Coalition against Major Diseases (CAMD) · Coalition against Major Diseases Work Scope CAMD...

Coalition against Major Diseases

(CAMD)

Work Scope 1.1JULY 2009

Coalition against Major Diseases Work Scope

CAMD �

MeMBers

• AbbottLaboratories• AllianceforAgingResearch• Alzheimer’sAssociation• Alzheimer’sFoundationofAmerica• AstraZenecaPharmaceuticalsLP• Bristol-MyersSquibbCompany• DaiichiSankyo• EliLillyandCompany• F.HoffmannLaRoche,Ltd.• ForestResearchInstitute• Genentech,Inc.• GlaxoSmithKline• Johnson&Johnson• NationalHealthCouncil• NovartisPharmaceuticalCorporation• Parkinson’sActionNetwork• Parkinson’sDiseaseFoundation• Pfizer,Inc.• sanofi-aventis,US,Inc.• Schering-Plough• WyethPharmaceuticals,Inc.

NON-VOTING PARTICIPANTS

•U.S.Food&DrugAdministration(FDA)• EuropeanMedicineAgency(EMEA)•NationalInstituteonAging(NIA)•NationalInstituteofNeurologicalDisorders(NINDS)

IN COLLABORATION WITH

• EngelbergCenterforHealthCareReformattheBrookingsInstitution


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taBle oF Contents

OVERVIEW...............................................................................................................................................3

CHAPTER I: INTRODUCTION.............................................................................................................4

CAMDCaseStatement..........................................................................................................................4 Collaboration..........................................................................................................................................7 Background............................................................................................................................................7 InitialWorkgroups...............................................................................................................................10 WorkflowAmongWorkgroups.............................................................................................................11 StructureofWorkgroups......................................................................................................................12CHAPTER II: PROPOSED WORKGROUPS FOR RESEARCH.....................................................13

Workgroup1–Data.............................................................................................................................13 SubgroupA:DataSources,StandardsandSharing.............................................................14 SubgroupB:DataInfrastructure.........................................................................................19 Workgroup2–Disease-ProgressionModeling....................................................................................26 ProcesstoDetermine/CompileDataNeeds........................................................................28 QuantitativeNeurodegenerativeDiseaseModelCreation...................................................29 Workgroup3–BiomarkerEvaluation.................................................................................................32 Process.................................................................................................................................32 Deliverables.........................................................................................................................34 Workgroup4–HealthAuthoritiesSubmissions...................................................................................35 AllianceswithPatientCommunities....................................................................................................36CHAPTER III: SUPPORT AND COMMUNICATIONS TEAM.......................................................37 AdministrationandProjectManagement............................................................................................37 AnnouncementsandOngoingExternalCommunications...................................................................38

APPENDICES..........................................................................................................................................40 AppendixA:GlossaryofTermsandAcronyms..................................................................................40 AppendixB:OverviewandPurposeoftheCAMDLegalAgreement................................................42 AppendixC:CAMDParticipantRoles................................................................................................44

REFERENCES CITED...........................................................................................................................45


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oVerVieW

ThegoaloftheCoalitionAgainstMajorDiseases(CAMD)istobringtogethermajorpharmaceuti-calcompanies,theU.S.FoodandDrugAdministration(FDA),theEuropeanMedicineAgency

(EMEA),theNationalInstituteonAging(NIA),theNationalInstituteofNeurologicalDisordersandStroke(NINDS),andpatientgroupsinacollaborationtodevelopnewknowledgethatwillenhancetheindustry’sabilitytodevelopinnovativenewtherapies.CAMDwillfocusfirstonAlzheimer’sandParkinson’sdiseasesandthenexpandtootherdiseases.

Thisworkscopedefinestheroleoftheinitialfourworkgroupsthatwillgeneratenewknowledgeresult-ingintoolstoimprovethemedicalproductdevelopmentprocess.Themajordeliverablesofthecoalitionare:

• TosubmitbiomarkerstotheFDAforqualificationtoaccuratelydiagnosedisease,stratifypatient populations,andpredictpatientoutcomes. • TosubmitmultiparametermodelsofdiseaseprogressiontotheFDAforqualificationthatcan beusedtoprojecttheeffectsofpotentialdiagnosticsandtreatments,aswellasinfluencethe designofclinicaltrials. • TodevelopanintegrateddatabasefromcompletedtrialsinacommonClinicalDataInterchange StandardsConsortium(CDISC)standardformatusableforresearchbycoalitionmembersand others.

Aworkgrouphasbeencreatedtoworkoneachmajordeliverable.AfourthworkgroupwillbeformedtoassistinthecreationofthedossiersforsubmissiontotheFDA.

Itisnottheintentofthecoalitiontoduplicatecurrenteffortsalreadyunderwayintheseareas,butin-steadtoleverageexistingdataandknowledge,createconsensusonmethodstoadvanceproductdevel-opment,andmakethemethodsavailableforbroadapplications.Whereappropriate,theresultingapplieddataandnewinformationwillbesubmittedforFDAreview,withthegoaltohavethemqualified,andinallcases,tohavethemwidelyavailableforuseinnewmedicalproductdevelopment.

ThecoalitionisbeingfoundedandsupportedbytheCriticalPathInstitute(C-Path)incollaborationwiththeEngelbergCenterforHealthCareReformattheBrookingsInstitution.CAMDisaself-govern-ingentityadvisedbyscientistsfromtheFDA,EMEA,andtheNationalInstitutesofHealth(NIH)anddirectedbyitsmembers,whoarepharmaceuticalandbiotechcompaniesandpatientgroupscommittedtoadvancingthecareofpatientswithneurodegenerativediseases.


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CAMD CASE STATEMENT

Oneofthegreatestchallengesfacingbiomedicalsciencesinthe21stcenturyisthedevelopmentoffun-damentallybettertreatmentsforneurodegenerativediseases.Thetwomostprevalentofthese,Alzheim-er’sdiseaseandParkinson’sdisease,exertaheavyandrapidlygrowinghumanandeconomicburdenonoursociety.Ourlackofknowledgeaboutthespecificcause(s)ofeitherdiseaseisamajorobstacletothedevelopmentoftreatmentsthatwouldhavethepotentialtoeithercureorprevent.

InordertoreplicatethesuccessfulprocessthatwasusedtodevelopHIV/AIDSdrugsduringthe1980s,theCriticalPathInstitute(C-Path),incollaborationwiththeEngelbergCenterforHealthCareReformattheBrookingsInstitution,hasformedtheCoalitionAgainstMajorDiseases(CAMD),whichincludesadvisorsfromtheFDA,EMEA,NIH(NIAandNINDS),andacademia.Membersincludepatientgroupsandthemedicalproductsindustry.Acoordinatingcommitteewithrepresentationfromeachmemberorganizationwilldirect,prioritize,coordinate,andoverseetheworkofthecoalition.CAMDwillfocusfirstonAlzheimer’sandParkinson’sdiseasesandthenexpandtootherdiseaseswithsignificantpublichealthimplications.

Theinitial,veryambitiousgoalofCAMDistoestablishacommonresearchsupportinfrastructureforusingpooledcontrolorplacebopatientdatafromclinicaltrialstocreatequantitativedisease-progressionmodelsforbothAlzheimer’sdiseaseandParkinson’sdisease.Thesemodelswillutilizealreadydefineddatastandardswhenpossible,andthecoalitionwilldevelopnewdatastandardswhengapsexist.Coalitionmembersalsowillworktogethertoincorporatedataonimagingandbiochemicalandmolecularbiomark-ersthathavethegreatestpotentialtoidentifythosepatientswiththemaximumlikelihoodofderivingben-efitfromand/orthelikelihoodofharmfromspecifictherapies.Importantly,whereappropriateanduseful,CAMDmemberswillcollaboratetoassemble,evaluate,andsubmittheevidencesupportingrequestsfortheFDAtodesignatesuchtoolsasqualifiedforuseindrugdevelopment.Thesenewlyqualifiedtoolsthenwillbemadepubliclyavailableforallscientistsandcommercialdeveloperstoutilize.

TheCAMDCoordinatingCommittee,with21membersrepresented,metonSeptember22,2008,inWashington,D.C.,andauthorizedC-Pathtoenrolladditionalparticipantsandtodraftadetailedworkscopeofactivitiestobeexecutedoverthenextfewyears.ByJanuary2009thedraftworkscopewascompletedandbeganwiththecreationoffourmajorworkgroupsthatwillbesupportedbyateamfo-cusedonprovidingtheinformationtechnologyinfrastructureandtheinterorganizationalcommunicationnecessaryforeffectivecollaboration.

Itisnottheintentofthecoalitiontoduplicatecurrenteffortsalreadyunderwayinanyoftheseareas,butinsteadtogather,integrate,shareandleverageexistingdataandknowledgebymakingthemavail-ableforbroadapplicationandtohavetheresultinganalyticaltoolsandprocessesqualifiedbytheFDAwhereappropriate,sotheymaybewidelyutilizedinnewmedicalproductdevelopment.

cHApTer I: INTroDUcTIoN


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Alzheimer’sandParkinson’sdiseaseshavebeenchoseninitiallybecauseoftheirprevalence,impactonmorbidityandmortality,extensivepriordataavailable,andcurrentinvestmentbyacademia,governmentandindustryforbetterdiseaseunderstandingandinterventionsforpreventionorbettertreatment.TheoverallroadmapfortheCAMDactivitiesisshowninthefollowingdiagram(Figure1).

Theexecutionphaseofthecoalitionbeganinearly2009,withameetingofthecoordinatingcounciltolaunchtheinitialworkgroups.TheevidencewillbeevaluatedbytheworkinggroupsandsubmittedtotheFDAasvoluntaryexploratorydatasubmissions(VXDS).OnceaninternalconsensusisreachedwithinCAMDthatthereisadequateevidencetosupportthequalificationofagivenbiomarker,aBio-markerQualificationReviewTeam(BQRT)willbeformedattheFDAtoreviewthesubmissionpack-ageforqualification.Acceptancebythehealthauthorityagencieswillmeanthatthenewmethodsarethenqualifiedforuseindrugdevelopmentinadefinedmanner.

ThenewmethodsandtoolsfromCAMDareexpectedtohaveasignificanteffectonthedrugdevelop-mentprocess.Today,mostdrugcandidatesareidentifiedbecausetheyhavedemonstratedsomemea-surablechangeinalaboratorymodelthatisconsideredrelevanttoadisease.Thislabassay,ifitcanbelinkedtopatientswiththedisease,oftenhasthepotentialtobeausefulbiomarkerduringdrugdevelop-mentandperhapsinclinicalpractice.Biomarkerscanidentifysubsetsofpatientswithadiseasewhohavedistinctpatternsofprogressionoroutcomes.InCAMD,dataintegrationandsharingareplannedtocreateaquantitativedisease-progressionmodelthatincludesbiomarkersthatpotentiallyidentifydiscretepatientsubsetsofthedisease.Increasingly,a“diseasemodel”anda“drugmodel”areintegrated,andmodelingandsimulationareusedtosimulateanddesignclinicaltrialswithagreaterchanceofsuccess.Thedrugmodelincludesinformationaboutitspharmacokinetics,pharmacodynamics,andthepatient-specificfactorsthatinfluenceitsactions(e.g.,CYPisoformmetabolism).Diseasemodelsenablegreateraccuracyinpredictingtheoccurrenceofclinicallysignificanteventsandtheinfluenceofpotentiallyconfoundingfactors.

Figure1.CAMDRoadmap(VXDS=VoluntaryeXploratoryDataSubmission,BQR=BiomarkerQualificationReview).


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CAMDwilladdresstheneedforamorereliableandpredictableprocessofdrugdevelopmentforthesediseasesbycreatingscientificconsensusfornewtoolsandmethodsqualifiedbytheFDAforuseindrugdevelopment.AsshownbelowinFigure2,inputsforcreatingthediseasemodelwillcomefrommanyestablishedandnewsources.ThediseasemodelandbiomarkerswillbereviewedbytheFDAand“qualifiedforuse”wherepossible,andwillbecomepartofthedrugdevelopmentprocess.Thecombina-tionofqualifiedbiomarkersandquantitativediseasemodelswillprovideimportanttoolsforthephar-maceuticalindustrytousetoidentifypotentialnewtherapies,tolearnmoreaboutwhentomorequicklyterminatecandidatedrugsthathavealowprobabilityofsuccess,andtoensurethatwhenanewtherapyisfound,ithasamuchhigherprobabilitytomovethroughthedevelopmentandregulatorysystemsuc-cessfullyandmorerapidly.

