hudson River

SAVE THE DATE!

Goals of the Meeting

• Knowledge:

– The principles and practice of drug discovery, with a focus on the unique aspects for neurodegenerative diseases

• Network:

– >190 attendees from 20 countries, ~40% from industry

– Exchange ideas, foster alliances, partnerships and collaborations

•WHO estimates neurodegenerative disorders will be the major unmet medical need of the 21st century, •surpassing cancer as the worlds’ second leading cause of death by the year 2040

Neurodegenerative Diseases Affect >22 Million Worldwide

Alzheimer’s disease; 5,000,000

Parkinson’s disease; 1,000,000

ALS; 30,000

Multiple sclerosis; 400,000 Huntington’s, 30,000

Some symptomatic agents, few disease modifying drugs

Developing a Drug is Risky, Takes 12-15 years and Costs Over $1.2B

1 FDAApproved

Drug

HUMAN STUDIES BIOLOGY

AND CHEMISTRY

ANIMALSTUDIES and

PHARMACOLOGY

InnovationProof

of MechanismSafety and

Proof of ConceptProof

of Efficacy

10,000 to>1 millionchemicals

Drug Discovery is a Vital Stage in Drug DevelopmentWhen Innovation is Created

Opportunity and Challenges for Success:A Perspective On The Origin of FDA Approved Drugs

From: T. Bartfai and GV Lees, Drug Discovery from Bedside to Wall Street, 2006;Le Couteur, et al 2011

Most are variants on formulation and delivery

Many anti-microbials

Less than 500 distinct chemical entities

Targeting ~266 human genome derived proteins

~50M compounds in Chem Abstracts;1040-10100 possible small molecules

20,000 human genes100,000 proteins

~10,000 approved drugs

Less than 50 unique chemical scaffolds

• Deposits of Misfolded Protein– Β-Amyloid, tau, α-synuclein, TDP-43, poly-Q aggregates

• Oxidative stress• Inflammation• Mitochondrial dysfunction• Synaptic and neuronal cell dysfunction• Vascular ischemia and damage• Other novel mechanisms (eg. epigenetics)

How a Biologist Thinks About Drug Discovery:Many Targets for Neurodegeneration?

• Target types– GPCR (small ligand)– Enzyme (small ligand)– Ion channel– Nuclear receptor– Protease– Enzyme (large ligand)– GPCR (large ligand)– Cytotoxic (other)– Protein kinase– Protein-protein

High

Success

Low

How a Chemist Thinks About Targets for Drug Discovery:Success Rates of Target Types

Why A Biological Network Approach to Drug Discovery is Needed: Signaling in the Synapse is Complex

How Were New Drugs Discovered? Phenotypic Screening Vs. Target-based

Screening

Swinney, et al, Nature Reviews Drug Discovery, July, 2011

Test for in vivo activity

Focused Medicinal Chemistry

Selection of leads

High throughput screen (500,000 cpds.)

Assay development

Screening approach

Inhibitor Development

Rational design approach

generation ofprotein

CrystalStructure

ComputerModel

MedicinalChemistry

PK

Specificity

Potency

Identification of hits

Case Studies: Routes to Drug Discovery

beta-secretase inhibitors gamma-secretase inhibitors

Improving Success Rates?Drug Discovery in Academia

• Drug discovery is the interface between basic research and clinical development

• Requires extensive resources and collaboration between teams of investigators

• Increasingly requires partnerships between pharma, biotechs, non-profits, and government, especially for neurodegenerative diseases

Drug Discovery and Development Requires Multidisciplinary Teams of Scientists

Clinical DevelopmentClinical Trialists

IND enabling studies: ADMET, formulation and scale-up chemistryPharamaceutical Scientists

In vivo Testing and Preclinical Proof of MechanismBiomarker Development

Animal Trialists

High Throughput Screening

Lead Identification and optimization

Structure Based Chemistry

Medicinal Chemistry, Pharmacology

Assay DevelopmentChemical Libraries

Computational Chemistry

Target identification Basic Neurobiology

The ADDF has granted over $55 million to >370 Alzheimer’s drug discovery programs in academic centers

and biotechnology companies in 20 countries

ADDF funding has resulted in

>$2 billion in follow-on commitments,

and several novel drugs entering clinical trials

Feeding the Pipeline:The Alzheimer’s Drug Discovery

Foundation

www.AlzDiscovery.org

http://www.alzdiscovery.org/

Drug Discovery: The “Valley of Death”? Or “Welcome to An Amazing Journey”!

