Theseeffortsarefocusedon optimizing 43 thetranslationofnovelTBdrugsindevelopmentandinformingthe 44 study design and enrichment of complex combination clinical 45 trials Figure1 Thisholis
Trang 15 Q1Debra Hanna * , Klaus Romero, Marco Schito
6 Critical Path Institute, 1730 E River Road, Tucson, Arizona 85718, USA
7
8 1 Introduction
9 Q2 In2016,tuberculosis(TB)remainstheleadingworldwidecause
10 ofdeathduetoaninfectiousdisease.Itisaconditionthatimpacts
11 one-thirdoftheworld’spopulationandthereareapproximately
12 Q3 1.5millionTB-relateddeathsworldwideeachyear.1 Thereisno
13 questionthatamoreefficaciousandshorterdurationtherapeutic
14 treatmentforTBisneeded,andthatitsdevelopmentshouldbea
15 globalpriority.However,thedevelopmentofsuchatherapyisa
16 tallorder,giventhatthetreatmentofthisdiseaserequiresa
multi-17 drugregimenandthatthereareissuesrelatedtotolerabilityand
18 theemergenceofresistanceforallTBdrugs.Therefore,anentirely
19 novelmulti-drugregimenisrequiredtoovercomethesebarriers
20 andimprovethelivesofpatientssufferingfromthisdisease
21 Thedevelopmentofthisnovelregimen willrequirearobust
22 drug development pipeline, as well as an improved drug
23 developmentprocesstoadvancethenewtherapeuticcandidates
24 Such a process needs tools to inform critical decisions in the
25 complex regimen development pathway Two exciting new
26 therapeuticadvancementsemergedin 2012and 2014withthe
27 accelerated conditional approvals of both bedaquiline2 and
28 delamanid These novel drugs hold the promise of optimized
29 therapies and outcomesfor patientswiththe mostchallenging
30 drug-resistant forms of the disease, but their utility could be
31 jeopardizedby combiningthemwitholder, lesseffectivedrugs
32 The TB community also hasan opportunity to learn from and
33 improvethedesignofcomplexmulti-drugstudiesbyleveraging
34 thedatafromthreephaseIIIquinolonecontainingtrialsthatfailed
35
tomeettheirexpectedendpoints.3–5
36 Since its inception in 2010, the Critical Path to TB Drug
37 Regimens (CPTR)Initiative, a globalpublic–private partnership,
38 haskeenlyfocusedonacceleratingthedevelopmentofanentirely
39 novel,shorterdurationtherapyforTB.6AcoreelementoftheCPTR
40 strategyisthedevelopment,validation,andrefinementofasuite
41
ofpre-clinical,translationalmethodologiesandquantitativedrug
42 developmentplatforms Theseeffortsarefocusedon optimizing
43 thetranslationofnovelTBdrugsindevelopmentandinformingthe
44 study design and enrichment of complex combination clinical
45 trials (Figure1 Thisholistic approach isdesigned tointegrate
46 learningsfromexperiment-levelandpatient-levelcontemporary
47 data, including pre-clinical and clinical studies These data are
48 integrated using the Clinical Trial Data Interchange Standards
49 Consortium (CDISC) Therapeutic Area Data Standard for TB, as
50 describedinFigure2.7Thisfigurealsodescribesothercomponents
International Journal of Infectious Diseases xxx (2016) xxx–xxx
A R T I C L E I N F O
Article history:
Received 7 October 2016
Accepted 11 October 2016
Corresponding Editor: Eskild Petersen,
Aarhus, Denmark
Keywords:
Tuberculosis (TB)
Modeling
Simulation
Pharmacokinetic/pharmacodynamics
(PK/PD)
Drug development
Translational science
S U M M A R Y
Thedevelopmentofnoveltuberculosis(TB)multi-drugregimensthataremoreefficaciousandofshorter duration requires a robust drug development pipeline Advances in quantitative modeling and simulationcanbeusedtomaximizetheutilityofpatient-leveldatafrompriorandcontemporaryclinical trials,thusoptimizingstudydesignforanti-TBregimens.Thisperspectivearticlehighlightstheworkof sevenprojectteamsdevelopingfirst-in-classtranslationalandquantitativemethodologiesthataimto informdrugdevelopmentdecision-making,doseselection,trialdesign,andsafetyassessments,inorder
toachieveshorterandsafertherapiesforpatientsinneed.Thesetoolsoffertheopportunitytoevaluate multiplehypothesesandprovideameanstoidentify,quantify,andunderstandrelevantsourcesof variability, to optimize translation and clinical trial design When incorporated into the broader regulatorysciencesframework,theseeffortshavethepotentialtotransformthedevelopmentparadigm forTBcombinationdevelopment,aswellasotherareasofglobalhealth
ß2016PublishedbyElsevierLtdonbehalfofInternationalSocietyforInfectiousDiseases.Thisisanopen accessarticleundertheCCBY-NC-NDlicense(http://creativecommons.org/licenses/by-nc-nd/4.0/)
* Corresponding author Tel.: +1 520 382 1406.