CAMDalsowillprovideaframeworkforcontinuouslearningaboutthediseasesbecausethedatabaseandthediseasemodelswillbeenrichedasnewinformationbecomesavailable.Furthermore,theexperi-encewithAlzheimer’sandParkinson’sdiseasewillbereadilyexpandedtoasystematicexplorationformanyotherimportantdiseases.

Figure 2. CAMD’s contribution to integrated drug development.


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COLLABORATION

ThereisagreatdealofresearchunderwaytodayinbothAlzheimer’sandParkinson’sdiseases.TheAlzheimer’sStudyGrouprecentlypublishedareportonthechallengesofeffectivelyutilizingallofthisnewsciencetogenerateeffectivetherapiesforpatients.1TheCAMDstaff,aspartofthedevelopmentofthisWorkScope,hasmaintainedclosecommunicationwiththoseorganizationsinvolvedinactiveareasofresearch.TheBiomarkerConsortium,Alzheimer’sDiseaseNeuroimagingProject(ADNI),Parkin-son’sStudyGroup(PSG),andAlzheimer’sDiseaseCooperativeStudy(ADCS)haveallbeencontactedandinvitedtocollaboratewithCAMD.

CAMD’sinitialworkinvolvesthesharingofclinicaltrialinformationbyourcorporatememberstogen-eratethecoreinformationneededtobuildnewdiseasemodelsthatrepresentpopulations.Inaddition,wewillalsoseektoincorporatedatafromconcurrentresearchbyotherstosupplementthesediseasemodels,aswellastoenrichthesemodelswithprioritybiomarkerinformationfromotherresearchef-forts.TheactiveparticipationoftheFDAandtheircommitmenttoreviewdataforpossiblequalificationmakeCAMDnovelandespeciallyimportant.Wewillseekqualificationforthesemodelsandbiomark-ersandplacethemintothepublicrecordsoeveryonecanusethemtoenhanceresearchanddrugdevel-opmentforthesediseases.

BACKGROUND

ALZHEIMER’S DISEASE

Ithasbeenmorethan100yearssinceDr.AloisAlzheimerfirstdescribedthecaseofAugusteD.,apatientwithrapidlyfailingmemory,confusion,disorientation,troubleexpressingherthoughts,andunfoundedsuspicionsaboutherfamilyandhospitalstaff.Today,Alzheimer’sdisease(AD)—themostcommonformofdementia—affects4.6millionnewpatientsworldwideeachyear.Thereare5.1mil-lioncasesintheU.S.,mostofthemreceivingcareunderMedicare.By2030,thenumberofAmericans65andolderwithADwillhavegrownby50percentto7.7million.2ADisestimatedtoafflictabout10percentofpeopleoverage65and30to50percentofthoseoverage85.Asacauseofdeath,ADgrewby33percentfrom2000to2004,comparedtodeclinesinthepercentagesofdeathscausedbyheartdisease,stroke,andbreastcancer.ThedirectandindirectcostsofADandotherdementias,includingMedicareandMedicaidcostsandtheindirectcosttoemployersofcaregivers,ismorethan$148billionannuallyintheU.S.2Forthe10millionAmericanscaringforapersonwithADorotherdementia,theannualburden(intermsofreducedproductivityandlowerhealthstatus)hasbeenestimatedat$60bil-lion.2

Inthepast20years,morethan300drugshaveenteredtestingforAD,yetonlyfivehavebeenapprovedindevelopedcountries.Whilethesefivedrugshavesomeimpactonsymptomsforpatientswhohaveal-readydevelopedsignsofdisease,theydonotfundamentallyalteritscourse,andtheircost-effectivenesshasbeenquestioned.3,4ThougheffectiveADdrugsarebadlyneeded,5progresshasbeendifficult.


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ThereiscurrentlyaworldwideefforttoidentifyandvalidatebiomarkersofAD.Theidentificationofbiomolecules—proteins,genesandtheirpathways—combinedwithadvancedimagingtechnologies,promisestoinformonrisk,prevention,identificationoftreatmenttargetsandresponse,anddiseasepro-gression.ItisbelievedthatADisaheterogeneousdisease,comprisingseveralsubtypes,eachofwhichmayhavedifferentetiopathogeneticmechanismsleadingultimatelytoasimilarpathology.Inaddition,thetwoanatomicalhallmarksofAD,amyloidplaquesandneurofibrillarytangles,arenowknown,re-spectively,tobeassociatedwithagingintheabsenceofdementiaandarefoundinotherdiseasestatesaswellasAD.

Forthesereasons,itishighlylikelythatpanelsofbiomarkers,combinedwithimagingtechnologies,willbeneededtospeedprogressinaccurateearlydiagnosisandsuccessfultreatmentstrategies.6Therealpushistowarddevelopmentofantecedentmarkerstoenableearlydetectionorpreventionofdisease,basedonthehypothesisthatbiochemicalchangesoccurfarinadvanceofcognitivedeclineandbraindamage.7

Todate,fourgenesassociatedwithanincreasedriskofADhavebeenidentified.Mutationsinpreseni-lin1(PS1)andpresenilin2(PS2)arethoughttocauseearly-onsetAD.Mutationsingenesexpressingamyloidprecursorprotein(APP)associatedwithβ-andγ-secretaseareanotherrarecauseofearly-onsetfamilialAD.MutationsinPS1,PS2andAPPthatareassociatedwithADallresultinincreasedβ-amy-loid-42(Aβ42)production.Thesemutations,however,arerare,andnogenestodatehavebeenfoundtobeassociatedwiththecommonsporadicformofAD.However,certainallelesoftheapolipoproteinE(ApoE)genehavebeenassociatedwithriskofdisease;theE4allelewithincreasedrisk,andtheE2allelewithdecreasedrisk.

Overthelastdecade,biomarkersderivedfromcerebrospinalfluid(CSF)wereshowntocorrelatewithpathogenicprocessesinADandhavehighpotentialasdiagnosticmarkers.ThecombinationsofelevatedtotalTau(t-Tau),orphosphorylatedTauproteins(p-Tau),andlowβ-amyloid-42(Aβ42)arecurrentlytheonlyCSFbiomarkerswithhighsensitivityandspecificityfordifferentiatingearly-stageADfromotherdementias.Theirstabilityinindividualpatientsovertimealsomakesthempromisingmarkersformonitoringtreatmentresponseinclinicaltrialswithpotentialdisease-modifyingdrugs.OtherresearchsuggeststhatlevelsofP-Tauandisoprostanescombinedwithimaging(MRIorFDG-PET)maybemoresensitiveinassessingdruginterventions.8,9Onthehorizonareadditionalproteinssuchasvisinin-likeprotein1(VLP-1),abraininjurymarker,andtheenzymeBACE1.Inarecentstudy,CSFVLP-1concentrationswereshowntocorrelatewithtauproteinsandwithscoresontheMini-MentalStateExamination,astandardclinicaldiagnostictool.10WhencombinedwithAβ42andtauproteins,VLP-1improveddiagnosticaccuracy.10Similarly,BACE1correlateswithbetaamyloidandtheApoE4allele,11andwhencombinedmaybeusefulasapredictivepanelofdiseasemarkers.

Animportantgoalistodevelopnoninvasiveearlydiagnosticmarkers.Whileconfirmatorytrialsareneeded,CD69valuesinwhitebloodcellsallowedresearcherstodifferentiatebetweenpatientswithAlzheimer’sdiseaseandthosewithParkinson’sdiseasewithgreaterthan90percentaccuracy.12ThemeasurealsodistinguishednormalsubjectsfrompatientswithADwith88percentsensitivity,and82


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percentofthetimewhentheindividualshadnocognitivedeficits.Severaladditionalblood-basedbio-markersforpredictingonsetofdiseaseanddiagnosis,includingAβ42,APP,andBACE,arecurrentlyindevelopment.

Neuroimaging(MRIandPET)technologiesandmarkersalsohavereceivedmuchattentionandresearcheffort.TheabilitytoproduceimagesofamyloidinthebrainsoflivingpeoplerepresentsagreatadvanceindiagnosingAlzheimer’sdisease.Inaddition,imagingcanhelpconfirmthevalueofsurrogatemark-ers13andmayservetoassesstheefficacyofdruginterventions.Whiletherearesomelimitationsduetothehalf-lifeofsomeradiotracers,requiringthemtobemadeon-site,improvedtracersthatcouldbeusedinmorecommunitysettingsarebeingdeveloped.12,14

PARKINSON’S DISEASE

Parkinson’sdisease(PD)isachronicdegenerativedisorderofthecentralnervoussystem.Britishphy-sicianJamesParkinsonfirstdescribeditas“theshakingpalsy”in1817.TheU.S.prevalenceofPDisestimatedatonemillioncases,secondonlytoADamongneurodegenerativediseases.15Theaverageageofonsetis60years,thoughPDcanstrikeadultsatanyage.Thetotalcosttothenationisestimatedtoexceed$25billionannually.TheriskofPDincreaseswithage,soanalystsexpectthefinancialandpublichealthimpactofthisdiseasetoincreaseasthepopulationages.

Parkinson’sdiseaseischaracterizedbyspecificmovementdisorders,includingtremor,rigidity,slowmovement,andposturalinstability.Thesesymptomsusuallybegingraduallyandworsenwithtime.Astheybecomemorepronounced,patientsmayhavedifficultywalking,talking,orcompletingothersimpletasks.AdvancedPDpatientsalsomaysufferfromdementia,adisconcerting,butperhapsinfor-mative,nexusbetweenthesetwodisablingdiseases.

ThespecificcauseofPDremainsunknown.PDoccurswhenneuronsinanareaofthebrainknownasthesubstantianigradieorbecomeimpaired,reducingproductionofdopamine—aneurotransmitterrequiredtoproducesmooth,purposefulmovement.RecentstudieshaveshownthatpeoplewithPDalsohavelossofthenerveendingsthatproducenorepinephrine,whichmayexplainthenonmotorfeaturesofPD,includingfatigueandabnormalitiesofbloodpressureregulation.ManybraincellsofpeoplewithPDcontainLewybodies—unusualdepositsofproteins—butresearchersdonotyetknowwhatroletheyplayindevelopmentofthedisease.SeveralgeneticmutationshavebeenassociatedwithPD,andmanymoregeneshavebeententativelylinkedtothedisorder.AlthoughtheimportanceofgeneticsinPDisincreasinglyrecognized,mostresearchersbelieveenvironmentalexposuresalsoincreaseaperson’sriskofdevelopingthedisease.Certaintoxicchemicals,trauma,andsomevirusesareknownenvironmentaltriggersforPD.Atacellularlevel,mitochondrialdysfunction,oxidativestress,inflammation,andmanyotherprocessesmaycontributetoPD,buttheactualcauseofthedopaminecelldeathformostpatientsisstillundetermined.16Unmetclinicalneedsthusincludethevalidationofbiomarkersandimagingtech-niques,suchas18F-dopaPET,17fortheirabilitytobetterdiscriminatediseasetypes,leadingtoabetterunderstandingofetiology,andultimately,treatment.18


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Inthe1990s,therewasoptimismamongpatientadvocatesandresearchersthatemergingsciencewouldenablePDtobecuredinaslittleasfivetotenyears.In2000,theNIHissuedanambitiousParkinson’sDiseaseResearchAgendathatwouldleveragenewresearchcapabilities,suchashigh-throughputdrugscreening,arraytechnologies,andtissuerepositories,tobetterunderstandPDandtodevelopnewphar-macological,surgical,cellimplantation,gene,andrehabilitationtherapies.19However,thatoptimismhasnotyetturnedintotheneededeffectivenewtherapies.OfthefivenewdrugsapprovedforPDbytheFDAsince2004(rasagiline,rotigotinetransdermal,ropineroleextendedrelease,selegilinedissolvingtablets,andcarbidopa/levodoparapidlydissolvingtablets),onlyrasagilineisanovelcompound—theotherfourarereformulationsofexistingproducts.CurrenttreatmentsforPD,likethoseforAD,aretorelievesymptoms,ratherthanreverseorpreventunderlyingcauses,andtheylosetheireffectivenessovertime.

INITIAL WORKGROUPS

Thisworkscopedocumentdescribestheprocessesthatwillguideactivitytobegininearly2009.Inthisdocument,anumberofworkgroupsareidentifiedtoconductthetasksrelatedtovariousprojects.Theyarelistedbelow,andothersmaybecreatedasnecessary.Finally,ateamwillprovidelogisticalandcom-municationssupportforthecoalition.

