This document proposes a new public-private partnership (PPP) model to validate novel drug targets through clinical proof-of-concept (POCM) studies more efficiently. It outlines the achievements and impact of the existing Structural Genomics Consortium (SGC) model of open access drug discovery. The new PPP would conduct precompetitive Phase II clinical trials on novel targets from academics and share all results and reagents openly to accelerate target validation and drug development while reducing waste. Regulators, patient groups, and funders have expressed interest in collaborating to design studies and leverage resources under this model.

1. SGC OxfordSGC Toronto
A new model to reduce waste
in clinical development:
open access collaboration

2. Outline(
• SGC$
$%$what$is$it$
$%$our$objec3ves$
$%$achievements$
$%$impact$(2$examples)$
• Now$extending$this$model$into$clinic:$create$a$
new$PPP$to$do$Phase$II$studies$with$novel$targets,$
pre%compe33vely$
• Lessons$
$

3. What(is(SGC?(
• PPP$ $%$GSK,$Pfizer,$Novar3s,$Lilly,$AbboJ,$Takeda$
$ $%$GC,$Ontario,$CIHR,$Wellcome$Trust$
$
• Two$other$pharmas$joining$by$end$month$
$
• Private$funding $ $%$2003:$$5M$
$ $ $ $%$2007:$$15M$
$ $ $ $%$2012:$$64M$
$
• 200$scien3sts$in$Universi3es$of$Toronto$and$Oxford$
• Academic$network:$>250$labs$

4. Output(
• Generate$freely$available$reagents:$$
$%$novel$human$therapeu3cally$relevant$
$ $proteins,$$
$%$novel$assays,$$
$%$novel$structures,$$
$%$novel$inhibitors,$$
$%$novel$an3bodies$
• Give$to$collaborators$to$discover$new$targets$
for$drug$discovery$
$

5. This(model(is(working(
SGC:$$
$
• structures$ $(2003%$$$$$)$
• inhibitors$ $(2009%$$$$$)$

6. Achievements(
• Have$purified$>$2000$human$proteins$
• More$than$1300$human$protein$structures$(nearly$
25%$of$PDB)$
• 12$inhibitors$(probes)$of$epigene3c$proteins$
• >1$publica3on$per$week$(Science,$Cell$or$Nature$–$
every$month)$
• Several$hundred$reagents$distributed$freely$every$
year$(academia,$biotech,$pharma)$

7. Nature, Dec 23, 2010
Novel inhibitor for BET sub-family (JQ1)

8. JQ1(has(ac@ve(and(inac@ve(enan@omers((

9. JQ1(reduces(prolifera@on(in((
two(pa@ent(derived(cell(lines(
797 403
0
20
40
60
80
100
Vehicle JQ1 Vehicle JQ1
Ki67Positive(%)
KI67 positive = proliferating

10. JQ1(induces(apoptosis(
Annexin V, marker of early apoptosis
PI = propidium iodide, marker of late apoptosis
STA = Staurosporine

11. JQ1(reduces(tumour(size$$

12. Scien@fic,(drug(discovery(&(economic(
impact((
! Published Dec 23 2010 - already cited >90 times
! Distributed to >250 labs/companies - profile in several therapeutic areas
! Pharmas - started proprietary efforts
! Harvard spin off - $15 M seed funding
! Opened new area:
Zuber$et$al$:$$ $BRD4$as$target$in$acute$leukaemia $ $Nature,$2011$Aug$3$
Delmore$et$al:$ $JQ1$suppresses$myc$in$mul3ple$myeloma$ $Cell,$2011$Volume$146,$$904%917,$16$
Dawson$et$al:$ $BRD4$in$MLL$(isoxazole$inhibitor) $ $Nature$2011,$Oct$2.$
Blobel$et$al:$$ $Novel$Targets$in$AML $ $ $Cancer(Cell,$2011,$Sep$13$
Mertz$et$al$:$ $Myc$dependent$cancer $ $ $PNAS,$2011,$Oct$4$
Zhao$et$al:$ $ $Post$mito3c$transcrip3onal$re%ac3va3on $Nature(Cell(Biology,$2011$Oct$9$

