sunday (2) lipinski

30
Where is drug discovery going? Christopher A. Lipinski Scientific Advisor, Melior Discovery clipinski@meliordiscovery .com 1 DDND 2012 Lipinski keynote

Upload: plmiami

Post on 20-Jan-2015

535 views

Category:

Technology


0 download

DESCRIPTION

 

TRANSCRIPT

Page 1: Sunday (2) lipinski

Where is drug discovery going?

Christopher A. LipinskiScientific Advisor, Melior Discovery

[email protected]

1DDND 2012 Lipinski keynote

Page 2: Sunday (2) lipinski

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 for2DDND 2012 Lipinski keynote

Page 3: Sunday (2) lipinski

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

3DDND 2012 Lipinski keynote

Page 4: Sunday (2) lipinski

Death Valley California

DDND 2012 Lipinski keynote 4

Page 5: Sunday (2) lipinski

Translational valley of death

DDND 2012 Lipinski keynote 5

"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.

Page 6: Sunday (2) lipinski

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

6DDND 2012 Lipinski keynote

Page 7: Sunday (2) lipinski

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

DDND 2012 Lipinski keynote 7

Page 8: Sunday (2) lipinski

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

DDND 2012 Lipinski keynote 8

Page 9: Sunday (2) lipinski

Bayer observation in NRDD

DDND 2012 Lipinski keynote 9

Page 10: Sunday (2) lipinski

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

DDND 2012 Lipinski keynote 10

Page 11: Sunday (2) lipinski

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

DDND 2012 Lipinski keynote 11

Page 12: Sunday (2) lipinski

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.

DDND 2012 Lipinski keynote 12

Page 13: Sunday (2) lipinski

DDND 2012 Lipinski keynote 13

Genomics financial madness

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

Page 14: Sunday (2) lipinski

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

DDND 2012 Lipinski keynote 14

Page 15: Sunday (2) lipinski

….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

DDND 2012 Lipinski keynote 15

Page 16: Sunday (2) lipinski

50 years of medicinal chemistry

DDND 2012 Lipinski keynote 16

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

Page 17: Sunday (2) lipinski

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.

DDND 2012 Lipinski keynote 17

Page 18: Sunday (2) lipinski

Nanomolar is not necessary

DDND 2012 Lipinski keynote 18

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.

Page 19: Sunday (2) lipinski

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.

DDND 2012 Lipinski keynote 19

Page 20: Sunday (2) lipinski

Phenotypic screening

• Finally government is paying attention

• NIH new institute TRND

• 25% of assays are reserved for phenotypic screening

DDND 2012 Lipinski keynote 20

Page 21: Sunday (2) lipinski

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

21DDND 2012 Lipinski keynote

Page 22: Sunday (2) lipinski

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

DDND 2012 Lipinski keynote 22

Page 23: Sunday (2) lipinski

Do drug structure networks map on biology networks?

DDND 2012 Lipinski keynote 23

Page 24: Sunday (2) lipinski

Chemistry drug class network

DDND 2012 Lipinski keynote 24

Page 25: Sunday (2) lipinski

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.”

DDND 2012 Lipinski keynote 25

Page 26: Sunday (2) lipinski

What is going on?

• Old maxim: Similar biology implies similar chemistry

• If strictly true biology and chemistry networks should coincide

DDND 2012 Lipinski keynote 26

Page 27: Sunday (2) lipinski

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

DDND 2012 Lipinski keynote 27

Page 28: Sunday (2) lipinski

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

DDND 2012 Lipinski keynote 28

Page 29: Sunday (2) lipinski

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

DDND 2012 Lipinski keynote 29

Page 30: Sunday (2) lipinski

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

DDND 2012 Lipinski keynote 30