Workgroup (WG) 1: Data • CompiledataidentifiedbyWorkgroups2and3 • Establishdatastandardsanddataremapping • Providedatamanagementinfrastructure

Workgroup (WG) 2: Disease-Progression Modeling • Determineclinicaltrialdatarequirements • Createquantitativediseasemodels • Determinedatarequirementsforinclusionofelectronichealthrecords

Workgroup (WG) 3: Biomarker Evaluation • Determinebiomarkerandimagingdatarequirements • Selectbiomarkerstosubsetpatientsinthemodel

Workgroup (WG) 4: Health Authorities Submissions

Support and Communications Team


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WORKFLOW AMONG WORKGROUPS

WG 2 (Disease Progression Modeling) and WG 3 (Biomarker Evaluation) will identify for WG 1 (Data) what data it will need and will assist with compiling these data. WG 1 will request the data from the member companies, NIH, FDA (if feasible and as permitted), etc.; standardize/remap the data; put the data into an infrastructure; and make the data available to WG s 2 and 3 as the data are ready. WG 2 will define the data needed for model building and work with the data as they become available to create

Figure3.Workflowamongworkgroups.


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a disease model (empirical now - mechanistic at first, based on clinical trial data), while WG 3 works with the data to evaluate and identify the most promising biomarkers, including imaging. Candidate biomarkers identified by WG 3 will be referred back to WG 2 for the development of more sophisticated mechanistic disease models. Once biomarkers and disease models have been adequately developed with sufficient evidence, WG 4 will submit them to the FDA for consideration and possible qualification.

STRUCTURE OF WORKGROUPS

Thecurrentstructureoftheworkgroupsisshownabove.Eachofthethreeinitialworkgroupshasadirectliaisonwiththecoordinatingcommittee.Theworkgroupsareledbytwoco-chairs,onefromC-Pathandtheotherfromanindustrymember.Workgroups2and3haveformedseparateAlzheimer’sandParkinson’sdiseaseteamsinordertofocustheknowledgeandexpertiseinthedistinctareas.

Figure4.Structureofworkgroups.


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WORKGROUP 1: DATA

OVERVIEW

TheDataWorkgroupwillfocusonenablingtheeffortsoftheBiomarkerEvaluationandDisease-Pro-gressionModelingworkgroups.Thiswillbeaccomplishedbyworkingwiththesegroupstounderstandtheirneedsandprioritiesforinformationandthenworkingwiththemembercompaniestocompilethisinformationfromthesourcedata.Thissectionaddressesthetechnicalrequirementsofgathering,as-sessing,standardizing,andpoolingdisparatesourcesofclinicalandlaboratorydataintoanintegrateddatabase.Itdescribestheworkneededtodevelopstandardsforremappingandintegratingdatafromavarietyofsourcesandformatsintoacommonformatbasedonopen,consensus-basedstandardswherefeasible(e.g.,CDISCandHealthLevel7[HL7]).Italsoaddressesthearchitecturespecifications:howallpiecesofthecoalition’sinformationtechnology(IT)interacttointegrate,submit,storeandaccessthedataforanalysisineitheracentralizedorfederatedsystem.

OBJECTIVES

TheDataWorkgroupwilladdresstwoprimaryobjectives,possiblyviaseparatecollaborativesubgroups:1)toconvertalldatadomainsandindividualdataelementsrequestedbytheDisease-ProgressionMod-elingandBiomarkerEvaluationworkgroupstoastandardusableformattopopulatetheintegrateddata-base,and2)toprovidetheinfrastructure/architectureoftheentireITsystemforthecoalition.

Insupportoftheseprimaryobjectives,theDataWorkgroupwillmakelinkagestokeypersonnelwithinthemembercompanies,FDA,EMEA,NIH,NIH-fundedefforts,academia,patientgroups,andotherconsortiatocollecttheinformationanddatathatarerelevanttothescopeofCAMD.ThisworkgroupwilldevelopdatausabilitycriteriainconsultationwiththeDisease-ProgressionModelingWorkgroup,andwillusethesecriteriatoassessfitnessofcandidatesourcedataforinclusionintheproject.TheDataWorkgroupwillworkcloselywiththeotherworkgroupstounderstandtheirevolvingdataneedsandtoanticipatefutureneedssodataconversioncanoccurinatimelymanner.TheDataWorkgroupwillneedtoaddressqualitycontrolthroughouttheprocessofdataconversionandwillcoordinate,whenappli-cable,submissionofdatatoFDAforqualification.

Inconsiderationofdevelopingtheinfrastructure,theDataWorkgroupwillevaluateandrecommendpotentialhardwareandtechnologyproductsandvendorsfortheirabilitytomeetthesecurityandfunc-tionalityrequirementsofCAMD.Additionally,inconsultationwiththeDisease-ProgressionModelingWorkgroup,theDataWorkgroupwillassistindecisionsastowhetherornottoacquireanyavailablecommercialoff-the-shelf(COTS)analysistools,ortodevelopcustomanalysistoolsthatwillfittherequirementsoftheproject.

cHApTer II: propoSeD WorkGroUpS For reSeArcH


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SUBGROUP A: DATA SOURCES, STANDARDS AND SHARING

OverviewThissubsectiondescribesthefirstroleoftheDataWorkgroup(WG1):developingtechnicalstandardsforremappingandintegratingdisparatesourcesofclinicaldata.Anoverviewoftheworkflowispresent-edinFigure3,anddeliverablesandresourcesrequiredformeetingtimelinegoalsareoutlinedbelow.

IntroductionWhenconsideringthevariousdataneedsofthecoalition,itisimportanttodistinguishbetweendatarequirementsofthediseasemodels,thestandardsforintegratingthedata,therequirementsfordatastorageinfrastructure,andthetoolsfordataanalysis.Theprimaryobjectiveofthedatateamdescribedinthissectionistocompileandconvertsourcedataintoastandardizedformatforsemanticinteroper-abilityandintegrationinthediseasemodeldatabase.Thisteamwillalsoplayasignificantroleintheinfrastructureconsiderationsaddressedinthenextsection.ThedatarequirementsofthediseasemodelrefertothoseindividualelementsordomainsdeemednecessarybytheDisease-ProgressionModelingandBiomarkerEvaluationworkgroupstodrawmeaningfulscientificconclusions,andshouldthereforebeconsidereddeliverablesofthoseworkgroups.Itwillbeimportanttoestablishbestpracticesstandardsforbothdatamining/modelingandreportingmodels.Thesestandardswilllikelyevolveovertime,buttheyareimportantconsiderationsinsettingtheframeworkforhowtaskswillbeaccomplished.

TheDataWorkgroupwillworkwithnationalstandardsorganizations,suchastheClinicalDataInter-changeStandardsConsortium(CDISC)andHealthLevel7(HL7),toensurethatitseffortsareneitherredundantnorcontradictorytothestandardizationeffortscurrentlybeingdevelopedandimplementedbytheFDAandinthepharmaceuticaland,ifpossible,healthcareindustries.TheworkgroupwillworkwiththeFDAtoensurealldataforCAMDareformattedinamannerthatisaccessiblebytheagency.

Specific AspectsAbroadoverviewoftheworkflowamongtheworkgroupsispresentedinFigure3.TheDisease-Pro-gressionModelingWorkgroup’sprocessforconstructingmodelsisiterative;eachmodelproducedwillbuildonthepreviousmodelsasmoreconclusionsaredrawn,morehypothesesaregenerated,andmoretypesofdataareincluded.AstheDisease-ProgressionModelingandBiomarkerEvaluationworkgroupsidentifynewormorecomplexcandidateprocesses,toolsandbiomarkers,theywillrequesttherepresen-tativedatarequiredformodelingthesefactorsfromtheDataWorkgroup,whichthenwillproducethesedatainausableformat.Consideringthattheusabilityofpreexistingdatawilllimitallfuturemodelingactivities,anessentialearlyandongoingtaskoftheDataWorkgroupwillbetoestablishaprocessforassessingtheusabilityofclinicalstudydataandstudyacceptanceinaprospectivemanner.TheDataWorkgroupalsowillneedtoconsiderthatwhilethefirstsourcesofdatafortheDisease-Pro-gressionModelingWorkgroupwillbelimitedtoclinicaltrialdatafromthemembercompanies,addi-tionalsourcesofdatasuchastheADNI(Alzheimer’sDiseaseNeuroimagingInitiative)willbeusedtoenrichthemodelsastheworkprogresses.


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Asthecomplexityofthemodelsincrease,thescopeofcontributingdatawillalsoincrease.Figure5belowillustrateshowthevarioussourcesofdatabuildontheprevioussourcesasdatafromNIHclinicalstudiesandconsortia(e.g.,ADNI),availablebiomarkersdata,andultimately,personalhealthrecordandelectronichealthrecorddatathatareincorporatedintothemodel.Thislastsourceofdataisalater-phasegoalbutisworthpursuingsincethedataobtainedmayhelpcorroboratetheclinicalobservationsandtheconclusionsdrawnbythemodel,andmayverifytheirrelevancetothegeneralpopulation.Additionally,theelectronicmedicalrecordandpersonalhealthrecorddataalsomayhelptheCAMDeffortserveasavaluablepatientresourceandaclinicaltrialrecruitmenttool.

Theapproachofconvertingonlytherequesteddataforagivenexerciseisthemostefficientsinceitallowstheminimumsetofdataelementsordomainstoundergothesignificanttaskofconversion,reducingtherequiredeffortandresources.Con-versionofentirebodiesofdatafromtheavailablestudiesisanenormoustaskthatislikelyunnecessary;manyofthedatacollectedinthesestudieswillnotberequiredbythemodels.Regardlessofthechosenformat,theworkloadissignificant,sowork-loadaloneshouldnotbeafactorintermsofchoosingthespecificnewstandard.ThefirstmodelinggoalofCAMDwillbetocreatearelativelybasicempiricalmodelfoundedonrelativelyfewerclinicaldomainsandclinicaldataelementsthanarerepresentedinanentireclinicaltrial.TheDisease-ProgressionModelingWorkgroupalsowillrequestbasicdemographicinformationandavarietyofothersupportingdata.Formuchofthisdata,therearelikelytobeexistingCDISCstandards.TheDataWorkgroupwillworkwithitsCDISCexperts,and,whennecessary,CDISCleaderstodeterminehowbesttofitCAMD-requesteddataintoStudyDataTabulationModel(SDTM).

CAMDwillsubmitmodelsandrealdatatotheFDAforassessmentandqualification,andbyusingCDISCandHL7standards,thecoalitioncanensurethattheFDAwillbeabletoreceiveandworkwiththesubmissionsandwiththestandardinteractiveanalyticaltoolsbeingimplemented.Additionally,com-paniescurrentlyconductingstudieswillbenefitfromknowingthattheproactiveconversionofdatawillhelpthemrespondtoanypotentialregulatoryrequeststhatmaycomeyearsafterthestudyissubmit-ted.ConsideringthatCAMDeffortswillcontinueformanyyears,itisinevitablethatthecoalitionwilleventuallyreceivedatafromitsmembersinSDTMformat.Itwouldbeunreasonabletoexpectthatthesefuturedatashouldberetrofittedtosomeotheroutdatedstandardusedbythecoalition.Finally,remap-

Figure 5. Sources of data (Obtaining de-identified data from personal health records and electronic medical records is a future goal of CAMD.)


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pingexistingdatatoCDISCstandardsisbecomingaprescribedprocess.Thechanceoffindingmeta-data-drivenandfullyauditableCOTSanalyticaltools,in-houseexpertise,and/orqualifiedconsultantstoassistintheprocessisthereforeincreased.

WhetherornotnewCDISCdomainstandardsforParkinson’sdiseaseandAlzheimer’sdiseasewillneedtobecreated,orwhethertheexistingstandardscanaccommodatethediseasemodeldatarequirementsremainstobeseenasthecomplexityofthemodelsgrows.Mostlikely,asnewcandidatebiochemicalandimagingbiomarkersemerge,newtherapeutic-areastandardstoaccommodatetheseelementswillneedtobecreated.CAMDwillnotdelaymodelingprogresswhileawaitingfinaldevelopmentofthesenewdomainstandards(assumingnewdomainsarenecessary).Therefore,itwillbenecessarytokeepCDISCabreastofcoalitionactivitiesasitmovesforwardtoavoidcontradictoryorduplicatedeffortsinthefuture.ItisalsoimportanttonotethatthedefinedCDISCprocessfordevelopingnewdisease-spe-cificdomainsinvolvesassemblingsubject-matterexperts,manyofwhomlikelywillhavebeeninvolvedintheCAMDeffort,therebyreducingthechanceofconflictingefforts.

