Pre-competitive projects can work to deliver science and change culture

• Established 2003

• 200 scientists; labs in Toronto, Oxford and Stockholm

• Funded by - Private: GSK, Merck, Novartis, Lilly, Pfizer, Life

Tech- Govt: Canada, Ontario, Sweden - Charities: Wellcome Trust, Wallenberg Foundation

The SGC: A model for sharing in experimental science

SGC: open access works• 1000 human protein structures – all available without

restriction– ~30% of novel human proteins in PDB per annum– Structures used to be “competitive”

• >100 structures of proteins from parasitic protozoa– Chemical validation for drug targets in toxoplasmosis (Nature,

2010) and sleeping sickness (Nature, 2010)

• 500 cDNA clones distributed freely every year (academia, biotech, pharma)

• 75 visiting scientists per annum

Why does the SGC model work?

• SGC model allows opportunity to work with the very best – 200+ collaborations

• SGC model drives fast data dissemination– On average, each SGC structure enters public domain 18-24

months in advance of academic norms

• SGC model promotes collaboration– Average of >3 non-SGC authors for each paper

• SGC model focuses on milestones– 1000 structure target (2004-2011); 1,100 achieved to date

• No IP

In biomedicine, the system is the greatest hurdle to the discovery of innovative medicines

The funding system does not support “innovation”

HUMAN PROTEIN KINASES (ordered by most citations 1950-2002)

CITA

TIO

NS

(nor

mal

ized

)

Citations as a function of time

1950-2002

2003-2008

2009

How have we responded to the genome?

Another way of looking at it

• 65% of 2009 kinase publications on the 10% of the kinome that was “hot” in early 1990’s

• 5% of 2009 kinase publications on the 300 kinases that were the least studied in 2002

Others also feel trapped by the system

What should the scientific community do?

1. Pay less attention to the literature2. Be more daring when funding research3. Support young scientists to dream bigger

NUCLEAR HORMONE RECEPTOR

CITA

TIO

NS

Another path emerges from examining the history of nuclear hormone receptor research (1950-2010)

