Consortia-BasedStrategiesinNeurodegenerativeDiseases:CriticalPathInstitute’sTrackRecordinCollaborativeEffortsMarthaA.Brumfield,PhDPresident&CEO

Agenda

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• C-PathModelforCollaborationandWhereWeFocus

• InnovativeDrugDevelopmentTools

• WhatIsInScopeforThisCollaboration

• CriticalImportanceofSharingData

HowC-PathWorks:APublic-PrivatePartnership

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• Actasatrusted,neutralthirdparty• Convenescientificconsortiaofindustry,academia,andgovernmentforsharingofdata/expertiseü Thebestscienceü Thebroadestexperience

ü Activeconsensusbuildingü Sharedriskandcosts

• EnableiterativeEMA/FDA/PMDAparticipationindevelopingnewmethodstoassessthesafetyandefficacyofmedicalproducts

• Officialregulatoryendorsementofnovelmethodologiesanddrugdevelopmenttools

C-PathConsortia

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Coalition Against Major DiseasesFocusing on diseases of the brain

Coalition For Accelerating Standards and TherapiesData standards

Critical Path for Parkinson’s ConsortiumEnabling clinical trials in Parkinson’s Disease

Critical Path to TB Drug RegimensAccelerating the development of TB drug regimens and diagnostics

Duchenne Regulatory Science ConsortiumDuchenne Muscular Dystrophy

International Neonatal ConsortiumNeonatal clinical trials

Polycystic Kidney Disease Outcomes ConsortiumNew imaging biomarker for PKD

Multiple Sclerosis Outcome Assessments Consortium Drug Effectiveness in MS

Patient-Reported Outcome ConsortiumAssessing treatment benefit

Electronic Patient-Reported Outcome ConsortiumElectronic capture of treatment benefit

Predictive Safety Testing ConsortiumDrug safety

Pediatric Trials ConsortiumDeveloping effective therapies for children

BiomarkersClinicaloutcomeassessmentinstruments

ClinicaltrialsimulationtoolsDatastandardsInvitrotools

Transplant Therapeutics ConsortiumNew drug development tools for transplantation

Type 1 Diabetes ConsortiumQualifying biomarkers for type 1 diabetes

Huntington's Disease Regulatory Science ConsortiumExpediting approval of Huntington's therapeutics

C-PathRegulatorySuccesses

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ADclinicaltrialdatabase

ADclinicaltrialsimulationtool

EMAqualifiedADbiomarker

FDALettersofSupport- ADbiomarkers

30therapeuticareausersguidesacross25differentdiseaseareas,CDISC

FDAandEMAletterofsupport- PDbiomarker

EMAqualifiedHollowFiberSystemforTuberculosis

ReSeqTB dataplatform

TotalKidneyVolumeImaging(TKV)biomarkerqualifiedwithEMAandFDA

FDAletterofsupport(TKV)

PKDclinicaldatabase

EMA/FDA/PMDAqualifiednon-clinicalkidneysafetybiomarkers

FDAandEMAlettersofsupport:- Kidneybiomarkers

- Skeletalmuscleinjurybiomarkers

- Drug-inducedliverinjury

EXAMPLES OF HOW BIOMARKERS ARE USED IN DRUG DEVELOPMENT

Basic Research

Prototype Design or Discovery

Preclinical Development

Clinical Development FDA Filing/ Approval

and LaunchPhase 1 Phase 2 Phase 3

Molecular Pathways Leading to Disease

• Preclinical Safety Assessment

• Mechanism of Action• Dose Selection

• Stratification• Patient Selection• Enrichment

• Dose Selection• Safety Assessment• Efficacy Assessment

• Mechanism of Action• Drug Target Selection

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CourtesyofShashiAmur,OfficeofTranslationalSciences,FDACDER

SomeEnablersforBiomarkerDevelopment

• Datastandards

• Dataquality

• Datareproducibility

• Statisticalconsiderations

• Assay/imagingconsiderations/validation

• Assay/imagingprotocols

• Establishingcutpoints

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CourtesyofShashiAmur,OfficeofTranslationalSciences,CDER

Huntington’sDiseaseRegulatoryScienceConsortium:Scope

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Ourworkinvolvesmulti-stakeholdercollaborationinapre-competitivespace.Clarityregardingwhatisinandoutofscopeisveryimportant.Herearehigh-levelprinciples:

INSCOPE

• PromotedevelopmentofinnovativedrugdevelopmenttoolstobeincorporatedintoregulatoryapproachescriticalforadvancingsafeandeffectiveHDtherapies

• Enableprotectedmechanismsforinformationanddatasharinginthecollaborationamongindustry,academiccenters,patients,regulatoryandothergovernmentagencies

• Fosterawarenessoftheimportanceofdatastandardizationandtheneedtofocusonearlystageofdisease