Realisticdetailedestimationsoftimeandresourcerequirementstoachievethegoalsabovearenotfeasi-blewithoutfirstknowingthequantityandcurrentstateofthesourcedatathatwillneedtobeconvertedandintegrated.However,severalgeneralizationscanbemadeandextrapolatedbyapplyingtheexam-plesrelayedtousbyexpertswhohaveembarkedonsimilarefforts.Generallyspeaking,theamountofeffortrequiredinconvertingthedatadependsonanswerstothefollowingquestions: • Howmanyclinicalstudiesneedtoberemapped? • Howmanydifferentsponsorsareinvolved? • Howmanydomainsneedtobeconvertedtothenewstandard? • Howmanystandardvariablesareneeded? • Willnewdomainsneedtobecreated? • Whatdegreeofterminologymappingisrequired? • Howwelldocumentedaretheavailablestudydata? • Howaccessiblearethepeoplewhoarefamiliarwiththedataandthestudyprotocol? • Whatisthecurrentstateanddegreeofstandardizationoflegacydatasetstobetransformed? • Howusefularetheanalysistoolstodetecterrorsinthedata(datevariablescontainingdates, plusotherforeigndatafromshiftedcolumns)?

Thelargesteffortinvolvedintheseundertakingswillbethepreliminarymetadataanalysis.Therefore,thelasttwoitemsabovetouchuponresourcesthataregermanetotheconversionproject.TheFDAandCDISCrecentlyengagedinasimilareffort—TheIntegratedPilotDatabaseProject—whereinitwasat-temptedtointegratedatafrom29clinicalstudiesinvolving8clinicaldomains,8sponsors,andatotalof13compounds.Thiswork,thefirstofitskind,took4FTEs(full-timeequivalentemployees)andnearly6monthstocomplete,andonly8oftheoriginal29studieswereultimatelyintegrated.OtherestimatesfromCDISC“registeredsolutionproviders”indicatethatatypicalconversionof~40sourcedatado-mains,resultingin20to25SDTMdomains,takesapproximately4weeksforawell-documented,morerecentstudy,andupto3monthsforolderstudies.Intheirestimation,thetaskrequires4“roles”(though


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notnecessarily4FTEs),whichtheydefineasjobdeveloper,projectmanager,statistician,andaclini-calleadwhoisfamiliarwiththedata,aswellasanexpertmedicalreviewertoassessthesoundnessoftheintegrateddata.Theworkofthisreviewerwillbefacilitatedbyhavinginteractiveaccesstographicdisplaysof“PatientProfileViews”ofindividualpatientdataandgraphicdisplaysofaggregateddata,includingthe“Napoleon’sMarch”graphicdisplay.

Giventheaboveconsiderations,itisrealistictoexpectthatwithinthefirst5months,theDataWork-groupwillassemble,agreeuponastandard,andinventory/characterizethefirstsetsofsourcedatatomeetthemodelers’needsfortheempiricalmodelbasedonclinicaldataelements.Implementationofanerror-checkingtoolearlyintheprocesswillminimizefindingproblemsattheendoftheanalyticalpro-cess.However,allowingtimeforteamandworkflownormalization,andthepossibilityofencounteringsomepoor-qualitydata,itisreasonabletoallowanother3to6monthsfortheconversionofthefirstsetofrequesteddomainsandtheirintegrationintothedisease-modeldatabase.Inotherwords,withinthefirst8to11months,thecoalitioncanexpecttohavethenecessarydatatocreateitsfirstempiricalmodel,basedonaninitialdatasetresidinginasharedinfrastructure.Itisimportanttonotethatmoreaggressivetimelinescanbeachievedbytakingleanerapproachestodocumentationandvalidation,relyinginsteadonCOTSvalidationtools.ThefeasibilityofthiswillbediscussedwiththeFDA.Inaddition,thedegreeofcommitmentfromparticipantscandrasticallyaffectthetimeline.Foroptimumprogress,asmallteamofpeopleworkingnearlyfulltimeintheinitialstagesisideal.CAMDwillconsultwiththeappropriateexpertstoensurethecoalitioncanmeetitsgoalswithqualityandtimeliness.

Withintwoyearsoflaunch,thecoalitioncanexpecttohavegainedeconomiesofscale.Awell-estab-lishedprocessforcategorizingandremappingsourcedatashouldbeinplace,andtheDataWorkgroupcanbeexpectedtobeproactiveandresponsivetotheneedsoftheDisease-ProgressionModelingWork-grouptodeliverthedataitrequires.Specificoptimizedanalyticaltoolsmayneedtobecreatedtodoadditionalassessments.Also,bythistime(ifnotsooner)amorerobustinfrastructureshouldbeinplacewithsuitabledata-storagesolutions,andGUI(graphicaluserinterface)portalstothedataandanalysistoolsthathavebeenchosenbytheDisease-ProgressionModelingWorkgroupwillbeintegratedintotheinfrastructure.Withinfiveyears,anynewCDISCdomainsthatwerenecessarywillhavebeenlongcompleted,thecoalitionwillhaveprogressedthroughthehierarchyofdatasourcestoincludeEHR(electronichealthrecord)data,anditwillpossiblybeacceptingPHR(personalhealthrecord)data.Thedatabasemaybeservingasaclinicaltrialrecruitmenttoolforinterestedpatientsbythistime.

Deliverables, Considerations, and Resource Requirements I. Datadeliverables A. Surveyofcurrentlyavailabledata,includingalistofmembercompaniesthathavegenerated oraregeneratingstudydata,brokendownby: 1. Numberofstudiesperdisease(ADandPD) 2. Typesofstudiesbydisease(phaseII,III,failedstudies,etc.) 3. Numberofinvestigatorsandnumberofpatientsperinvestigator B. Allfinal,annotatedblankCRFs(casereportforms)fromcandidatestudies C. Allfinalapprovedprotocolsfromcandidatestudies


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D. FinalrawclinicaldatasetsthatmatchtheannotatedCRFs(eventhoughnotalldatawillbe converted) E. Alldiagnosticsandsupplementaldata(labs,ECG,ePRO,etc.) F. Possiblyuseful:analysisdatasetsusedforclinicalstudyreports(CSRs) II. Data-assessmenttasks A. Verifyalldatasetscanbeaccessedandarenotcorrupted B. Developandimplementcriteriaforassessingstudydataofvaluetotheproject 1. Datateamrole:criteriaforqualityofdatawithregardstotechnicalstandards (flagsuspiciousdata;donotattemptcleaningatthisstage) 2. Modelingteamrole:communicatecriteriaforscientificutilityofdata(smallnumber, dropoutrates,trialduration,etc.,thatmayrenderdataundesirable) C. Evaluateandunderstandtheprotocols;metadataanalysis III.Dataconversion A. Personnelrequirements(roles) 1. Ofthecoalition a. Facilitator(s)tocoordinatetheactivitiesamongthevariouscontributinggroups b. Administrativesupportstaff 2. Ofeachcontributinggroup a. Projectmanager-preferablyexperiencedindataconversion b. LeadSDTManalyst c. SDTMprogrammingleader(SASprogrammer—workswithleadanalysttocommu- nicateandresolveinconsistencies) e. Statistician(familiarwitheachstudytobeconverted) f. Clinicallead(familiarwiththestudyobjectives) g. Anysupportstaffrequired,tobedeterminedbyeachgroup B. Specialconsiderations 1. Otherpossiblesourcesofcollaborativedatasharing a. ADNI/LONI (Laboratory of NeuroImaging) b. Other NIA databases c. PD-DOC (Parkinson’s Disease Data and Organizing Center) d. EHRs e. Others (ADCS, REGARDS Study, etc.) 2. Overall workflow considerations a. Each member company converts its own data before submitting to CAMD, or b. A coordinated, shared resource work plan to convert all contributed data will be established.


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SUBGROUP B: DATA INFRASTRUCTURE

The data life cycle needs to accommodate the varied ac-tivities to support transformation of data into information and knowledge, accounting for future data modalities and complex analysis.

The data model and database architecture must accom-modate individual contributing sites and must include workflows that can integrate with the downstream analysis. This section describes the robust infrastructure meeting these criteria. It is important to note that less sophisticated systems can and should be used in earlier stages of the CAMD effort. See Figure 6 to the right for an outline of data infrastructure goals.

The data infrastructure must be designed to support:

• Efficient data infusion: receipt and ETL (extract, transform and load) operations• Quality assurance steps before incorporating the data into the repository• Partitioning and mapping data for integrity and quality benchmarking• Data integration across disparate sources through the use of standards—with extensibility in mind as new standards emerge• A mapping of data provenance and dating, incorporated with tools for data-quality rating and archiving features for old or infrequently used data sets• Risk avoidance via proper backup and recovery proce- dures• Security within the transmission, storage, and manipu- lation of data• Efficient structure for data analyses and reporting• Workflow, visualization, and collaboration tools for consumers of the data• An ability to integrate with other external sources and repositories for greater knowledge aggregation and broader data analysis• Information in multiple standard-compliant formats for data analytics and data-mining activities• Sharing both directly derived and inferred content• Monitoring for availability, performance, and security

Figure6.Datainfrastructuregoals.


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Our proposed basic model for the receipt and infusion of data from disparate sources into a single, cohe-sive data warehouse is shown in Figure 7 below.

This model assumes source data are coming from multiple sources (e.g., pharmaceutical companies “A” through “Z” and others). The pertinent concepts of the data flow of this model are shown in the table on the following page.

Figure7:Proposeddatawarehousemodel.


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Though it is extremely important to capture quality data in a consistent model, of equal importance is the ability for coalition members to access, view, and manipulate that data in a reliable, secure manner once it has been consolidated.


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The basic model for the access and use of the consolidated data set is shown in the diagram below, and described in the following table. Note: The data-access model begins with “Step 9” (from the previous data consolidation flow model), meaning the data-access model assumes that the data have already been transferred, quality-checked, transformed as necessary, and are resident in the CAMD repository. See Figure 8 and the table below for the CAMD data access model and flow description.

Figure8.Proposeddataaccessmodel.


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To accomplish the Data Consolidation and Data Access flow models as described above, the following infrastructure concept is proposed. Figure 9 below is meant to be a conceptual model, not a representa-tion of physical connectivity.

Incomingdatatransfersandrequestsforinformationwillarrive,encryptedattheperimeteroftheC-Pathinfrastructure.Theseservicerequestswillbehandledbyredundant(nosinglepoint-of-failure)infrastructurethroughout.Theperimetersecurity(e.g.,firewalls,intrusiondetection,andproxies)willpassservicerequeststoload-balancedWebservicesthroughalimitedsetofcoalition-agreed-uponports,protocolsandservices.TheWebserversaloneshalltalktoapplicationservices,whichinturnshalltalkalonetodatabaseservices.Theserviceswillbeseparatedbyenclaveboundariesusinga“defense-in-depth”approach,sothatminimalservicesneedtobeopenedbetweenenclaves.

ThisstructurewilllimitCAMD’sriskfor: • Unauthorizeddataaccess • Dataloss • Datatheft • Datatampering • Downtime/outages • Otherproblems

Detailsoftheinfrastructure-specificconfigurationsandsettingswillbedeterminedbyC-PathasCAMDparticipantsformdefinitiveopinionsonanswerstothefollowingquestions:

Figure9.Proposeddataconsolidationmodel.


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Availability • Whatistheallowabledowntime,i.e.,meantimebetweenfailure(MTBF)andmeantimeto repair(MTTR)? • Isredundancyacrossallinfrastructurecomponentswarrantedattheassociatedcost? • Whatisthecontinuityofoperationsplan? - Howoftenmustconfigurationsbebackedup? • Willdailyincrementalbackupsandweeklyfullbackupssuffice? - Howquicklymustrestoreproceduresbeexecuted? - Isoffsitebackupwarranted? - Isadisaster-recoverysitewarranted? • OtherconsiderationsProcessing • Areopen-sourceproducts(e.g.,Linux,Apache,PostgreSQL)acceptabletotheCAMDpartici- pantsinordertominimizecostwhilestillprovidingascalablesolution? • Whataretheresponserequirements? • Howmanysimultaneoususersareenvisioned? • Whattypeofloadisenvisioned?CPUbound?DiskI/Ointensive? • OtherconsiderationsStorage • Whatvolumeofmaterialsisenvisioned? • Whatperformancemetricsareenvisioned? • Underwhatconditions(e.g.,age,quality,infrequencyofuse)woulddatabetakenoffline? • Isdataarchivingnecessary? • Inadditiontodataprovenanceissues,whatadditionalmetadataarerequired? • OtherconsiderationsData Mining • Willthevolumeandusagebesuchthataseparatesetofinfrastructuresfordataminingiswarranted? • Whatquality-validationrulesdoesthecoalitiondesiretoenforce? • Whatisthenatureofthedata,andwhatsortsofreportsandqueriesareofgreatestinterest? • OtherconsiderationsSecurity • Howstringentshouldthecoalitionbewithregardtoauthenticationandauthorization? • Whatspecificports,protocols,andservicesshouldbeallowableattheperimeterandbetween enclaves? • WhatlevelofautomatedmonitoringandcorrectiveactionwouldCAMDliketosee? • Whatforumwillevaluatesecurityviolations,andwhatarethepunitiveactions,ifany,forviolations? • Otherconsiderations

Furtherdetailregardingthedatainfrastructureisleftpendinguntilagreementisreachedregardingthesebasicconcepts,namelytheDataConsolidationFlowModel,theDataAccessFlowModel,andthebasicdesignofthesupportinginfrastructure.Oncethesebasicshavereachedconsensus,thisworkgroupwillholdrequirementsmeeting(s)withCAMDrepresentativestofleshoutfurtherdetailsofthedatainfra-structuredesign.


