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

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%)

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: nv@ipharma.ruWeb-site: www.ipharma.ru