13. Lysine(Demethylases(
SGC structure
Non SGC structure
Catalytic domain purified
Alphascreen in place

14. OXFORD CENTRE FOR OA PATHOGENESIS!
!Novel(JMJD3(inhibitor(produces(dose(related(inhibi@on((
of(TNF(release(from(human(macrophages(
Inhibitor$$
% increases$K27me3,$$
% decreases$RNApolII$
% no$change$in$H3$

15. JMJD3(inhibitor(reduces((
bone(resorp@ve(ac@vity(in(osteoclasts(
RANKL$=$receptor$ac3vator$of$nuclear$factor$KB$ligand$
RANK$=$osteoclast$cell$surface$receptor$

16. Vehicle
D3 inhib
Red$dots:$propidium$iodide$stained$apopto3c$cells$
D3$inhibi3on,$increases$K27me3,$decreases$BCL2,$increases$apoptosis$
JMJD3 inhibitor increases apoptosis
in human breast cancer cells

17. UHRF1$
SMYD3$
MLL$
PRMT3$
SETDB1$
FALZ$
BRD9$
PCAF$
JMJD2$2nd$$
JMJD3$2nd$$
PB1@2$
PHIP$
PRMT5$
SMYD2$
BRPF3$
ATAD2$
PB1@5$
JMJD1$
CECR2$
BAZ2A$
SETD7$
FBXL11$2nd$
JMJD2B$
MMSET$
SUV420H1/2$
JMJD3$3rd$
Screening$/$Chemistry$
In vitro assay Cell assay
JARID1A$
Potent &
Selective
Potent
Weak
None
Probe/ Tool
Compound
TIF1α$
JMJD2A$
JMJD2C$
SPIN1$
SUV39H2$
EP300$
L3MBTL1$
53BP1$
SETD8$
JMJD3$
BET$2nd$$
G9a/GLP$BET$
PHD2$
L3MBTL3$
CREBBP$4th$
WDR5$
DOT1L$BAZ2B/A$
JMJD2$
CREBBP$1%3$
G9a/GLP$2nd$$
SMARCA4$
Cell activity
Pan$2%OG$
Me$Lys$Binders$BRD$ (H)MT$ KDM$HAT$ TUD$2OG$Oxygenase$ WD$Domain$
SMARCA4$2nd$$
JARID1C$
BAZ2B/A$2nd$$
EZH2$
Epigene@cs(inhibitor(pipeline(

18. Nearly(all(novel(targets(fail(at((
clinical(POC(
Target((
ID/((
Discovery(
Hit/((
Probe/((
Lead((
ID(
Clinical((
candidate((
ID(
Tox./((
Pharmacy(
Phase((
I(
Phase((
IIa/(b(
HTS LO
10% 30% 30% 90+%50%
this is killing
our industry
…we can generate “safe” molecules, but they
are not developable in chosen patient group

19. This(failure(is(repeated,(many(@mes(
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
…and(outcomes(are(not(shared((

20. Most companies have patents for TRPV1

21. …in probably all therapeutic areas

22. Building(a(new(PPP(to((
validate(novel(targets(in(pa@ents(
• Academics,$regulators,$ci3zens,$health$industry,$
through$to$Proof$Of$Clinical$Mechanism$$
• POCM:$Phase$IIa,$Exp$Med,$highlight$clinical$poten3al$
• Regulators$$and$pa3ent$groups$$want$to$be$ac3ve$
par3cipants$
• Knowledge$crea3on$endeavour$
• All$reagents$will$be$freely$shared$