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WORKGROUP �: DISEASE-PROGRESSION MODELING

OVERVIEW

This section describes the application of mathematical models to characterize disease progression, and how the modeling process is a continuum that depends on the existing knowledge about specific condi-tions, as well as the different data needed to develop such models. In the case of Alzheimer’s and Par-kinson’s diseases, the existing knowledge provides information about clinically observable phenomena, which can be used to create empirical disease-progression models. A particular application for quantita-tive disease, drug, and trial models is to help make more efficient decisions in the drug development pro-cess. The two key strategic goals of this workgroup are to provide a library of trial designs, endpoints, and analysis options for 1) early, exploratory, or phase II clinical trials and 2) late, adequate and well-controlled, or phase III, clinical trials.

Previous models developed by FDA or member companies will act as the basis for further model de-velopment. The work will be conducted considering the differences and similarities of Parkinson’s and Alzheimer’s disease in the context of neurodegeneration, from the clinical to the biological spectrum of both conditions (see Figure 10 below).

Figure 10. AD and PD in the context of neurodegeneration


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Asfurtherknowledgeregardingbiomarkers,mechanisticallydefinedsubpopulations,andimagingpa-rametersbecomeincorporatedintothemodelsandassociatedwithoutcomesthathavebeendefinedasclinicallyrelevant,itwillbepossibletoexaminepotentialrelationshipsandassociations.

Oncetheoverallmodelscontainsufficientdataaboutthecomplexinteractionsamongparametersintheindividualdiseasemodels,asystemsdynamicsapproachcanbeappliedtocreatewholesystembiologymodels.Criteriathencanbeestablishedforconsensusidentificationofcandidateparameters(biomark-ers,imagingmarkers,etc.)thatcanbesubmittedtotheFDAwitharequestthattheybedeemed“quali-fied”forspecificuse(s)indrugdevelopment.Thesubsequentresultsfromtheparameters’applicationindrugdevelopmentcanbeconsideredconfirmationofknowledgethatisthenusedtoenrichthemodelandimprovingitspredictiveaccuracy.OBJECTIVES

Thisworkgroupwillpooldatatocreaterobust(intermsofscopeandpredictiveaccuracy),quantitativedisease-progressionmodelsforuseindrugdevelopmentforAlzheimer’sandParkinson’sdiseases.ThedatausedtocreatesuchmodelsinitiallywillbepooledfromcontrolarmsofclinicaltrialsperformedbyCAMDmembercompaniesandfullclinicaltrialsthatwereconsideredfailuresduetoeitherefficacyorsafetyconcerns,aswellaspubliclyavailablesourcesliketheANDIdatabase.

Additionaldataonrelevantbiomarkers(laboratorytests,imagingparameters,etc.)willbeprogressivelyincorporatedintothemodelsastheyaregeneratedbytherespectiveteamofthecoalition.Otherdatasourcesthatcouldhavefuturevaluerelevanttotheworkgroupincludeelectronichealthrecordsoflesssystematicallyidentified,characterized,andcontrolledpopulationscomparedtoindividualsparticipatinginindustryorNIH-sponsoredclinicaltrials.

Further Objectives • Describemodelingtechniquesandtheircontextofapplication • Describehowandwhenthosemodelingtechniquescouldbeappliedtogeneraterobustquantita- tivedisease-progressionmodelsforuseindrugdevelopmentforAlzheimer’sandParkinson’s diseases • Definetheclinicaltrialendpointsthatwillbeincorporatedintothemodel • Evaluatethelevelofcorrelationamongmultipleendpoints(ADAS-Cogvs.DADvs.NTB,etc.) • Definethelevelofcorrelationamongthesubscaleswithineachscale • Evaluatethelongitudinalpredictabilityofeachscaleanditsapplicabilityindrugdevelopment

Milestones Needed to Achieve the Workgroup’s Objectives • Identifyprospectiveorretrospectivedatasetsthatwillinformthemodeldevelopment • Designapredefinedmodelscope,aswellasadataandknowledgeanalysisplanforall drugresponseanddiseasescalesofinterest • Designapredefinedplanformodeldevelopment,evaluation,calibration,andimplementation


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• Continuouslyincorporatecandidatebiomarkersofdiseasestratification,activity/severity,and progression,bothforParkinson’sandAlzheimer’sdiseases,asidentifiedandqualifiedbythe BiomarkerEvaluationWorkgroup

PROCESS TO DETERMINE/COMPILE DATA NEEDS

Asexplainedbelow,theprocesstodeveloprobustquantitativediseasemodelswillfollowadownwardlyintegrativeapproach,beginningwithempiricalmodelsbasedonclinicallyobservedphenomena(seeFigure11below.)

Theprocesstodeterminewhichvariablesarerelevantforthedevelopmentofrobustmodelswillbebasedontheirstrengthsofassociationtodiseaseprogression,whichincludesthefollowing:

• Medicalhistory,includingageoffirstdiagnosis • Basicdemographicinformation • Standardtherapyanddosetracking • Non-pharmacologicalactions(food,rest,andexercise) • Frequencyoffollow-upvisitsandprocedures • Clinicalscoreevolutionovertime(medicalandself-assessed) • Additionallaboratoryandimagingtestsperformed • Patientdropoutrates

Additionalpathophysiologicdata,suchasbiomarkersofrisk,diseasestratification,activity,progres-sion,andprognosis,willbeincorporatedatfurtherstagesintheevolutionofthemodels.Theprocesstodeterminetherelevanceofsuchdatawillco-evolvewiththedevelopmentofCAMD,astheBiomarkerEvaluationWorkgroupandotherworldwidescientificgroupsgeneratenewinformation.

Figure 11. Disease-progression modeling.


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QUANTITATIVE NEURODEGENERATIVE DISEASE MODELS

Robustneurodegenerativedisease-progressionmodelsofferquantitativeinsightsintodiseasebehaviorandhowitcanbemodified.Thesemodelscanincreaseefficiencyanddecreaseriskoferrorsindrug-developmentdecisionsbyovercomingthecomplexityanduncertaintiesofthedisease-drug-treatmentinteraction.

Manyfactorsthatinfluenceoutcomescanbeconsideredsimultaneouslywiththeuseofsimulations,andtheweightofknowledgeanddatagapsmaybemoresystematicallyrankedandprioritized.Amodel-baseddrug-developmentapproachcanincreaseefficiencybyintegratingallpertinentpriorinformationintoapredictivemodel,whichinturncanbeusedtoguidethedesignofclinicaltrialsanddrugdevelop-mentstrategy.20-23

Asystematicmodel-basedframeworktomaximizeknowledgeanddatainterpretationfrompriorandongoingclinicaltrialinformation,aswellasrelevantpreclinicalandlaboratoryresearch,iscriticallyneeded.24Suchanapproachcanbeusedtocharacterizeandquantifynaturaldiseaseprogression,placeboanddrugeffects,informeddoseselection,aswellastrialexecutionvariables(patientdiscontinuationrates,compliance,selfmedication,specificdesign,etc.)frommultipletrialsusingpatient-leveldata.25,26

Alargespectrumofmodelingmethodsandtechniqueswillbeconsideredandmaybeused,dependingondifferentfactors,suchasthequestionstoberesolved;thestageofdrugresearchanddevelopmentatwhichthesequestionsarise;dataavailability;lengthandtimescalesoftheproblem(moleculartopa-tients,weekstoyears);andmanpowerandtimeconstraints.Thesemethodsincludethefollowing:

• Empiricalmodels,whichoftenmayoriginatefroma“top-down”approach(frompatientpopulation dataintopathophysiologicalphenomena,andasdrivenbydrugdoseandpharmacokinetics.• Semi-empiricalorsemi-mechanistic,withincreasinglyexplicitrepresentationofpathophysiological, cellular,molecular,marker,and/ordrugpharmacokineticsmechanisms.Thesemayincludemath- ematicaltransformstogeneratemeasurableoutputsthatcanberelatedtomeasurableevents.• Mechanisticor“firstprinciple”models,whichoftenarebuiltupona“bottom-up”approach(from molecularpathwaystopathophysiologyandclinicalendpoints,andasdrivenbydrugdoseandpharmacokinetics).• Searchandinferencealgorithms,whichmaybeappliedacrosslengthandtimescalesandareaimed atestablishinglinksamongvariablesofinterest,forwhichmeasurementsareavailable.• Acombinationorintegrationthereoftogeneratesystemsbiologymodelsofhighcomplexity.20,23,25,26

Asanillustration,anempiricalmodelmaydescribetheshapeortrajectoryofdiseasemarkers(bio-chemicaltests,imagingpatterns,clinicalscores,etc.)overtime,andmaytrytorelatechangesinthesemarkerstotreatmentinterventions.Thesemodelsmayhavelittleornorelevancetobiologicalbasisofdiseaseprogression.Thesetrajectoriesandtheirvariationscanbeusefulforsimulatingclinicaltrialsanddetectingpotentialdrugeffects.27,28Atthislevelofobservation,bothlinearandnonlinearapproachescanbeappliedtoprovideanestimateofdiseasestatesthatrelatetoprogression.29ExamplesofAlzheimer’s


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diseasemodelsincludetheworkofHolfordandPeace,21,22aswellasLockwoodetal.30Anothermoredetailedapproachusesmathematicaltransformsthatprovideanoutputwithoutnecessarilyincorporatingexplicitinterconnectionsofunderlyingbiologicalmechanisms.20Thesekindsofmodelsareparticularlyusefulinoscillating,periodic,oraperiodiccontexts,whereinthemostdetailedlevel,suchastherela-tionshipbetweenheartratevariabilityandcardiacevents,30-32cannotbeadequatelydefined.

Amechanisticallyorientedmodelincorporatesarepresentationofkeymolecularsignaling,cellularre-sponses,orpathophysiologicalprocesses(oracombinationofthese)involvedindisease-statemanifes-tationandprogression.Sucharepresentationoftenincorporatesfeedbackandfeed-forwardregulatoryloopsthatmaintainhomeostasisinnonlinear,adaptivesystems,thusprovidingsignificantinsightsintodiseaseprogression.20Suchmodelsmaysimulatealterationsinoneormoreparametersoveradefinedtimeperiodofinterest.Inaddition,thefunctionofmultipleparametersmaybeassessedsimultaneouslytoprovidesignificantinsightsintothedynamicsofthesystem.33-35

Allapproachesrequiredatafromwell-designedandwell-executedstudies,whetherinvitro,invivoorclinical,forthemodeltobeadequatelyinformedanduseful.Model-drivenexperimentaldesign,withatargetedcollectionoftime-series(longitudinal)data,canhelpuncoverunderlyingmechanismsandtheirassociatedkineticswithinbiologicalandpathophysiologicalregulatoryloops.20Amodel-drivenexperi-mentaldesignshouldconsiderimportantaspectssuchasthetimingandpatternofpharmacokineticandpharmacodynamiceffects,response-hysteresisphenomena,e.g.,thetimescaleforthebiologicalsystemtoshiftfromandreturntoabaselinestateafteraneventorintervention,etc.20,29Allthesecomponentsshouldbeintegratedcontinuouslyandprogressivelyintoamodel-basedframework.

