A Peek at Dpharm 2012
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A Peek at Dpharm 2012

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Disruptive Innovation presentation from 2nd Annual Disruptive Innovations to Advance Clinical Trials, Sept 2012, Boston, MA on 'A new model to reduce waste in clinical development', from Chas ...

Disruptive Innovation presentation from 2nd Annual Disruptive Innovations to Advance Clinical Trials, Sept 2012, Boston, MA on 'A new model to reduce waste in clinical development', from Chas Bountra

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    A Peek at Dpharm 2012 A Peek at Dpharm 2012 Presentation Transcript

    • SGC OxfordSGC 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:$$ $ •  structures$ $(2003%$$$$$)$ •  inhibitors$ $(2009%$$$$$)$
    • Achievements( •  Have$purified$>$2000$human$proteins$ •  More$than$1300$human$protein$structures$(nearly$ 25%$of$PDB)$ •  12$inhibitors$(probes)$of$epigene3c$proteins$ •  >1$publica3on$per$week$(Science,$Cell$or$Nature$–$ every$month)$ •  Several$hundred$reagents$distributed$freely$every$ year$(academia,$biotech,$pharma)$
    • Nature, Dec 23, 2010 Novel inhibitor for BET sub-family (JQ1)
    • JQ1(has(ac@ve(and(inac@ve(enan@omers((
    • JQ1(reduces(prolifera@on(in(( two(pa@ent(derived(cell(lines( 797 403 0 20 40 60 80 100 Vehicle JQ1 Vehicle JQ1 Ki67Positive(%) KI67 positive = proliferating
    • JQ1(induces(apoptosis( Annexin V, marker of early apoptosis PI = propidium iodide, marker of late apoptosis STA = Staurosporine
    • JQ1(reduces(tumour(size$$
    • 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$$ PB1@2$ PHIP$ PRMT5$ SMYD2$ BRPF3$ ATAD2$ PB1@5$ JMJD1$ CECR2$ BAZ2A$ SETD7$ FBXL11$2nd$ JMJD2B$ MMSET$ SUV420H1/2$ JMJD3$3rd$ Screening$/$Chemistry$ In vitro assay Cell assay JARID1A$ Potent & Selective Potent Weak None Probe/ Tool Compound TIF1α$ JMJD2A$ JMJD2C$ SPIN1$ SUV39H2$ EP300$ L3MBTL1$ 53BP1$ SETD8$ JMJD3$ BET$2nd$$ 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$$ EZH2$ Epigene@cs(inhibitor(pipeline(
    • Nearly(all(novel(targets(fail(at(( clinical(POC( Target(( ID/(( Discovery( Hit/(( Probe/(( Lead(( ID( Clinical(( candidate(( ID( Tox./(( Pharmacy( Phase(( I( Phase(( IIa/(b( HTS LO 10% 30% 30% 90+%50% this is killing our industry …we can generate “safe” molecules, but they are not developable in chosen patient group
    • This(failure(is(repeated,(many(@mes( Target$$ 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$