23. Pa@ent(groups(will(enable(faster(
and(cheaper(studies(
• Will$facilitate$recruitment$
• Will$minimise$payments$

24. Unprecedented(input(from(
regulators(
$
• help$design$new$clinical$studies$
• help$validate$new$biomarkers$
• pave$path$for$new$targets$
• host$Arch2POCM$data$
$

25. Reagents(and(publica@ons(will(facilitate(
collabora@on,((leveraged(funds,(and(POCMs$
!
Lead(
iden@fica@on(
$
$$$$$$$$
$$$$$$$(
(
$$$$$$$$ $$$$$$$$Phase(I(
$$$$$$
$$$$$$$$$Phase(II(
$
Preclinical
Lead
optimisation
Efficacy
in cellular
assays
Efficacy
in in vivo
“disease”
models
ADME,
toxicology
Human
safety &
tolerability
Efficacy
in patients
Lead
Clinical
candidate
Phase I
asset
Phase II
asset POCM
in vitro
probe
in vivo
probe

26. What(happens(aYer(POCM?(
Develop((
molecule*(
Non(
(developable(
molecule(
Developable(
molecule(
Develop(
proprietary((
molecules(
Develop(
proprietary(
molecules(
Invalid(
mechanism(
Publish(
quickly(
Proceeds(to(
independent(
fund(
Valid((
mechanism(
POCM Auc@on((
IND(
(
90%
10%
30%
70%
*Based on existing
market exclusivity laws

27. Status(
• Established$SAB$(Bell,$Feldman,$Hyman,$Ford$
Hutchison)$
• Project$started$in$cancer$
• Project$under$discussion$in$neuroscience$
$%$schizo,$au3sm,$depression,$AD$
$%$CIHR$earmarked$$30M,$likely$get$other$
$public$funds$
$%$6$pharmas$interested$$
$%$high$level$mee3ng$being$arranged$in$OJawa$$

28. Advantages(of(no(IP(before(POCM$
$
$
• $ pool$private$funds$and$capabili3es$
• $ access$significant$public$funds$
• $$$$$$access$philanthropic$funds$
• $ access$many$academic$labs$quickly$and$
$freely$
• $ access$input$of$pa3ent$groups$
• $ access$regulatory$input$in$an$
$unprecedented$way$

29. Output/(impact(of(this(model(
• Generate$clinically$validated/$de%risked$targets$
for$industry$$
• More$novel$medicines$for$pa3ents$
• Reduce$duplica3on$and$wastage$
• Stop$pa3ents$being$needlessly$dosed$

30. Lessons(
• Academia$needs$quality$probes/$candidates$to$help$discover/$
validate$new$targets$
• Pre%compe33ve$efforts$catalyse$compe33ve$endeavours$
• Based$on$cellular$data$it$is$almost$impossible$to$predict$which$
pa3ents$will$benefit$
• Target$valida3on$occurs$in$pa3ents$with$quality$molecules$
• Industry$needs$$
$%$novel$validated$targets,$$
$%$novel$biomarkers$
$%$novel$methodologies$to$stra3fy$pa3ents$
$%$to$share$risk$

31. Drug(Discovery(is(high(risk(
• We$must$$
% pool$resources$and$capabili3es$
% rapidly$disseminate$$findings$
% delay$IP$un3l$aqer$target$is$validated$in$pa3ents$
• If$we$do$not$WE$will$$
% have$few$new$drugs$
% will$con3nue$to$waste$money$
% will$con3nue$to$harm$pa3ents$
% further$erode$the$this$industry$$

32. Acknowledgements(
• SGC:$Aled$Edwards,$Stefan$Knapp,$Udo$Oppermann$
$
• SAGE$Bionetworks:$Stephen$Friend,$Thea$Norman$
$
• Harvard:$Jay$Bradner$
$
• CIHR,$Genome$Canada,$Ontario,$Wellcome$Trust$
• GSK$(Rab$Prinjha,$David$Wilson),$Novar3s,$Pfizer$
(Kevin$Lee),$Lilly,$AbboJ,$Takeda$