Inthecaseofquantitativeneurodegenerativediseasemodels,itisessentialtotakeintoaccountade-tailedclinicalscoreevolution(UnifiedParkinson’sDiseaseRatingScale,orUPDRS,andAlzheimer’sDiseaseAssessmentScale-Cognitivesubscale,orADAS-Cog),patientdropoutrates,genotypeandotherbiomarkers,aswellasenvironmentalhistorydataasextractedfromhumanandpossiblyinvivo/invitrostudies,bothpreviousandongoing.Themodelalsoshouldconsiderallrelevantpharmacokineticandpharmacodynamicpathways(e.g.,CytochromeP450polymorphisms,etc.)thatmayaffecttreatmentresponseandcontainrelevantcovariatessuchasacuteandchronictreatmenteffects.21,36,37

Thequalificationofcandidateefficacyandsafetybiomarkersisafundamentalcomponentofanevolv-ingquantitativedisease-progressionmodel.Sincebiomarkerqualificationiscontext-dependent,andthecontextisprovidedbythedrug-diseasemodelandthedatajustifyingthemodel,biomarkerqualificationanddrug-diseasemodelingareintimatelylinked.Informationabouthowthemodelresponds(ornot)toadruginterventionrepresentsafundamentalopportunitytoenrichanyevolvingquantitativedisease-progressionmodel.

Withoverallfeaturessuchasdifferentdiseasestatesandprogressionsbeingadequatelyrepresented,anintegrateddrug-diseasemodelshouldreproduceclinicallyobservedtrendsortrajectoriescorrectly,byaccuratelymodelingcontrolandsubsequenttreatmentresponsestovariousdrugclasses.20-23,25-29Akeyaspectinthecaseofneurodegenerativediseasesistheneedforthemodeltobeabletocorrectlyrepre-sentdifferingresponseandprogressionratestonoveltherapiesincharacterizedpatientsubpopulations.


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Asbrieflydescribedabove,different—andoftencomplementary—modelingmethodsandtechniquesmaybeusedtocreatequantitativediseasemodels.Inthespecificcaseof Parkinson’sandAlzheimer’sdiseases,giventhelimitedunderstandingofthemolecularandphysiologicalcausalchainsthatleadtothediseasesandtheirprogression,adownwardlyintegrativeapproachmaybepreferredinitially.20Satel-litemodelingefforts(e.g.,modelsborrowingfrominvitroand/orinvivostudiesandscalinguptohu-man,molecularmarkerkineticmodelsinvariousbodycompartments,model-basedscalingfromanimaltopatients,etc.)maybeusedtoindirectlysupportthetop-downapproach.

Theproposedapproachwouldstartbyconsideringclinicallyobservedphenomena,whichareincludedineachdisease’sclinicalscoremetrics(UPDRSandADAS-Cog),followedbyanattempttorepresentthesetoplevelswithkeypathophysiologicalfunctionsthatfeedintoclinicalscoresortheirsubcompo-nents.Inthisdownwardlyintegrativeattempt,theroleofcertainbiomarkersmaybeascertainedmorefully,therebycontributingtoprovidingabasisfortheirpotentialqualification.

Certainly,therewillbesomeknowledgeandevidencegaps,whichwillbenotedandconsideredforfur-theranalysis,e.g.,viahypothesistestingthroughsimulationsofthelargermodelingframework,aswellastargetedexperimentalworkorevaluationviathesatellitemodelsdescribedabove.Insomeinstances,physiologicallyreasonableassumptionscantemporarilyattempttofillsomeofthosegaps.Modelcalibrationandrobustnessneedtobetestedateachstageofdevelopmentandateachscaleofinterestagainstavailableoutputdata.

AlthoughParkinson’sandAlzheimer’sdiseasesare,accordingtothebestunderstandingavailable,twodifferentmedicalconditions,thereareareasofpathophysiologicalsimilarityandclinicaloverlap.38-42Forthisreason,aconstantinteractionbetweentheteamsfocusingoneachdiseaseiscrucialforthesuccessofCAMD.Specificteamscancarryoutworkineachparticularcondition,butwitharegularandperiod-icalefforttowardcommonstandardsandintegrationofadvances.Suchacontinuousprocessofinforma-tion-sharingcanprovideusefulinsightsforscientistsworkingoneachdisease.

SinceFDAscientistshavedevelopedaninitialquantitativediseasemodelforPDwhilemembercompa-nieshaveworkedonotherin-housemodelsforAD,theproposedapproachforthisworkgroupistostartbycross-testingandenrichingtheexistingmodels,withacontinuousfeedbackbasedontheexperiencegatheredateachstage.

Ultimately,theapplicationofquantitativemathematicalmodelingcanprovideusefulandsignificantinsightsintothenatureofneurodegenerativediseasesandtheirpotentialresponsetopharmacologicalinterventions.Thelevelofdetailrequiredbythemodelswillbedictatedbythenatureofthequestionsposedregardingbothdiseasesand,byextension,thelevelofknowledgerequiredinordertosufficientlyaddressthese.


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WORKGROUP 3: BIOMARKER EVALUATION

OVERVIEW

ThefocusoftheBiomarkerEvaluationWorkgroupwillbetoestablishaprocessandexecutetheplanforcompilingandevaluatingthescientificmeritofreportedbiomarkers(includingimagingdata)thatarepotentiallyusefulindrugordiagnostictestdevelopment.Initially,throughcollaborationwiththeDataWorkgroup,dataformatandrequirements,aswellasITsupportforthedatabase,willbeestablished.Aninitiallistofcandidatebiomarkerswillbecompiledfrommembersandotheravailabledatasources,andevidencewillbethoroughlyandsystematicallyreviewed.Gapanalysiswillbeperformed,andprogramswillbeimplementedtoaddressgaps.Whenbiomarkersaredeterminedtobeadequatelysupportedbyevidence,andifdeemedappropriate,theywillmoveintothebiomarkerqualificationprocessdescribedinChapter1.Theultimateobjectiveistoidentifyandqualifybiomarkersthathavepromiseinthedevel-opmentofnewmedicalproductstoimprovethemanagementandoutcomeofthesediseases.

OBJECTIVES

• Establishaprocessforcollatingacomprehensivelistofpotentialbiomarkersusingpubliclyavail- abledataandCAMDmembers’proprietarydata• Establishanevidence-basedprocessincorporatingcurrentmethodstoassessscientificstrengthof candidatebiomarkers• Determinewhichbiomarkersshouldhavepriorityforfurtherdevelopmentefforts,aswellasspecific usecontexts• Determinewhenbiomarkershavesufficientevidencetobesubmittedtothebiomarkerqualification processwithFDAandEMEA(EuropeanMedicinesAgency)• Integratebiomarkerdataintoquantitativedisease-progressionmodels,anduseevolvingdisease modelstohelpwiththeevaluationofbiomarkers

PROCESS

TheBiomarkerEvaluationWorkgroupwillevaluateandprioritizecandidatebiomarkersforfurtherde-velopment,submission,andqualificationbasedonanalysisofestablisheddatabases,incorporationintodisease-progressionmodels,andinternalCAMDmemberunpublisheddataandpublishedreports.TheBiomarkerEvaluationWorkgroupwillincluderepresentativesfromthemembercompanies,memberpatientorganizations,NIH,academiaandotherresearchorganizations,FDA,andC-Path.Themissionofthisworkgroupwillbetoestablishandexecuteasystematicprocessforreviewofcandidatebiomark-ersandtoevaluatethescientificmerit/strengthofevidencesupportingbiomarkersfordiseasedetection,activity,progression,predisposition,predictionofresponsetotreatment,negativeresponsemarkers,andsafetybiomarkers.

Thefirstphaseofthisbiomarkerrevieweffortwillfocusonprocessdefinition,e.g.,definingthedatasourcesforcandidatebiomarkersbycompilingacomprehensivelistofexistentimagingandbiochemi-


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calbiomarkers,definingtheprocessforaddingnewbiomarkerstothelist,determiningcriteriaforevaluation,andestablishingthemethodofratingthedegreeofconfidenceineachbiomarkeraccordingtoestablishedmethodsofreview.43,44DataonexploratorybiomarkerswillbesharedwiththeFDAinmultipleVoluntaryExploratoryDataSubmissions(VXDS)meetings.WorkingtogetherwiththeDataWorkgroup,informationmanagementalsowillbeaddressed,includingdevelopmentofastandardizedformatforthebiomarkerevidencedatabase,aswellastheinfrastructureandmethodforstorageandsharingofbiomarkerinformation.Figure12belowoutlinesthisprocess.

Thesecondphasewillbetheongoingevaluationofevidenceandtheselectionofthemostpromis-ingbiomarkersforregulatoryreview,qualification(whereappropriate),andacceptanceandusebythescientificcommunityforaspecificpurpose.Theworkgroupwillevaluateexternalreportsandmemberorganizationdatathroughliteraturepresentationsandinternaldatapresentations,withtheparticipationofadditionalinvitedexperts.Evidencewillbethoroughlyreviewed,includingrigorousstatisticalanaly-sisofdata.Candidatebiomarkerswillberanked,andevaluationoftop-tierbiomarkerswillcontinue

Figure 12. Biomarker evaluation process and estimated timeline.


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withformulationoftheclaimofspecificpurpose(s)foreachbiomarker,reviewofevidencesupportingclaims,andidentificationofgapsinsupportingevidence.Aclinicalvalidationprogram,foreitherdenovoand/orre-miningofretrospectivedata,willbedesignedtoaddressgaps.Itisdesirabletodevelopclinicalprogramtemplatesthatcanbeusedasatooltoguideclinicalprogramdevelopmentinastan-dardizedapproach,butitisalsoanticipatedthatthespecificprogramforqualificationwillbebiomarkeranddrugdevelopmentclaim-specific.Whenclaimsaredeterminedtobeadequatelysupportedbyevi-dence,thesewillbeconsideredforsubmissiontothebiomarkerqualificationprocessbytheHealthAuthoritiesSubmissionWorkgroup,asdescribedinthesectionbelowonWorkgroup4.

Thisprocessasdescribedisopenanddynamic,withdatasupportingcandidatebiomarkersenteringtheevaluationprocessonanongoingbasis.Asdatabecomeavailabletheworkgroupwillre-evaluatethemandreprioritizebiomarkersbasedoncumulativeevidence.

Note:Thetimelineabove(Figure12)isabestestimateforevaluationandqualificationoftop-tierbio-markersexpectedtobefurtheralongindevelopment.Qualificationofadditionalbiomarkers,withlesssupportingevidenceandthereforerequiringmoreclinicalprograms,isexpectedtohaveanextendedtimeline.

DELIVERABLES

Nine months • Standardizedformatforbiomarkerdatabase• Criteriaandprocessforevaluationofscientificmeritofevidence• Infrastructuretosupportdataandaccess• Comprehensivelistofexistentcandidatebiomarkerswithexistingscientificevidenceminedfrom publicandCAMDmemberdatabases,includingformulatingclaimsofuse• Initialprioritizationofbiomarkers• Processforupdatingdatabase

Nine to fifteen months• Datafromadditionalsourcesoncurrentbiomarkersincorporatedintotheexistingdatabase• Gapanalysisoftop-tier• Definitionandinitiationofclinicalplantoaddressgaps

Fifteen to twenty-four months• SubmissionofbiomarkerstoWorkgroup4forsubmissiontoFDA/EMEAforqualificationforspe- cificusethroughtheBQRTattheFDA


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WORKGROUP 4: HEALTH AUTHORITIES SUBMISSIONS

OVERVIEW

TheHealthAuthoritiesSubmissionsWorkgroup(HASWG)hasasitsmandatetobetheinterfacebe-tweentheotherworkinggroupsandgovernmenthealthauthorities(agencies)forthepurposeofregula-torysubmissions.Thusthisgroupdoesnotdeveloporanalyzebiomarkerdataordiseasemodels,butratherassuresthattheprogressoftheseeffortsisinformedbythecurrentthinkingrelevanttobiomarkerandmodelqualificationsofhealthauthorities.Importantly,whensuchbiomarkerdataordiseasemodelsreachalevelofmaturitythatwarrantsregulatoryreview,theHASWGwillberesponsibleforseeingthatthecollationofsuchinformationisreadyforsubmissiontothehealthauthorities.TheHASWGwillpre-parethesubmissionpackage,followingcurrenthealthauthoritysubmissionpractices,andwillserveastheprimaryinterfaceforcommunicationamongtheCAMDandthehealthauthoritiesduringthereviewprocess.

FDApersonnelwillparticipateinthefunctionalworkgroupsasadvisorsand,insomecases,itwillhavedirectscientificinvolvement.Ontheotherhand,therewillbenoFDAdirectparticipationontheHASWG.Certainly,theHASWGmayhavekeycontactswithinthehealthauthorities,andthesecontactsmayofferadviceregardingdataformatandproceduralissues,buttomaintainobjectivityinthereviewprocess,thesecontactswillnotparticipateinthesubmissionpreparation;inasimilarfashion,reviewersattheFDAmustnothavebeeninvolvedinCAMDactivity.