E-mail address: dhanna@c-path.org (D Hanna).
ContentslistsavailableatScienceDirect
j o urn a l hom e pa ge : ww w e l s e v i e r c om/ l o ca t e / i j i d
http://dx.doi.org/10.1016/j.ijid.2016.10.008
1201-9712/ß 2016 Published by Elsevier Ltd on behalf of International Society for Infectious Diseases This is an open access article under the CC BY-NC-ND license ( http:// creativecommons.org/licenses/by-nc-nd/4.0/ ).
Trang 251 oftheCPTRdatacollaborationprograms,includingthePlatformfor
52 theAggregation of Clinical Trials(TB-PACTS)and TB Relational
53 SequencingDataPlatform(ReSeqTB).8,9Theseintegrateddataare
54 beingusedtodevelopfirst-in-classtranslationalmethodologies,
55 representedbythesevenprojectteamsdescribedbelow
56 2 LearningfromthecollectiveTBdrugdevelopment
57 experiencethroughthemodel-basedmeta-analysisofphaseIII
58 quinoloneclinicaltrials:informingthepathforward
59 CPTR and the World Health Organization (WHO) Global TB
60 ProgrammehaveconvenedleadersofrecentmajorTBclinicaltrials
61 and key subject matter experts This team has reviewed key
62 findings fromthe phase IIItrials of fluoroquinolone-containing
63 shortenedregimens for drug-susceptible TB (OFLOTUB, REMox,
64 Rifaquin)thatwereconductedoverthelastdecade,andintegrated
65 thesefindingsintoTB-PACTS.Theintentistoextractkeylessons
66 fromtheTB-PACTSplatformforfutureTBtrialdesign,including
67 theanalysisofendpointsoftreatmentoutcomefortheselectionof
68 newregimenstobetestedinphaseIIIclinicaltrials,thestatistical
69 methodsfor assessment ofnon-inferiority,the incorporationof
70 pharmacokinetic/pharmacodynamic(PK/PD)parametersinto
pri-71 mary analyses, and the need for improved knowledge of the
72 variability in patient response to treatment The TB-PACTS
73 database will also be used to determine whether there is a
74 predictablelinkagebetweenpathogenloaddynamicsand
clini-75 callyrelevantendpoints inTB clinicaltrials Aframework fora
76 regulatory-oriented disease progression modeling analysis that
77 links pathogen dynamics over time (i.e., biomarker of drug
78 response) with clinicallyrelevant endpoints will be developed
79 Thepathogenloaddynamicsmodelisbeingadvancedtoenablethe
80 additionof a drugbiomarker model andits applicationfor the
81 development ofnewtherapies againstTB Thelinktoclinically
82 relevant endpoints is aimed at optimizing drug development
83 decisions
84
3 Mechanisticsystemspharmacologymodeltolinktarget
85 selectionwithmechanismsofactionandimmuneresponse:
86 improvingdiscovery-to-developmenttranslation
87 GiventhecomplexityofTBdiseaseanddrugtreatmentandthe
88 lack of optimal clinical endpoints, a translational systems
89 pharmacology framework is being developed that integrates
90
insilicomodelsofTBdiseaseprogressionwithimmuneanddrug
91 response This mechanistic model is based on non-clinical and
92 clinicaldata,whichareultimatelyneededtoinformTBtreatment
93 optimizationanddrugdevelopment.Theobjectiveofthisworkis
94
to combine interdisciplinary systems biology and systems
95 pharmacologymodelstoformallycharacterize
drug-host-bacte-96 ria-infectedcellinteractionsduringTBinfection–anessentialstepQ4
Figure 1 CPTR comprehensive approach to optimizing translational understanding of new TB drugs and regimens.
Figure 2 CPTR data collaboration platform.
