The Importance of Early Interaction with FDA: EOP2A Experiences
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1 The Importance of Early Interaction with FDA: EOP2A Experiences Yaning Wang, Ph.D. Office of Clinical Pharmacology Center of Drug Evaluation and Research Food and Drug Administration
2 Schematic of Development Process and EOP2A Pre-IND EOP2A EOP2 Pre-NDA Labeling IND Submission NDA Submission Action Letter Preclinical Phase 1 Phase 2A Phase 2B Phase 3 EOP2 is too late for FDA to influence the drug development THE HORSES ARE OUT OF THE BARN 2
3 End of Phase 2A Meetings Purpose: Late phase clinical trial (2b, 3) unnecessary failure Format: non-binding scientific interchange. Marketing issues should be in the development plan, not at this meeting. Deliverables: Perform modeling (relevant phase 1/2a data) & simulation of next trial design employing Mechanistic or empirical drug-disease model Literature estimates for comparative drug effects if relevant Placebo effect (magnitude & time-course) Rates for dropout and compliance. (prior FDA experience) Recommendation on sponsors trial design + alternative including patient selection, dosage regimen, Code from FDA work, Sponsor can extend work (EOP2, NDA) Answers to other questions from the clinical and clinical pharmacology development plan Time course: ~ 6 weeks Key sponsor & FDA participants: physician, biostatistician, clinical pharmacology (pharmacometrics), project management 3
4 EOP2A Meeting Process Meeting request letter & questions FDA evaluation & approval Sponsor phone meeting: explain process & data needed FDA receive briefing package, data, next trial design 6-week starts Final Meeting Focus on drug-disease modeling & clinical trial simulations min presentation 1 hour dialogue focused on trial design, dosage regimens, patient selection Simulation Strategy Trial design alternatives Dosage regimens Sample size Patient selection FDA begins data analysis Sponsor questions Answer other questions in writing before meeting 4
5 EOP2A Meeting Metrics Completed 10 Therapeutic area: problem: Epilepsy: dosing Anti-infective: dosing HIV: new mechanism, dosing Prostate Cancer: Formulation/dosing Type 2 Diabetes: Genotype, dosing, trial design Anticonvulsant: New mechanism VMS (hot flashes): New mechanism, dosing Pain: receptor specificity/adr s, dosing Weight-loss: new mechanism, dosing Anticoagulant: dosing Workload: 5-7 person/project (6 weeks) Sponsor evaluation (post-meeting): (1=worthless, 5=pivotal) 5
6 Case Study 6
7 FDA Review Team OND Eddie Gabry David Orloff Biostatistics Todd Sahlroot Meiyu Shen Project management Jena Weber Clinical Pharmacology Division II Jaya Vaidyanathan Dong Yim Hae Young Ahn Hank Malinowski Pharmacogenomics Federico Goodsaid Pharmacometrics Yaning Wang Jenny J Zheng Joga Gobburu Bob Powell 7
8 Drug X Treatment for a chronic disease Polymorphism in metabolic enzyme a/a 20% a/b 50% Extensive metabolizers (EM s) b/b 30% Poor metabolizers (PM s) Biomarker (B) & Surrogate (S) levels Goal: How to manage a genotypic influence on drug clearance in dose selection for Phase III trial design 8
9 Genotype Caused PK Difference a/a a/b b/b EM s PM s 9 Dose Normalized AUC (ng.h/ml/1 mg) auc
10 Genotype Caused PD Difference (Week 12, QD, 20 mg) Surrogate Change from Baseline a/a a/b b/b EM s PM s 10
11 Sponsor s Exploratory Exposure-Response Analysis week drop in HbA1c 12 Week Drop in Surrogate Level AUC AUC(ug*h/L)
12 Limitation of AUC as Exposure: Cannot Differentiate QD vs BID (Week 12 Efficacy) Surrogate Change from Baseline PM 20 mg 40 mg EM 20 mg 40 mg QD BID QD BID 12
13 Modeling Strategy Pharmacokinetics (Sponsor) Phase 1 data for population PK model Phase 2 data for model update Pharmacodynamics (Biomarker and Surrogate) Model established using clinical trial data available to FDA from drugs in this class (more patients and long term) Simultaneous modeling biomarker and surrogate Models updated with Drug X data 13
14 K in %LRPDUNHU % Emax C K out (1 + ) EC + C 50 K in K out 6XUURJDWH 6 1 st order Oral Absorption 6XUURJDWH %LRPDUNHU 'UXJ&RQF db dt ds dt K in K Cmt 1 Cmt 2 Emax C K out (1 ) EC C in B K out 50 S B 7LPH:HHN 14
15 Modeling Results for Biomarker & Surrogate Individual Predicted Biomarker Level Biomarker Observed Level (Drug Y in 900 patients) Week Observed DV B Level Observed Week Individual Predicted Surrogate Level Surrogate Observed Level Week Observed S Level 15
16
17 17
