Flexible designs for pivotal clinical trials Vlad Dragalin, RSU-SDS-BDS-GSK FDA/Industry Workshop Session: Flexible Designs – Are We Ready Yet? Washington,

Slides:



Advertisements
Similar presentations
Design of Dose Response Clinical Trials
Advertisements

Emerging Issues with Adaptation of Clinical Trial Design in Drug Development* H.M. James Hung Division of Biometrics I, Office of Biostatistics, OPaSS,
Bayesian Trial Designs: Drug Case Study Donald A. Berry Donald A. Berry
Labeling claims for patient- reported outcomes (A regulatory perspective) FDA/Industry Workshop Washington, DC September 16, 2005 Lisa A. Kammerman, Ph.D.
Non-randomized Medical Device Clinical Studies: A Regulatory Perspective Sep. 16, 2005 Lilly Yue, Ph.D.* CDRH, FDA, Rockville MD * No official support.
Matthew M. Riggs, Ph.D. metrum research group LLC
A Practical Approach to Accelerating the Clinical Development Process Jerald S. Schindler, Dr.P.H. Assistant Vice President Global Biostatistics & Clinical.
Gatekeeping Testing Strategies in Clinical Trials Alex Dmitrienko, Ph.D. Eli Lilly and Company FDA/Industry Statistics Workshop September 2004.
1 Bayesian CTS FDA/Industry Workshop September 18, 2003Copyright Pharsight Case Study in the Use of Bayesian Hierarchical Modeling and Simulation.
Interim Analysis in Clinical Trials: A Bayesian Approach in the Regulatory Setting Telba Z. Irony, Ph.D. and Gene Pennello, Ph.D. Division of Biostatistics.
1 Changing Trial Designs on the Fly Janet Wittes Statistics Collaborative ASA/FDA/Industry Workshop September 2003.
1 Superior Safety in Noninferiority Trials David R. Bristol To appear in Biometrical Journal, 2005.
The Application of Propensity Score Analysis to Non-randomized Medical Device Clinical Studies: A Regulatory Perspective Lilly Yue, Ph.D.* CDRH, FDA,
FDA/Industry Workshop September, 19, 2003 Johnson & Johnson Pharmaceutical Research and Development L.L.C. 1 Uses and Abuses of (Adaptive) Randomization:
Confidentiality and trial integrity issues for monitoring adaptive design trials Paul Gallo FDA-Industry Workshop September 28, 2006.
Just How Flexible Can a Prospective Clinical Trial Be? Donald A. Berry Donald A. Berry
0 - 0.
DIVIDING INTEGERS 1. IF THE SIGNS ARE THE SAME THE ANSWER IS POSITIVE 2. IF THE SIGNS ARE DIFFERENT THE ANSWER IS NEGATIVE.
SUBTRACTING INTEGERS 1. CHANGE THE SUBTRACTION SIGN TO ADDITION
MULT. INTEGERS 1. IF THE SIGNS ARE THE SAME THE ANSWER IS POSITIVE 2. IF THE SIGNS ARE DIFFERENT THE ANSWER IS NEGATIVE.
Addition Facts
Assumptions underlying regression analysis
STATISTICAL INFERENCE ABOUT MEANS AND PROPORTIONS WITH TWO POPULATIONS
Mentor: Dr. Kathryn Chaloner Iowa Summer Institute in Biostatistics
Phase II/III Design: Case Study
Regulatory Clinical Trials Clinical Trials. Clinical Trials Definition: research studies to find ways to improve health Definition: research studies to.
Issues of Simultaneous Tests for Non-Inferiority and Superiority Tie-Hua Ng*, Ph. D. U.S. Food and Drug Administration Presented at MCP.
Addition 1’s to 20.
Week 1.
Statistical Inferences Based on Two Samples
Care and support planning Care Act Outline of content  Introduction Introduction  Production of the plan Production of the plan  Planning for.
T. A. LouisTrialNet Workshop March 7, The POPPI 1 Example: Statistical Comments Thomas A. