effective clinical trial design
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EFFECTIVE CLINICAL TRIAL DESIGN
Natalia VostokovaChief Operating Officer
IPHARMA LLCNovember 24, 2015
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WORKSHOP SUBJECT• Effective phase 2 and 3 clinical study design• Adaptive design implementation in local
clinical studies
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WORKSHOP AGENDA• Phase 2 and 3 study concepts• What is adaptive design?• Adaptive design advantages and risks• Next-in-class drugs• Examples of successful adaptive design
implementation
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SCIENTIFIC EXPERIMENT
Objective
ResultDesign
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PHASE 2= pilot trial
• Objectives Results• works or doesn’t work• optimum dosing schedule• preliminary efficacy data for planning phase 3
• Design – fast and demonstrative
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PHASE 2Ra
ndom
izatio
n Dose 1
Dose 2
Dose 3
Placebo
Response
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PHASE 3= pivotal trial
• Objectives Results• Hypothesis testing with pre-defined predictable
result
• Design – with minimal risk
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PHASE 3Ra
ndom
izatio
n
Investigational product
«Gold standard»
Response
≥
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STUDY DESIGN DEVELOPMENT PRINCIPLES
• Primary endpoint• Binary (response rate)• Continues (change of parameter)
• Hypothesis• Non-inferiority• Equivalence• Superiority
Study objective
Drug mode of action
Primary endpoint
HypothesisH0 ↔ Hа
Sample sizing calculation
Treatment length and procedures
Data collection
Decision-making
algorithm
Control group expected value
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CLINICAL STUDY DESIGN
Adaptive design
Classic design«Prehistoric design»
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ADAPTIVE DESIGN• Study that allows modifying any design or
hypothesis aspect based on the interim data analysis• in accordance with a pre-defined plan • in preselected timepoints• blinded or unblinded• with or without a hypothesis testing
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WELL-UNDERSTOOD ADAPTIVE DESIGNS• Adaptation of study eligibility criteria based on analyses of
pretreatment (baseline) data • Adaptations to maintain study power based on blinded
interim analyses of aggregate data • Adaptations based on interim results of an outcome unrelated
to efficacy • Adaptations using group sequential methods and unblinded
analyses for early study termination because of either lack of benefit or demonstrated efficacy
• Adaptations in the data analysis plan not dependent on within study, between-group outcome differences
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LESS-UNDERSTOOD ADAPTIVE DESIGNS• Adaptations for dose selection studies*• Adaptive randomization based on relative treatment group
responses • Adaptation of sample size based on interim-effect size
estimates • Adaptation of patient population based on treatment-effect
estimates • Adaptation for endpoint selection based on interim estimate
of treatment effect• Adaptation of multiple-study design features in a single
study* • Adaptations in non-inferiority studies
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ADAPTIVE DESIGN ADVANTAGES• More efficient data collection• Shorter study duration• Less number of patients
• Increasing a probability of success in achieving the study objectives
• Improved understanding of the investigational product’s effects
Optimization of drug development compared to the classic non-adaptive methodology
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ADAPTIVE DESIGN RISKS• Risks of bias• Misinterpretation of the interim analysis• Non-achievement of the study objectives
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ADAPTIVE DESIGN RISKS MITIGATION• Well-planned study• Well-considered statistical validity• α-adjustment for a multiplicity• Minimal clearly planned adaptation• Pre-scheduled modification of the study parameters• Without correction of the statistical methods
• Appropriate use• Data Monitoring Committee (DMC)
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NEXT-IN-CLASS DRUGS• Original patented drugs• Affects the well-known biotargets• Similar to the existing drugs in structure and mode of
action• High predictability of effects in humans• Possible achievement of better results owing to
«improvement» of the original molecule• Less expensive and shorter timelines for development
Low-risk R&D strategy
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MINISTRY OF INDUSTRY AND TRADE PROGRAM
DRAFT Government of the Russian Federation Regulationas of _______ 2015 № _______ Concerning approval of the rules of granting subsidies from the federal budget to Russian organizations on partial reimbursement for implementation of the projects in development of innovative analogues of pharmaceuticals similar in pharmacotherapeutic action
= separate block of the MIT projects oriented on the next-in-class drugs development