ERa PR

PPARgRARa

MR

PXRLX

Ra

PPARdCAR

NGFIBa

RARgTR

aDAX

SHP

ERRa

RORg

Rev-erb

a

NGFIBg

RXRgTR

2ER

RbTR

4TL

X

COUP30

5000

10000

15000

20000

25000

30000

35000

CITA

TIO

NS

ERa

PPARa PRRARa

MR

LXRa

PPARdTR

bRORg

ERb

HNF4a

SHP

SF1

Rev-erb

a

COUP2TR

aLR

H1

NGFIBg

RXRaRXRg

ERRb

GCNFTR

2

COUP30

500

1000

1500

2000

2500

3000

NUCLEAR HORMONE RECEPTOR

In 2009, the research is even more biased

Pre- and post-genome NR citations

1950-1995

2009

0

1000

2000

3000

4000

5000

6000

7000

**** *

**

*

CITA

TIO

NS

Chemical probe available

ERa

PPARa PRRARa

MR

LXRa

PPARdTR

bRORg

ERb

HNF4a

SHP

SF1

Rev-erb

a

COUP2TR

aLR

H1

NGFIBg

RXRaRXRg

ERRb

GCNFTR

2

COUP30

500

1000

1500

2000

2500

3000

NUCLEAR HORMONE RECEPTOR

The power of open access reagents

No chemical probes available

Can we be proactive?Epigenetics – a pioneer area of science and medicine

Number of Citations

Fam

ily m

embe

r

CloningExpression

& Purification

Crystallography

The SGC: Delivered(ing) on its core mandate

Construct Design

Wellcome Trust

Sweden

CanadaOntario

GSKNovartisMerck

• >2000 purified human proteins

• >1000 human crystal structures

CloningExpression

& Purification

Crystallography

Pushing the pre-competitive boundary

Construct Design

Wellcome Trust

Sweden

CanadaOntario

GSKNovartisMerck

• >2000 purified human proteins

• >1000 human crystal structures

Medicinal Chemistry

Oxford:SGCChemistryBiochemistry

Toronto SGCUNC CICBDD

OICR

More than 50 universitiies

GSKPfizerLillyNovartis

• Epigenetics Chemical Probes Consortium

• Pre-competitive tools for new drug target validation

IndustryPublicDomain

Public/PrivatePartnership

ChemicalProbes

ScreeningChemistryStructureBioavailability

TargetValidation

No IPNo restrictionsPublication

DrugDiscovery

(re)ScreeningChemistryLead optimizationPharmacologyDMPKToxicologyChemical developmentClinical development

Our Model for Pre-Competitive Chemistry

Creative commons Proprietary

Jan 09

Well. Trust (£4.1M)NCGC (20HTSs)

GSK (8FTEs)

Ontario ($5.0M)

OICR(2FTEs)

UNC(3FTEs)

April 09

June 09July 11

Lilly, Pfizer

(8FTEs)

Epigenetics Chemical Probes ConsortiumAccessing expertise, assays and resource quickly

Sweden ($3.0M)

15 acad. labs

….more than $50M of resource

Novartis(8FTEs)

It’s working. The BET probe

797 403

0

20

40

60

80

100

Vehicle JQ1 Vehicle JQ1

Ki6

7 P

osi

tive

( %

)

250+ labsacross the globe

IdentifiedJan 10

PublishedSep 10

DistributedJan 11

Take home message:

SGC and its pharma partners have moved the pre-competitive boundary to medicinal chemistry

SGC OxfordSGC Toronto SGC Stockholm

How is this linked to the development of new medicines?

Structural Genomics Consortium

The Challenge of Pioneer Drug Discovery

• Number of pioneer drugs (Priority Reviewed NCEs) has not increased from 1993-2008

• Investment in pharmaceutical R&D has risen dramatically over this period

• >90% failure rate in clinical trials for pioneer drugs due to lack of efficacy

19931994

19951996

19971998

19992000

20012002

20032004

20052006

20072008

13121018

91619

97 7 9

1713

6 77 0

20

40

60

80

100

120

Yearly FDA Approvals

New Drug ApprovalsNew Chemical EntitiesPriority Reviewed NCEs

Public Data from Center of Drug Evaluation and Research: www.fda.gov/cder/

Impact on pharma and biotech in 2009

• $100B in R&D

• 21 drugs approved (7 truly novel)

• 70,000 pharma employees let go

• Investment houses writing that pharma should “get out of R&D”

• Industry relying on academia for “innovation”

How industry acceses “innovation”

What’s the “innovative” drug discovery process?