Where is drug discovery going?

Christopher A. LipinskiScientific Advisor, Melior Discovery

[email protected]

20DDND 2012 Lipinski keynote

Outline• Academic targets and the translational gap

–is it just a missing resource issue?

• Chemistry & attrition - worse with time–reductionism , genomics, HTS to blame?

• Screening diverse compounds–the worst way to discover a drug–novelty drive comes from patents and not science

• Biology and chemistry networks analysis–chemistry due diligence on leads is essential

• What to look for21DDND 2012 Lipinski keynote

Drivers for discovery changes• Chemistry, 65% successful predictivity

• rules and filters, eg. phys chem, structural• ADME predictivity worsens outside of RO5 space

• Safety, 50% successful predictivity• Efficacy, 10% successful predictivity

• Tackle efficacy using academic collaborations• systems biology still too new to save us• target quality is most likely from rich biology


Death Valley California

DDND 2012 Lipinski keynote 23

Translational valley of death


"curing disease is a byproduct of the [NIH] system and not a goal," says FasterCures' Simon. Most scientists don't want to and don't have the skills to translate a discovery into a treatment; researchers at a dedicated center would try to do that full-time.

Death valley, politically correct causes?

• Academics lack drug discovery skills• Requires industry / academic collaboration

• eg. medicinal chemists are mostly in industry

• No access to ADMET, drug met, pharm sci etc.• critical disciplines not in academia

• No access to preclinical – clinical interface skills• eg. analytical, process chemistry, formulation

• No access to early development skills• eg. toxicology, biomarkers, project management


Death valley, politically incorrect causes?

• Assumption - academic ideas on new targets are of high quality

WRONG• Bayer analysis of validation of academic targets• 50 % of academic targets are wrong• 25% of academic targets are partially flawed• Translational death valley exists (in part) because

of poor quality academic target identification


Why the academic target problem• Culprit is primarily the pressure to publish to

support both grant applications and career development

• A people problem• A government problem• Exacerbated by hypothesis driven research

• The positive: infrastructure collaboration


Bayer observation in NRDD


Has drug discovery gone wrong?

• Prevailing mantra: identify a mechanism and discover a selective ligand for a single target

• Counter responses:• Phenotypic screening• Drug repurposing• Multi targeted drug discovery• In-vivo screening• Non target non mechanism screening


Genomics – Chemistry parallel

• Genome sequence deciphered in 2000• Automated chemistry starts in 1992• Misapplied, both impeded drug discovery

• “The DNA reductionist viewpoint of the molecular genetics community has set drug discovery back by 10-15 years” Craig Venter quote

• “In 1992-1997 if you had stored combinatorial chemistry libraries in giant garbage dumpsters you would have much improved drug discovery productivity” Chris Lipinski quote


Genomics / HTS science madness• Collaborations to mine genomic targets• Massive HTS campaigns to discover ligands• 500 different targets, a million data points • “a wish to screen 100,000 compounds per day

in a drug discovery factory and a wish to make a drug for each target”

Drug discovery and development using chemical genomics. A. Sehgal, Curr Opin in Drug Disc & Dev (2002), 5(4), 526-531.

The drug discovery factory : an inevitable evolutionary consequence of high throughput parallel processing. R. Archer, Nat Biotech (1999), 17(9), 834.