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STUDY PLANNING FOR NEXT-IN-CLASS DRUGS • Possible use of data of other drugs of the same
pharmacological class for planning the study (hypothesis, sample calculation, endpoints)
• Comparison with the best-in-class drug• Non-inferiority study• Possible adaptive design
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EFFICACY ASSESSMENT OF DIFFERENT DRUG DOSING
REGIMENS
Mono- and combination therapy
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TYPE 2 DIABETES MELLITUSDPP-4 INHIBITOR
Screening Monotherapy 12 weeks
Combination therapy24 weeks
Follow-up
Gosogliptin Gosogliptin+Metformin Vildagliptin Vildagliptin+Metformin
STAGE 1 STAGE 2
Interim analysis
Final analysis
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PATIENTS ALLOCATION
Stage 2Combination therapy
Stage 1Monotherapy
Randomization299 treatment naïve patients with T2DM
Gosogliptin N=149
Gosogliptin + Metformin
N=122
VildagliptinN=150
Vildagliptin + Metformin
N=114
~ 20% didn't roll-over to Stage 2
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INTERIM AND FINAL ANALYSIS
∆HbA1c, % Gosogliptin Vildagliptin
Monotherapy (W12-W0) -0.93% -1.03%
∆[97.5% CI]
0,104%[-0,133 to 0,342]
upper bound of 97.5% CI < 0.4
Combination (W36-W0) -1.29% -1.35%
∆[97.5% CI]
0,057% [-0,187 to 0,300]
upper bound of 97.5% CI < 0.4
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DOSE FINDING AND EFFICACY ASSESSMENT
Interim analysis using statistics for small sample size
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PREVENTION OF TROMBOSISDIRECT FACTOR Xa INHIBITOR
Screening
Rando
mizatio
n
Knee replace
ment
Hospital treatment
End of treatm
entFollow-up
Day D-14…-1 D0 D1 D4 D7 D12±2 D21 D42
1) Tearxaban twice a day (morning and evening) (first dose in the evening > 10 hours after surgery)
- 50 mg- 100 mg optimal daily dose selection at Stage 1- 150 mg
2) Enoxaparin 40 mg s/c(1st dose in the evening before the surgery)
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PATIENT ALLOCATIONStage 2Efficacy
assessment
Stage 1Dose-finding
Randomization
190 patients with knee replacement
(prevention of VTE)
Tearxaban 50 mgN=21
Tearxaban 100 mgN=21
Tearxaban 100 mgN=21+52=73
Tearxaban 150 mgN=20
Enoxaparin 40 mgN=22
Enoxaparin 40 mgN=22+54=76
Interim analysis Final analysis
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INTERIM ANALYSIS(80 PATIENTS, VTE, SIMON'S MINIMAX)
Tearxaban Enoxaparin
N = 2250 mgN = 21
100 mgN = 21
150 mgN = 20
Cumulative VTE 5 (23.8%) 3 (14.3%) 1 (5.0%) 5 (22.7%)
DVT frequency 5 (23.8%) 3 (14.3%) 1 (5.0%) 4 ( 18.2%)
Symptomatic VTE frequency (DVT, PE) 0 (0.0%) 0 (0.0%) 0 (0.0%) 2 (9.1%)
Non-fatal PE frequency 0 (0.0%) 0 (0.0%) 0 (0.0%) 1 (4.5%)
Cumulative hemorrhagic complications frequency 3 (14.3%) 1 (4.8%) 4 (19.0%) 1 (4.5%)
Major and clinical significant non-major bleeding frequency 2 (9.5%) 0 (0.0%) 1 (4.8%) 1 (4.5%)
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FINAL ANALYSIS(150 PATIENTS, VTE, NON-INFERIORITY)
TeaRX 100 mgN = 73
EnoxaparinN = 76
Cumulative VTE 14 (19.2%) 21 (27.6%)
∆[97.5% CI]
8.45%[-3.01%; 19.59%]
Lower bound of97.5% CI > -5.00%
DVT frequency 14 (19.2%) 20 (26.3%)
Symptomatic VTE frequency (DVT, PE) 0 (0.0%) 2 (2.6%)
Non-fatal PE frequency 0 (0.0%) 1 (1.3%)
Cumulative hemorrhagic complications frequency 1 (1.4%) 2 (2.6%)
Major and clinical significant non-major bleeding frequency 0 (0.0%) 2 (2.6%)
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DOSE FINDING AND EFFICACY ASSESSMENT
Interim analysis with a surrogate endpoint
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HIV, NNRTISCREENING Investigational therapy administration Follow-up
VM-1500 20 mg + ART
VM-1500 40 mg + ART
Efavirenz 600 mg + ART
V1 B2 V6 V8 V10 B11
W-2 W0 W12 W24 W48 W52↑ ↑ ↑ ↑Randomization Surrogate endpoint
(interim analysis)Primary endpoint (final analysis)
End of treatment
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PATIENTS ALLOCATIONStage 2Efficacy
assessment
Stage 1Dose-finding
Randomization
150 treatment naïve patients
with HIV
VM-1500 20 mgN=30
VM-1500 40 mgN=30
VM-1500 40 mgN=30+30=60
Efavirenz 600 mgN=30
Efavirenz 600 мгN=30+30=60
Interim analysis Final analysis
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INTERIM ANALYSIS(90 PATIENTS, HIV RNA< 400 COPIES/ML ON WEEK 12, NON-INFERIORITY)
Patients with HIV RNA < 400 copies/ml
Week VM-1500 20 mgN=30
VM-1500 40 mgN=29
EFV 600 mgN=27
W12 28 (93.3%) 25 (86.2%) 22 (81.5%)
∆[97.5% CI]
11.85% [-2.59%; 26.92%]
4.73% [-11.50%; 20.83%]
Lower bound97.5% CI > -15.00%
* Final analysis at Q1 2016
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CONCLUSION• Implementation of adaptive design provides
an opportunity to improve timeline and resources when developing next-in-class innovative drugs
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THANK YOU FOR YOUR ATTENTIONNatalia VostokovaChief Operating Officer7 Nobel street«Skolkovo» Innovation CenterMoscow, 143026, RussiaMobile: +7 (926) 098-3633Phone: +7 (495) 276-1143Fax: +7 (495) 276-1147E-mail: [email protected]: www.ipharma.ru