OBJECTIVES

TheHASWGhasasitsprimaryobjectivethepreparationandsubmissionofdata-setpackagesforre-viewbyhealthauthorities,andthesuccessfulqualificationofthesubmittedbiomarkersand/ordiseasemodelsforuseinregulateddrugdevelopment.

Aseriesofregular“grandrounds”eventsattheFDA,examiningthestateofthefieldandengagingout-sideexperts,maybepursuedpriortoformaldatasubmissiontotheFDAifthegrandroundsserveasavaluableopportunitytocommunicatethinkingandtoengageindiscussionwithalargenumberofFDAregulatoryscientistsandstaffmembers.

Submissionofdisease-progressionmodelsandbiomarkersdevelopedoutofCAMDworkwillfollowthepathdevelopedforbiomarkersubmissionthatthePredictiveSafetyTestingConsortiumpresentedtoboththeFDAandEMEA.45-48Forbothagencies,theprocesswillbeginwithabrieftwo-pagenotifi-cationoftheintenttoseekqualification.TheprocesswillproceedinthemannerplannedbyFDAandEMEAfortheirownfunctions.

Asidefromtherequirementsofthework,adedicatedteamfromthemembersofregulatoryaffairsde-partments,experiencedinbothFDAandEMEAsubmissions,isexpectedtomanagethepreparationofsubmissionmaterials.Theseindividualsshouldserveastheprimarypointsofcontactonthesubmissionforbiomarkerqualification.


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ALLIANCES WITH PATIENT COMMUNITIES

OVERVIEW

TheCriticalPathInstitute(C-Path)strivestopromotecollaborationamongbiopharmaceuticalcom-paniesandincludesfederalagenciessuchasFDAandNIH.ThefirstpriorityfortheC-PathCoalitionAgainstMajorDiseases(CAMD)istodevelopandqualifyforusethemostmoderntoolsandmethodsfordrugdevelopmentforAlzheimer’sandParkinson’sdiseases.Inrecognitionthatthepatientcom-munitiesrepresentavaluableresourceofknowledge,experience,service,advocacy,andsupportforresearch,CAMDincludestheparticipationbyandcontributionsfrompatientgroupsthathavebecomecoalitionmembers.

ThepatientgroupswillactivelyparticipateintheCAMDtechnicalworkgroupstoacceleratethede-velopmentofnewtherapiesforAlzheimer’sandParkinson’sdiseases.ThepatientgroupsconsistofAlzheimer’sandParkinson’sorganizations,aswellasothernot-for-profitorganizationsthatpromotehealth.

OBJECTIVES

ThepatientgroupswillbringtoCAMDtheircollectiveknowledgeoftheentireAlzheimer’sandParkin-son’sdiseasecommunities,includingpatients,researchers,scientists,andcompaniesworkingonthesediseases.Undermostcircumstances,thememberpatientgroupswillrepresentthevoicesofpatients—peoplelivingwithAlzheimer’sandParkinson’sdiseases—andtheircaregivers.Thepatientgroupswillensurethatpatientissuesareattheforefrontofalldiscussionsandconveyasenseofurgency.Ratherthanbeingaseparateworkgroup,theCAMDpatientgroupswillseektobeintegratedwithandcontrib-utetotheCAMDtechnicalworkgroups,whichinturnwillstrivetoimprovethedevelopmentofthera-piesforAlzheimer’sandParkinson’sdiseases.ThepatientgroupsalsowillserveinaleadershiproleincommunicatingbetweenCAMDandthebroaderpatientcommunitywhenappropriateandallowableundertheconfidentialityrestrictionsofthelegalagreement.

Aspartofthisprocess,CAMDwillinvitescientistssupportedbythepatientgroupsandthefederalgovernmenttopresenttheirdatatothetechnicalworkgroupsinthehopesofincreasingthetransparencyofresearch,promotingdialogueamongmultidisciplinaryscientists,andspeedingthetransitionfromdiscoverytotherapeutics.


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ADMINISTRATION AND PROJECT MANAGEMENT

OVERVIEW

TheSupportandCommunicationsTeamisresponsibleforsupportingtheoverallCAMDprojectcoordi-nationandcommunication.

OBJECTIVES

• Establishaprojectmanagementstaffsupportandinfrastructurethatwillmaintainprojectplans foreachworkgroup,aswellastrackandreportprogress • Facilitatecollaborationandinformation-sharingamongmembersofCAMD

SPECIFIC TASKS

1. Provideoverallcoordinationofworkgroupefforts.Tasksinclude: • Developandmaintainworkgroupschedulesandmilestones • Maintaindetailedworkplans,schedulemeetings,anddocumentactionsandthestatusofprojects • StandardizetheuseofMicrosoftProject;usingabaselinefortracking,assigntaskownersfor accountability,templatesforfilters,andaprocessforkeepinginformationuptodate • Standardizeageneralcommunicationandcollaborationtool • Manageexpensesandotherresourcesneededbytheworkgroups • Createtemplatesforimportantdocuments • Maintainadocumentationdatabasewithnecessarysecurityandcheck-outcontrols

2. Establishawebdomainandpassword-protectedsiteformembersofthecoalition.This“intranet” willhaveabasicstructureforcommunicationwithinthecoalition,includingamainpageforan- nouncementsofgeneralinterest,andpageswhereeachworkgroupcanpostdraftdocumentsand sharecomments.MicrosoftSharePointwillbethecollaborationsoftware.

AllmemberswillbegivenanIDandpasswordforaccesstotheCAMDsite.Workgroupleaderswill approveadditionalusers.

3. Establishteleconference,webconference,andvideoconferencecapabilitiesasrequiredtosupport CAMDworkgroupactivities.

4. Toreviewprogress,C-PathandBrookingswillhostformalannualmeetings(perhapsmorefre- quent)oftheCAMDcoordinatingcommittee.TokeepCAMDmembersinformedofprog- ressonanongoingbasis,morefrequentcommunicationswillbeconductedthroughe-mail.

cHApTer III: SUpporT AND coMMUNIcATIoNS TeAM


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ANNOUNCEMENTS AND ONGOING EXTERNAL COMMUNICATIONS

OVERVIEW

TheSupportandCommunicationsTeamisalsoresponsibleforannouncementsandongoingexternalcommunicationsofCAMDbenefitsandprogresstotheindustry,medicalandbusinesscommunities,andthemedia.ExternalcommunicationswillmaximizetheimpactofCAMDannouncements.Thiswillincludesecur-ingmediacoverageandindustry/medicalpublicationofsignificantaccomplishments.CAMDwillbehighlightedasanexampleofeffectivegovernment/privatepartnership.ThisexternalcommunicationisintendedtogeneratesignificantvisibilityforCAMDandtoleadtoenhancedopportunitiestobringad-ditionalsupporttotheproject.

OBJECTIVES

• GatherbroadexposureandpresscoveragefromCAMDlaunchannouncementandfutureprog- ress,developingawarenessintheindustry,patientcommunities,medicalcommunity,academia, andthegeneralpublic • ShowtheuniqueandcomplementaryvalueoftheCAMDeffort • Developapre-andpost-launchCAMDpressplan • Developapre-andpost-launchCAMDcommunicationsplantogovernmentofficials,industry andmedicalpublications,etc.

SPECIFIC TASKS

Specifictasksandresourcesrequiredforeachareoutlinedbelow.

CAMDlauncheventinWashington,D.C.,in2009: • PrepareCAMDlaunchviabroadpressreleaseacrossmediaplatforms

Post-launchcommunicationsplan:

CAMDcommunicationswillinvolveatieredapproachtoinformation,beginningwithamacromessageandbecomingprogressivelymoretechnicalasneeded.ThemacromessagewillallowCAMDtoemergeasamajorhealth-careinitiativethatisvaluedandrespectedbythepublic.Communicationswillbedirectedtowardthefollowingaudiences/constituencies:

• Media - Establishadetailedplanforperiodicpressreleasestoshowmetrics,transparency,and accountabilitythroughouttheCAMDprocess


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- Developcontinuousandupdatedcontentfromscientistsandothermemberstostayactive withmediaandprovidespecificmessagingforsophisticatedortargetedaudiences - Secureprominentplacementandcontinuedcoverageinindustryandmedicalpublications • Members Memberswillbekeptapprisedofnews,successesanddevelopmentsthroughtheCAMD projectmanagementteam.

• PatientCommunity Patientgroupswillbeakeyresourceforcommunicatingimportantfindingstothepatient communitythroughoutthetimelineofthecoalition.

• GeneralPublic ThegeneralpublicwillbeeducatedregardingthemagnitudeoftheAlzheimer’sandParkinson’s problemsandthesuccessesofCAMD.


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APPENDIX A: GLOSSARY OF TERMS AND ACRONYMS

AD: Alzheimer’sDisease

ADaM: AnalysisDataModel(aCDISCstandard)

ADAS-Cog(Alzheimer’sDiseaseAssessmentScale-Cognitivesubscale):Themostcommonlyusedprimaryoutcomeinstrumentinclinicaltrialsfortreatmentsofdementia.Itfocusesonmemoryloss,soitisoftencomplementedbytheapplicationoftheMini-MentalStateExamination(MMSE).

ADNI: Alzheimer’sDiseaseNeuroimagingInitiative(partofLONI)

BQRT: BiomarkerQualificationReviewTeam

CAMD:CoalitionAgainstMajorDiseases(partofC-Path)

CDISC:ClinicalDataInterchangeStandardsConsortium

CFIC:CenterforFDAandIndustryCollaboration

COTS:CommercialOff-the-Shelf(software)

C-Path:CriticalPathInstitute

CPI: CriticalPathInitiative(partoftheFDA)

CRF: CaseReportForm

CSR:ClinicalStudyReport

CSF:CerebrospinalFluid

EHR:ElectronicHealthRecords

EMEA:EuropeanMedicinesAgency

FDA: U.S.FoodandDrugAdministration

FTE:Full-timeequivalent(employee)

AppeNDIceS


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GUI:GraphicalUserInterface

HL-7:HealthLevel7

HHS:U.S.DepartmentofHealthandHumanServices

IT:InformationTechnology

LONI:LaboratoryofNeuroImaging(UCLA)

MMSE:Mini-MentalStateEvaluation.Ascreeningtoolfrequentlyusedbyhealth-careproviderstoassessoverallbrainfunction.ItisoftenusedtoevaluatepatientswithpossibleAlzheimer’sdiseaseoranotherrelateddementia.

NIA:NationalInstituteonAging

NINDS:NationalInstituteforNeurologicalDisordersandStroke

NIH: NationalInstitutesofHealth(partofHealthandHumanServices)

PD:Parkinson’sDisease

PD-DOC: Parkinson’sDiseaseDataandOrganizingCenter

PK:Pharmacokinetics

PRO: Patient-ReportedOutcomesSDTM: StudyDataTabulationModel(ACDISCstandard)

UPDRS(UnifiedParkinson’sDiseaseRatingScale):RatingscoreusedtofollowtheprospectivecourseofParkinson’sdisease,basedonthepatient’sexperiencewiththediseaseandamotorexamination.Itiscomposedofthefollowingsections:mentation,behaviorandmood;experiencesofdailyliving;motorexamination;andcomplicationsoftherapy.


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APPENDIX B: OVERVIEW AND PURPOSE OF CAMD LEGAL AGREEMENT

TheCAMDlegalagreementprovidestheframeworkfortheoperationoftheCoalitionAgainstMajorDiseases.Belowisabriefsummaryofimportantprovisionscontainedinthelegalagreement.

Section 2: Statement of Purpose: Research Plan

2.1:StatementofPurposeToformacoalitionofmembersrepresentinganyofthefollowing: 1. Patientorganizations 2. Pharmaceuticalcompanies 3. Biotechnologycompanies 4. Diagnosticandmedicaldevicecompanies 5. FoodandDrugAdministration 6. NationalInstituteonAgingorotherunitofNIH 7. Othergovernmentalentities 8. Researchinstitutions 9. NonprofitorganizationsToenablesharingofinformationaboutneurodegenerativediseases: Alzheimer’sdisease Parkinson’sdisease

Toexpeditethedevelopmentofsafenewtreatments,curesandpreventionsbycreatingquantitativedis-ease-progressionmodels

Toqualifybiomarkersforuseindrugdevelopmentandtoincorporatetheiruseindrugdevelopmentasclinicaldiagnostictools

Eachsignatoryoftheagreementwillappointonevotingrepresentativetoserveonacoordinatingcom-mitteethatwillgovernandguidetheworkoftheconsortium.Althoughnotexplicitintheagreement,itisexpectedthatthecoordinatingcommitteewillencourageeachmembertoassignscientiststopartici-pateineachworkinggroup(seeSection2.2).Memberswillbeexpectedtocontributedata,expertguid-ance,advocacyforthemission,orotherimportantcontributions.