18 Simulation Strategy & Assumptions Population PK model Two-compartment model Clearance dependent on genotype (a/a, a/b and b/b) Exposure-response model Drug-Biomarker-Surrogate model Trial designs Stratification by genotype Titration by biomarker Inclusion criterion Baseline Surrogate>70 and <100 Analysis Response rate at week 26 (Surrogate reduction > 10) 100 clinical trial replicates 18
19 Stratification by Genotype (Genotype 1 st, Parallel Dose, Placebo Control) 100 Patients = 20 a/a, 50 a/b, 30 b/b Dose mg/day EM PM PM EM Genotype 400 patients PBO PBO 0 26 Time (weeks) 19
20 Titration by Biomarker (Parallel Dose, Titration at 12 wk, Placebo Control) Dose mg/day All Titration by Biomarker (Biomarker p <13) (Biomarker non-responder) 40 (Biomarker responder) (Biomarker non-responder) 20(Biomarker responder) 400 patients (Biomarker non-responder) 10 (Biomarker responder) 100 PBO 3X (Biomarker non-responder) PBO (Biomarker responder) Time (weeks) 20
21 Clear Dose-Response Relationship for Various Regimens 100% Genotype Biomarker 84% Response Rate at Week 26 (%) 80% 60% 40% 20% 39% 33% 64% 54% 73% 29% 27% 53% 44% 74% 62% 0% BID_05 BID_10 BID_20 QD_10 QD_20 QD_40 21
22 Higher Response Rate at Week 26 for Stratification by Genotype 100% Genotype Biomarker 84% Response Rate at Week 26 (%) 80% 60% 40% 20% 39% 33% 64% 54% 73% 29% 27% 53% 44% 74% 62% 0% BID_05 BID_10 BID_20 QD_10 QD_20 QD_40 22
23 Smaller Difference in Response Rates at Later Weeks 100% Genotype Biomarker Response Rate (%) 80% 60% 40% 64% 54% 10% 70% 65% 5% 20% 0% Week 26 Week 38 23
24 Better Response Rates at Week 26 for BID than QD 100% Genotype Biomarker 84% Response Rate at Week 26 (%) 80% 60% 40% 20% 39% 33% 64% 54% 73% 29% 27% 53% 44% 74% 62% 0% BID_05 BID_10 BID_20 QD_10 QD_20 QD_40 24
25 Larger Difference in Response Rates for EM Patients 100% BID QD Response Rate at Week 26 (%) 80% 60% 40% 20% 59% 56% 66% 53% 0% PM EM 25
26 Some PM Patients Will Have Exposures beyond Previous Experience Proportion of PM patients receiving high doses not studied Genotype Biomarker BID 60 mg 3% 26% QD 120 mg 3% 32% 26
27 Summary of Case Study At week 26, higher response rates were achieved in stratification by genotype design than titration by biomarker design. But the difference is getting smaller at later weeks. BID regimens perform better than QD regimens, especially in EM population. High-dose safety data in PM is needed. Biomarker-Surrogate relationship can be applied to other drugs with similar mechanism of action. 27
28 Post-Meeting Evaluation Sponsor attendees: 3 Clin Devel, 1 Reg, 2 Proj. Mgmt, 2 Biostats, 1 Clin Pharm How valuable did you find this meeting? (5 pivotal-1 worthless) (mean 4.3 (range 4-5) Pivotal importance. We were at a juncture in development that required detailed discussion and feedback with FDA Clinical The technical discussion about the M&S approach in the development of this drug was of high-quality and, therefore, very valuable. It is good to experience that the FDA supports the use of (new) biometrical techniques in drug development. Biostats Did the meeting change the development plan? (sponsor: 7 yes, 1 no) The modeling offered alternative development scenarios that may impact the final development plan. Regulatory, Clinical Do you believe this meeting will have value in: Decreasing Phase 3 attrition? 8 yes, 1 no Designing Phase 3 trials with success chance? 8 yes Was the time and effort required to prepare for the meeting Adequate? 8 yes Worth the results? 8 yes 28
29 End of Phase 2A Meetings Purpose: Late phase clinical trial (2b, 3) unnecessary failure Format: non-binding scientific interchange. Marketing issues should be in the development plan, not at this meeting. Deliverables: Perform modeling (relevant phase 1/2a data) & simulation of next trial design employing Mechanistic or empirical drug-disease model Literature estimates for comparative drug effects if relevant Placebo effect (magnitude & time-course) Rates for dropout and compliance. (prior FDA experience) Recommendation on sponsors trial design + alternative including patient selection, dosage regimen, Code from FDA work, Sponsor can extend work (EOP2, NDA) Answers to other questions from the clinical and clinical pharmacology development plan Time-course: ~ 6 weeks Key sponsor & FDA participants: physician, biostatistician, clinical pharmacology (pharmacometrics), project management 29
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