SGC Oxford SGC Toronto

A new model to reduce waste in clinical development:

open access collaboration

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$$

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$labs$

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$discovery$

$

This(model(is(working(

SGC: $$

$

•  structures$ $(2003%$$$$$)$

•  inhibitors$ $(2009%$$$$$)$

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,$pharma)$

Nature, Dec 23, 2010

Novel inhibitor for BET sub-family (JQ1)

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

JQ1(reduces(prolifera@on(in((two(pa@ent(derived(cell(lines(

797 403

0

20

40

60

80

100

Vehicle JQ1 Vehicle JQ1

Ki67

Pos

itive

( %

)

KI67 positive = proliferating

JQ1(induces(apoptosis(

Annexin V, marker of early apoptosis PI = propidium iodide, marker of late apoptosis STA = Staurosporine

JQ1(reduces(tumour(size$$

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$9$

Lysine(Demethylases(

SGC structure

Non SGC structure

Catalytic domain purified

Alphascreen in place

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$H3$

JMJD3(inhibitor(reduces((bone(resorp@ve(ac@vity(in(osteoclasts(

RANKL$=$receptor$ac3vator$of$nuclear$factor$KB$ligand$RANK$=$osteoclast$cell$surface$receptor$$

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

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$3rd$

Screen

ing$/$Ch

emistry$

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(

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

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((

Most companies have patents for TRPV1

…in probably all therapeutic areas

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$shared$

Pa@ent(groups(will(enable(faster(and(cheaper(studies(

• Will$facilitate$recruitment$

• Will$minimise$payments$

Unprecedented(input(from(regulators(

$•  help$design$new$clinical$studies$

•  help$validate$new$biomarkers$

•  pave$path$for$new$targets$

•  host$Arch2POCM$data$$

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

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

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$$$%$high$level$mee3ng$being$arranged$in$OJawa$$

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$

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$

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$

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$$%  have$few$new$drugs$%  will$con3nue$to$waste$money$%  will$con3nue$to$harm$pa3ents$%  further$erode$the$this$industry$$

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,$Takeda$