D Hanna et al / International Journal of Infectious Diseases xxx (2016) xxx–xxx 2
Trang 397 towardsmaximizing the efficacyand shortening thetreatment
98 durationofnovelTBregimens(Figure2 Thedirectoutcomeofthis
99 projectisthedevelopmentofatranslationalTBdrugdevelopment
100 platformthatwillserveasatooltooptimizethestudydesignof
101 keypre-clinicalandclinicaltrials,leadingtoasignificantlyshorter
102 drugdevelopmenttimefornewTBregimens
103 4 Pre-clinicalquantitativeexposure–responsemodelingusing
104 theinvitrohollowfibersystemforTB(HFS-TB)toimprove
105 translation
106 Selectingthedrugand dosetoadvancefromthepre-clinical
107 study into early clinical studies is made more complex when
108 includingmultiplenewagents.TheCPTRpartnershipsuccessfully
109 quantifiedthepredictiveaccuracy oftheHFS-TBforsupporting
110 earlydrugdevelopmentanddosing,andqualifiedthistoolwiththe
111 European Medicines Agency (EMA) througha robust
evidence-112 based methodology.10–14 The partnership between the CPTR
113 expertteamandBaylorUniversityisprogressingworkwiththe
114 HFS-TBsystemtoproactivelyassesstheperformanceofnovelTB
115 drugsanddrugregimens
116 5 PhysiologicallybasedpharmacokineticmodelforTBto
117 understandthedistributionofdrugintheTB-infectedlung
118 The Simcyp physiologically based pharmacokinetic (PBPK)
119 platform,15aleadingtoolusedwidelybyindustryandregulators,
120 isintendedtooptimizethedesignofclinicalstudiesformultiple
121 indications CPTR,in partnershipwithSimcyp,developed a
TB-122 specificsetofmodelsandcompoundfilesintendedtoinformthe
123 designoffirst-in-humanstudiesthatwillsimultaneouslyevaluate
124 theexposureandefficacyofnovelanti-TBcombinationregimens
125 ofuptofourdrugs,includingtheirmetabolites.Thiscollectionof
126 modelscomprisesacomprehensivePBPKmodeloftheTB-infected
127 lung(which includesrelevant aspects of drugdistributioninto
128 granulomatouslesions),acompoundlibraryforstandard-of-care
129 drugs(withmetabolites)aswellasrecentlyapproveddrugs,anda
130 virtualSouthAfricanpopulation,whichcapturesrelevantgenetic
131 variants and TB-related physiological changes that affect drug
132 distributionin this population.14 With theintegration of these
133 componentsintoSimcyp version16 (a recognizedand
best-in-134 classmodelingandsimulationplatform),developmentteamsand
135 regulatorsevaluatingnovelTBregimenswillhavearobusttoolto
136 optimizeclinicaltrialdesignforfirst-in-humanaswellasdrug–
137 druginteractionstudies
138 6 Cardiacriskassessmentprogramtoassessincreasedrisk
139 withTBdrugregimendevelopment
140 Drug-inducedtorsadesdepointes(TdP)hasbeenamajorcause
141 for the withdrawal of drugs approved for marketing.16 The
142 potentialforcardiovascularriskisincreasedwhenmultipledrugs
143 mustbecombinedina complexTB drugregimen.17Inorderto
144 optimize predictions of clinically observed electrophysiological
145 effectsofexistingandnovelTBdrugsbasedonpre-clinicaldataon
146 ionchannelactivity,CPTRhaspartneredwithSimcypscientiststo
147 developamodel-basedrisk-stratificationalgorithmwitha
user-148 friendly interface Thisplatform integrates ion channel activity
149 datawithdrugexposureinformation,topredictthepotentialrisk
150 ofdrug-inducedTdPthatexistingandnovelTBdrugsmaypose
151 This tool is intended to optimize the safety decision-making
152 process for TB drug development An in silico modeling and
153 simulation approach that integrates electrocardiogram changes
154 beyondQTprolongationisnowavailableasanactionabletoolfor
155 optimizingthecardiacsafetyassessmentofTBdrugsanddrugsfor
156 otherindications.18Thisapproachallowsfortheoptimizationof
157 earlyscreeningaswellastestingofclinicalscenarios.Pre-clinical
158 andclinicaldevelopmentteamscanusethisquantitative-basedset
159
ofestimatestoinformthesafetyofsingledruganddrugregimen
160 development
161
7 Liquidcultureandquantitativeassessmentof
time-to-162 positivitytosupportthedevelopmentofadiseaseprogression
163 modelandclinicaltrialsimulationtoolforTB
164 Withthedevelopmentofliquidmedia-basedculturemeasures
165
ofpathogenload,thetime-to-detection(TTD),alsoknownas
time-166 to-positivity(TTP), hasemergedasan importantassessment of