• FocusonneedsofpeoplewithHD,needsoftherapeuticdevelopers,needsofregulators

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Huntington’sDiseaseRegulatoryScienceConsortium:Scope

• Discussions,evaluations,analysis,etc.thatpertaintospecific:• Productsortherapeuticsindevelopment• Clinicaltrialsspecifictoasingletherapeutic• Protocolsspecifictoasingletrial• Vendors• Researchsites• Investigators• HD-RSCMembers• Governmentadvocacy

• Discoveryof/basicresearchregardingnewbiomarkersandotherclinicaldevelopmenttools;rather,wefocusonassuringappropriateanalyticalandclinicalvalidationandadequateevidencegatheringtosupporttheiruseindrugdevelopment

OUTOFSCOPE

CriticalFactorsThatEnableCollaboration

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• MemberLegalAgreement

• Governance

• Scientific,Regulatory,andProjectManagementExpertise

• DataCollaborationCenter- DataContribution&DataUseAgreements

HistoryandEvolutionofDataSharing

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Past

• Data sharing among industry was extremely rare

• Academics misconstrued publishing of trial summary results as “data sharing”

• Trial participants always assumed their data were being shared

HistoryandEvolutionofDataSharing

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Past

• Extremely rare for industry• Academics misconstrued

publishing of trial summary results as “data sharing”

Present

• Many databases with patient-level data exist, from both industry and academic sources

• Trial participants are now adamant their data be shared

• ICMJE and many funders require that actual data be published

• Big data initiatives promise much, but can they deliver?

• Smart data can lead to more insights and answers

DATACOLLABORATIONNEUTRALSPACE

HistoryandEvolutionofDataSharing

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Past

• Extremely rare for industry• Academics misconstrued

publishing of trial summary results as “data sharing”

Present

• Many databases with patient level data from both industry and academic sources

• ICMJE and many funders requiring actual data be published

• Big data initiatives promise much but can they deliver?

• Smart data can lead to more insights and answers

DATACOLLABORATIONNEUTRALSPACE

The Emerging Future

• Disease-specific databases containing 10,000+ patient-level data fields that can be tapped to inform decisions

• Databases containing data from safety biomarkers, collected across multiple diseases, from multiple INDs, NDAs, that inform our learning

• Real-world data structured in a consistent manner

C-PathDataMappingandIntegrationProcess

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TherapeuticAreaDataStandards:KeytoCombiningDatasets

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ClinicalDataContributedtoC-Path

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Clinicaldata:97studies54,044subjects

Note:nonclinical119studies.6296subjects.ReSeqTB:5628IndividualIsolates

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Jun2014 Jun2015 Jun2016 Jun2017

Subjects

T1D

DuchenneMuscularDystrophy

Kidneyhealthyvolunteerstudy

Polycystickidneydisease

Multiplesclerosis

Tuberculosis

Parkinson'sdisease

Alzheimer'sdisease

SuccessfulC-PathDataCollaborationProjects

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ADplacebo-arm,patient-leveldatausedtodevelopdiseaseprogressionmodelandClinicalTrialsimulationtoolPKDdatabasetosupportregulatoryqualificationofprognosticbiomarkerCPTR:TBclinicalandpre-clinicaldataaggregationusedtosupportmodellingandsimulationdevelopmentMSplacebo-armdatatosupportregulatoryqualificationofPerformanceOutcomeMeasureParkinson’sdiseasedatabase(inprogress)

InsupportofFitforPurposediseasemodelDuchennemusculardystrophydatabase(inprogress)InsupportofFitforPurposediseasemodel

RoleofPublic-PrivatePartnerships

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Astheproductsofthesepartnershipsmature,itisincumbentuponallstakeholderstosharethecollectiveknowledgeandimpactfromintegratingthedeliverablesintodrugdevelopmentprograms.Cataloguingandsharingtheseexperiencesandsuccessespubliclywillenablefurtherlearningandencouragetheadoptionofthesenovelapproachestoachieveunmetpublichealthneeds.Withcontinuedpartnership,multisectorcollaborationscancontinuetoadvanceinnovationsinmedicalproductdevelopmentandthehealthofallAmericans.

ThankYouwww.c-path.org

C-PathCoreCompetencies

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• Regulatoryqualificationofpreclinicalandclinicalbiomarkersforsafety,efficacy,andtrialenrichment

• Outcomeassessmentinstrumentdevelopment

• Comprehensivemodeling&simulationprograms

• Novelinvitro toolstoexpediteproof-of-concept

• Clinicaldatastandardsdevelopment

• Securedatamanagement,standardization,curation,databasedevelopment,andhostingforexternaluse

• Formingandmanaginglargeinternationalconsortia

• Formingcollaborationswithnon-C-Pathconsortia(e.g.,IMI,FNIH)