Genomics financial madness

1% success, NPV $34M, Decision Resources March 29, 2004

Target-based drug discovery:

E1 E5

R2R3

R4R5

R6R1

E2

E3 E4 E7

E6

DP 1 DP 2

D1D2

Slide thanks to Andrew Reaume, Melior Discovery


….the real picture

R8

DP 5

E10

E9

E8E1 E5

R2R3

R4R5

R6R1

E2

E3 E4 E7

E6

DP 1 DP 2

R7

R9 R10

R11R12

DP 3DP 4

E7

E8

D1D2

Slide thanks to Andrew Reaume, Melior Discovery


50 years of medicinal chemistry


What Do Medicinal Chemists Actually Make? A 50-Year Retrospective Pat Walters et al. J Med Chem 2011

Attrition rates by phase

The Productivity Crisis in Pharmaceutical R&D, Fabio Pammolli, Laura Magazzini and Massimo Riccaboni, Nature Reviews Drug Discovery 2011 (10) 428-438.


Nanomolar is not necessary


Mean po dose is 47 mg Mean pXC50 is 7.3 (IC50 5 x 10-8)Gleeson, M. Paul; Hersey, Anne; Montanari, Dino; Overington, John. Probing the links between in vitro potency, ADMET and physicochemical parameters. Nature Reviews Drug Discovery (2011), 10(3), 197-208.

Phenotypic screening advantageThe majority of small-molecule first-in-class NMEs that were discovered between 1999 and 2008 were first discovered using phenotypic assays (FIG. 2): 28 of the first-in-class NMEs came from phenotypic screening approaches, compared with 17 from target-based approaches.

How were new medicines discovered? David C. Swinney and Jason Anthony Nature Reviews Drug Discovery 2011 (10) 507-519.


Phenotypic screening

• Finally government is paying attention• NIH new institute TRND• 25% of assays are reserved for phenotypic

screening


Chemistry novelty is harmful• Patents direct towards chemistry novelty

• Chemistry novelty correlates with decreased drug discovery success

• “The role of the patent system in promoting pharmaceutical innovation is widely seen as a tremendous success story. This view overlooks a serious shortcoming in the drug patent system: the standards by which drugs are deemed unpatentable under the novelty and non-obviousness requirement bear little relationship to the social value of those drugs or the need for a patent to motivate their development” Benjamin N. Roin, Texas Law Review


Screening diverse compounds is the worst way to discover a drug

• Every publication I know of argues that biologically active compounds are not uniformly distributed through chemistry space


Do drug structure networks map on biology networks?


Chemistry drug class network


Network comparison conclusions• “A startling result from our initial work on

pharmacological networks was the observation that networks based on ligand similarities differed greatly from those based on the sequence identities among their targets.”

• “Biological targets may be related by their ligands, leading to connections unanticipated by bioinformatics similarities.”


What is going on?

• Old maxim: Similar biology implies similar chemistry

• If strictly true biology and chemistry networks should coincide


Network comparisons – meaning?• “Structure of the ligand reflects the target”• Evolution selects target structure to perform a

useful biological function• Useful target structure is retained against a

breadth of biology• Conservation in chemistry binding motifs• Conservation in motifs where chemistry

binding is not evolutionarily desired–eg. protein – protein interactions


Hit / lead implications• You have a screening hit. SAR on the historical

chemistry of your hit can be useful even if it comes from a different biology area

• Medicinal chemistry principles outside of your current biology target can be extrapolated to the ligand chemistry (but not biology) of the new target

• Medicinal chemistry due diligence is essential


Changes in drug discovery

• Questioning of reductionist approach• A positive development in CNS drug discovery• Very few CNS agents are found rationally• Experimental observations in the clinic• Multiple Sclerosis as a paradigm• No drugs until disease progression biomarkers• Multiple MS drugs recently available


What to look for

• Disease progression biomarkers–first impact in drug discovery–later impact when therapy arrives

• Orphanization of disease diagnosis–new drugs or fitting patients to current drugs?–challenges to cost structures

• Exploring drug or target combinations


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