167 patient progress during therapy TTP represents the time to
168 detectablegrowthofMycobacteriumtuberculosisinliquidmedia
169 culture.TTPhasseveraltechnicaladvantagesoverothermethods,
170 suchascolony-formingunit(CFU)quantificationfromculturesin
171 solidmedium,includingreducedvariabilityandeasiertechnical
172 requirements In a first stage, this project has developed a
173 structuralmodelthatidentifiesandquantifiesthemostrelevant
174 sources of variability and interpretable parameters for the
175 longitudinal trajectory of TTP In a secondstage, a model that
176 links the interpretable parameters of TTP progression with
177 clinically relevant endpoints in the REMox study is being
178 developed.Thesemodelswillprovideaquantitativeplatformto
179 informdecision-makingwhendevelopmentteamsarefacedwith
180 choosing toadvance novel regimens fromphase II testing into
181 phaseIIItesting
182
8 Populationpharmacokinetic/pharmacodynamic(PK/PD)
183 modelsforstandard-of-careTBregimens
184 Thisproject hasexploredPK/PD data,withtherapeuticdrug
185 monitoringpracticedina‘real-world’clinicalsetting,inorderto
186 optimizedosingforfirst-linedrugsinpatientswithactivedisease
187
An equivalent population PK/PD understanding for second-line
188 drugsforpatientswithactivediseasewillalsobedeveloped.These
189 models will provide quantitative dosing recommendations for
190 first-andsecond-lineTBregimens
191
9 Conclusions
192 ImprovingthetranslationalperformanceofnewTBdrugswill
193
bea foundational elementtoacceleratethedevelopmentof an
194 entirelynovel,shorter-durationregimenforTB.TheCPTRInitiative
195 and its partners are committed to optimizing the design and
196 execution ofstudiestoevaluatenovel TBregimens,bycreating
197 robust quantitative drug development platforms that are fully
198 validated(Figure3 Theseplatformsarebasedontheintegration
199
oflegacyandcontemporarypre-clinicalandclinicaltrialdata.Each
200
of the quantitative drug development platforms described,
201 including a laboratory manual to support in vitro HFS-TB
202 experimentaldesignandexecution,willbemadepublically and
203 freely available to drug developers and to the TB research
204 community
205 The development of these quantitative drug development
206 platforms,togetherwithuser-friendlyinterfaces,isenvisionedto
207 optimize individualized dosing, the design of studies, and
208 mechanisticmodelsofpathophysiologicalprocesses.Withthese
209 tools,theTB drugdevelopment fieldcan enterthetwenty-first
210 centuryandapplysophisticatedtechnologyandresources
211 Modern drug development and medical practice, especially
212 when it relates to global health issues, demands the optimal
213 evidence for treatments, beyond limited empirical evidence
214 providedbyindividualcontrolledtrials.Evidence-basedanalysis
215 mustgofurtherthanthesimplisticstatisticalinferenceforprimary
216 endpointsofindividualtrialsandrequiresdataaggregationand
D Hanna et al / International Journal of Infectious Diseases xxx (2016) xxx–xxx 3
Trang 4217 correspondinganalysisofmultipletrialswithoutthelimitations
218 imposedbysystematicreviews.Thetoolsdescribedhereofferthe
219 opportunitytoevaluatemultiplehypothesesandincludeamyriad
220 ofdesignstoevaluatesuchhypotheses.Theseplatformsprovidea
221 meanstoidentify,quantify, andunderstand relevantsourcesof
222 variability,andtooptimizetranslationandclinicaltrialdesign
223 Thiseffort,incorporatedintoaregulatorysciencesframework
224 thatallowsarigorousandtransparentregulatoryreviewprocess,
225 has the potential to transform the paradigm not just for TB
226 combinationdrugdevelopment,butalsoforotherareasofglobal
227 health
228 Acknowledgements
229 TheCriticalPathtoTBDrugRegimensprogramissupportedby
230 theBill&MelindaGatesFoundation.TheCPTRprogramwouldlike
231 tothankandacknowledgeallofourcollaborators,includingour
232 partnersatBaylorUniversity,Certera,ColoradoStateUniversity,
233Q5 UniversityofCaliforniaSanFrancisco,andtheUniversityofFlorida
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D Hanna et al / International Journal of Infectious Diseases xxx (2016) xxx–xxx 4