2.2:ResearchProgramTheoverallresearchprogramoftheCAMDwillbeconductedthroughoneormoreresearchprojects.TheresearchplanandbudgetforeachresearchprojectwillbesubjecttoapprovalbytheCAMD’sCo-ordinatingCommittee,whichwillbeincorporatedintoaprojectagreementthatismutuallyagreedtobyC-Path(onbehalfoftheCAMD),themember(s)participatingintheresearchproject,and,ifapplicable,anyapprovedparticipatingthird-partycontractor(s).


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Eachresearchprojectwillbeoverseenbyaworkinggroup,composedofrepresentativesofeachofthepartiestosuchprojectagreement.2.3:MaterialsTransferInordertofacilitatetheresearchproject,itisexpectedthatbiologicalsamples,reagentsorchemicalsmaybeexchangedbythemembersfromtimetotime—thissectionallowsthememberstosharemateri-alsthroughouttheresearchprojectwithouttheneedforaseparatematerialstransferagreementforeachitemshared.2.4:PolicyregardingcompliancewithantitrustpolicyByreferencetoExhibitA,thisinformsallmembersandatteststhatthememberswillactincompliancewithantitrustlaws.2.5:DisclaimerofpartnershipThisstatestheintentofthememberstointeractasindependentcontractors,andnottocreateanyagency,jointventure,orsimilararrangement.

Section 4. Management4.1:ConsortiumManagement Director–willbeaC-Pathemployee Co-Director–willbeamember’srepresentativeelectedbymembers CoordinatingCommittee–Eachmemberhasonevotingrepresentativeonthecommittee.4.2:CoordinatingCommittee–Thissectiondefinesitsresponsibilities,e.g.: Developresearchplan Overseeresearchgroups Approveresearchprojectsandbudgets WillincludenonvotingFDAorEMEArepresentative(s)

Section 6. Confidentiality

6.1:Confidentiality–Thissectionenablesallmemberstosharetheirintellectualpropertywithoutlossoftheirrights.Thisisanessentialelementtoensurethedevelopmentofnewtherapies.6.2:Exceptions–standardlanguageforconfidentialityagreement6.3:Authorizeddisclosure–standardlanguagetodiscloseinformation6.4:Publications–standardlanguagethatencouragespromptpublicationandrespectsconfidentialityofinformationbeingsharedandhasstandardlanguagetoallowtimeforfilingpatents.6.5:Publicity–Permissionrequiredformentionofpartnersinpublicityregardingresearchortechnicalpublicity,butnotrequiredifonlymentioningtheirname.


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APPENDIX C: CAMD PARTICIPANT ROLES

Voting members of the Coordinating Council:

• Designated representatives of the member patient groups and industry. Responsible to be the conduit and champions for CAMD activities within their organizations. Together, they are the governing group for CAMD work plans and all matters pertaining to the coalition. • Critical Path Institute - Director of CAMD

Nonvoting participants and advisors:

• FDA, EMEA and NIA representatives (technical advisors to the Coordinating Council and workgroups) • Brookings Institution - cosponsor (with C-Path) of CAMD public meetings

Workgroup members:

• Scientists from relevant disciplines within the industry and patient group members to define and, in some cases, execute activity defined by that workgroup’s work scope • Patient group members to provide guidance on the direction and priority of work and assist in public policy messaging • Scientific and advisory personnel from the FDA, EMEA and NIH

Additional CAMD members:

• To be determined by the Coordinating Council and as defined by the CAMD Consortium Legal Agreement

Additional CAMD participants:

• Other organizations or individuals that are brought into workgroups to provide information, services, advice, etc., have a confidential disclosure agreement in place with C-Path, and are approved by the director of CAMD.


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reFereNceS cITeD

1. Source Document on Thinking About Alzheimer’s Disease. Alzheimer’s Study Group. Accessed May 19, 2009 at http://www.alzstudygroup.org/Portals/0/ASG_Source_Document_FINAL.pdf

2. Alzheimer’s Disease Facts and Figures 2007. Alzheimer’s Association, Chicago, IL. Accessed Aug 4, 2008 at http://www.alz.org/national/documents/Report_2007FactsAndFigures.pdf

3. Loveman E, Green C, Kirby J, et al. The clinical and cost-effectiveness of donepezil, rivastigmine, galantamine and memantine for Alzheimer’s disease. Health Technol Assess 2006;10:1–176.

4. Cacabelos R. Pharmacogenomics and therapeutic prospects in dementia. Eur Arch Psychiatry Clin Neurosci. 2008;258(Suppl 1):28–47. 5. Roberson ED, Mucke L. 100 years and counting: prospects for defeating Alzheimer’s disease. Science, 2006;314:781–784.

6. Iqbal K, Chohan MO, Grundke-Iqbal I. Stratification of patients is the way to go to develop neuro protective/disease-modifying drugs for Alzheimer’s disease. J Alzheimers Dis, 2008;15(2):339–45. 7. Fagan AM, et al. Cerebrospinal fluid tau/beta-amyloid(42) ratio as a prediction of cognitive decline in nondemented older adults. Arch Neurol, 2007;64(3):343–9.

8. de Leon MJ, et al. Longitudinal CSF isoprostane and MRI atrophy in the progression to AD. J Neurol, 2007;254(12):1666–75.

9. Thompson PW, Lockhart A. Monitoring the amyloid beta-peptide in vivo - caveat emptor. Drug Discov Today, 2009;14(5-6):241–51.

10. Lee JM, et al. The brain injury biomarker VLP-1 is increased in the cerebrospinal fluid of Alzheimer disease patients. Clin Chem, 2008;54(10):1617–23.

11. Ewers M, et al. Increased CSF-BACE 1 activity is associated with ApoE-epsilon 4 genotype in subjects with mild cognitive impairment and Alzheimer’s disease. Brain, 2008;131(Pt 5):1252–8.

12. Alzheimer’s Association Update, 2008;4(5):373–376.

13. Fagan AM, et al. Inverse relation between in vivo amyloid imaging load and cerebrospinal fluid Abeta42 in humans. Ann Neurol, 2006;59(3):512–9.


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14. Nelleke T, et al. IC-03-01: Imaging Alzheimer pathology in vivo: quantitative comparison of [11C]PIB and [18F]FDDNP. Alzheimer’s and Dementia, 2008;4(4):T307–T307.

15. Ten Frequently Asked Questions about Parkinson’s Disease. Parkinson’s Disease Foundation. 16. Parkinson’s Disease: Hope Through Research. National Institute of Neurological Disorders and Stroke. Accessed Aug 13, 2008 at http://www.ninds.nih.gov/disorders/parkinsons_disease/detail_ parkinsons_disease.htm#toc#toc

17. Gerlach M, et al. Early detection of Parkinson’s disease: unmet needs. Neurodegener Dis, 2008; 5(3-4):137–9.

18. Zhang J, et al. CSF multianalyte profile distinguishes Alzheimer and Parkinson diseases. Am J Clin Pathol, 2008;129(4):526–9.

19. Parkinson’s Disease Research Agenda. National Institute of Neurological Disorders and Stroke. Accessed Aug 13, 2008 at http://www.ninds.nih.gov/about_ninds/plans/nihparkinsons_agenda.htm.

20. Bies RR, Gastonguay MR, Schwartz SL. Mathematics for understanding disease. Clini Pharm Ther, 2008;83(6):904–8.

21. Holford MH, Peace KE. Methodologic aspects of a population pharmacodynamic model for cognitive effects in Alzheimer’s patients treated with tacrine. Proc Natl Acad Sci, 1992;89:11466–11470.

22. Holford NH, Peace KE. Results and validation of a population pharmacodynamic model for cognitive effects in Alzheimer’s patients treated with tacrine. Proc Natl Acad Sci 1992; 89:11471–11475.

23. Miller R, Ewy W, Corrigan BW, et al. How modeling and simulation have enhanced decision making in new drug development. J Pharmacokinet Pharmacodyn, 2005;32:185–197.

24. Challenge and opportunity on the critical path to new medical products. FDA. Accessed Sept. 23, 2008 at http://www.fda.gov/oc/initiatives/criticalpath/whitepaper.html.

25. Wang Y, Bhattaram AV, Jadhav PR, et al. Leveraging prior quantitative knowledge to guide drug development decisions and regulatory science recommendations: impact of FDA pharmacometrics during 2004–2006. J Clin Pharmacol, 2008;48:146–156.

26. Zhang L, Sinha V, Forgue ST, et al. Model-based drug development: the road to quantitative pharmacology. J Pharmacokinet Pharmacodyn, 2006;33:369–393.


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27. Chan PL, Holford NH. Drug treatment effects on disease progression. Annu Rev Pharmacol Toxicol, 01;41:625–659.

28. Mould DR, Denman NG, Duffull S. Using disease progression models as a tool to detect drug effect. Clin Pharmacol Ther, 2007;82:81–86.

29. Holford NH, Kimko HC, Monteleone JP, Peck CC. Simulation of clinical trials. Annu Rev Pharmacol Toxicol, 2000;40:209–34.

30. Lockwood P, Ewy W, Hermann D, Holford NH. Application of clinical trial simulation to compare proof-of-concept study designs for drugs with a slow onset of effect; an example in Alzheimer’s disease. Pharmaceutical Research, 2006;23(9):2050–9.

31. Goldberger A. Fractal mechanisms in the electrophysiology of the heart. IEEE Eng Med Biol 1992;11:47–52.

32. Mager DE, Abernethy, DR. Use of wavelet and fast Fourier transforms in pharmacodynamics. J Pharmacol Exp Ther, 2007;321:423–30.

33. Mager, DE, et al. Kullback-Leibler clustering of continuous wavelet transform measures of heart rate variability. Biomed Sci Instrum, 2004;40:337–42.

34. Bergman R. Orchestration of glucose homeostasis: from a small acorn to the California oak. Diabetes, 2207;56:1–15.

35. Guyton AC. Blood pressure control—special role of the kidneys and body fluids. Science, 1991;252:1813–16.

36. DallaMan C, Rizza R, Cobelli C. Meal simulation model of the glucose-insulin system. IEEE Trans Biomed Eng, 2007;54:1740–49.

37. Holford NHG, Mould DR, Peck CC. Disease Progress Models. In: Atkinson A, editor. Principles of Clinical Pharmacology. San Diego, CA: Academic Press; 2001, 253–62.

38. Mueller SG, Weiner MW, Thal LJ, Petersen RC, Jack CR, Jagust W, Trojanowski JQ, Toga AW, Beckett L. Ways toward an early diagnosis in Alzheimer’s disease: The Alzheimer’s Disease Neuroimaging Initiative (ADNI). Alzheimers Dement, 2005;1(1):55–66.

39. Gregory A, Westaway SK, Holm IE, Kotzbauer PT, et al. Neurodegeneration associated with genetic defects in phospholipase A2. Neurology, 2008 Sep 17. [Epub ahead of print]


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40. Gomperts SN, Rentz DM, Moran E, et al. Imaging amyloid deposition in Lewy body diseases. Neurology, 2008;71(12):903–10.

41. Jellinger KA. A critical evaluation of current staging of alpha-synuclein pathology in Lewy body disorders. Biochim Biophys Acta. 2008 Aug 5. [Epub ahead of print]

42. Koeppe RA, Gilman S, Junck L, Wernette K, Frey KA. Differentiating Alzheimer’s disease from dementia with Lewy bodies and Parkinson’s disease with (+)-[11C] dihydrotetrabenazine positron emission tomography. Alzheimers Dement. 2008;4(1 Suppl 1):S67–76.

43. Altar CA, et al. A prototypical process for creating evidentiary standards for biomarkers and diagnostics. Nature, 2008;83(2):368–371.

44. Teutsch SM, et al. The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Initiative: methods of the EGAPP Working Group. Genet Med. 2009;11(1):3–14.

45. Goodsaid FM, Frueh FW, Mattes W. Strategic paths for biomarker qualification. Toxicology, 2008;245(3):219–223.

46. Goodsaid FM, Frueh FW. Biomarker qualification pilot process at the US Food and Drug Adminis- tration. Aaps J, 2007;9(1):E105–108.

47. Amur S, Frueh FW, Lesko LJ, Huang S-M. Integration and use of biomarkers in drug development, regulation and clinical practice: a US regulatory perspective. Biomarkers in Medicine, 2008;2(3):305–311.

48. Medicines and Emerging Science: Biomarkers. European Medicines Agency. Accessed Oct 6, 2008, at http://www.emea.europa.eu/htms/human/mes/biomarkers.htm.

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