Target ID/

Discovery

Hit/ Probe/ Lead

ID

Clinical candidate

ID

Toxicology/ Pharmacy

Phase I

Phase IIa/ b

HTS LO

10% 30% 30% 90+%50%

Hypothesis generated

And tested

Failure rates

And here is how industry currently works

Target ID/

Discovery

Hit/ Probe/ Lead

ID

Clinical candidate

ID

Toxicology/ Pharmacy

Phase I

Phase IIa/ b

HTS

30% 30% 90+%

Target ID/

Discovery

Hit/ Probe/ Lead

ID

Clinical candidate

ID

Toxicology/ Pharmacy

Phase I

Phase IIa/ b

30% 30% 90+%

Target ID/

Discovery

Hit/ Probe/ Lead

ID

Clinical candidate

ID

Toxicology/ Pharmacy

Phase I

Phase IIa/ b

30% 30% 90+%

Target ID/

Discovery

Hit/ Probe/ Lead

ID

Clinical candidate

ID

Toxicology/ Pharmacy

Phase I

Phase IIa/ b

30% 30% 90+%

Target ID/

Discovery

Hit/ Probe/ Lead

ID

Clinical candidate

ID

Toxicology/ Pharmacy

Phase I

Phase IIa/ b

30% 30% 90+%

Target ID/

Discovery

Hit/ Probe/ Lead

ID

Clinical candidate

ID

Toxicology/ Pharmacy

Phase I

Phase IIa/ b

30% 30% 90+%

Target ID/

Discovery

Hit/ Probe/ Lead

ID

Clinical candidate

ID

Toxicology/ Pharmacy

Phase I

Phase IIa/ b

10% 30% 30% 90+%50%

LO

One example of the real worldTotal number of patents on TRPV1

Source: Derwent World Patent Index

Aurora Kinase Inhibitors

AT9283 PF03814735 AS703569 AMG-900 KW-2449 CYC116 AZD-1152 MLN-8054 MLN-8237 VX-667 PHA-739358 SU-6668 VX-680 SNS-314 ENMD-981693

Preclinical Phase I Phase II

• Antimitotic kinase – potential treatment for numerous cancer types

• Will also affect healthy proliferating cells – risk of low TI

• >60 separate organizations have pre-clinical programs with patents

• 11 compounds in Phase I

• Further 4 compounds in Phase II

• Estimated total expenditure >£200M

• No data available on outcomes of clinical studies, apart from rumours

>60

11

4

SGC OxfordSGC Toronto SGC Stockholm

What can we do?

Structural Genomics Consortium

Why not change the system?

Let’s imagine….

• A steady stream of pioneer targets whose links to disease have been validated in humans

• Engagement of top scientists and clinicians• A process in which regulators can fully collaborate to solve

key scientific problems• An engaged citizenry that promotes science and

acknowledges risk• Mechanisms to avoid bureaucratic and administrative

barriers• Sharing of knowledge to more rapidly achieve

understanding of human biology

Imagine…

• Pooled public and private sector funding into independent organization• Public sector provides stability and new ideas• Private sector brings focus and experience• Funding can focus explicitly on high-risk targets

• A pre-competitive model to test hypotheses• Disassociates science from financial gain• Will attract top scientists and clinicians• Will allow regulators to participate as scientists• Will reduce perceived conflicts of interests – engages citizens/patients• Will reduce bureaucratic and administrative overhead• Will allow rapid dissemination of information without restriction -

informs public and private sectors and reduces duplication

Progress

• arch2POCM concept• University of Toronto, University of Oxford, University of

California, San Francisco committed• CIHR and Genome Canada helping drive• Six large pharma engaged (none committed yet!)• Regulators (FDA) keen to be involved as participants• Patient groups fully engaged• Therapeutic foci selected

• Oncology, neuroscience and inflammation

• Business plan being written

What is needed

• A set of public funders keen to take the “risk” and drive the concept (Canada???)

• Leadership identified

• A core set of pharmaceutical funders

And when we succeed?• Less duplication• Broader scientific assessment• Faster dissemination of data• Pool academic and multiple pharma strengths and

funding – shared risk• Increasing knowledge of human biology (which will in

turn reduce attrition?)

More clinical POCs on novel targets….more clinically validated targets …..more novel drugs

How it might play out

1 or more partners develop probe *

Non developable

probe

Developableprobe

Otherpartnersdevelop

proprietary molecules

All partnersdevelop

proprietarymolecules

Invalidmechanism

Publishquickly

Proceeds toindependent

researchfund

Valid mechanism

POCAuction IND & all clinical

datato partners

80%

20%30%

70%

*Based on existing market exclusivity laws

Market size: ~$20B up for grabs

Potential opportunities for research and business

1. Academic partnerships that deliver new targets2. High value clinical trials3. Contract research organizations with leading edge science4. Biotech companies with compounds and technologies

Potential impact

5. More industry funding for University and Hospital-based research6. A business community built on high value service7. A clinical trial network that works on innovative targets8. Better business climate for biotech due to enhanced links with industry

Commercial opportunities for Canada in the new “open access” drug discovery ecosystem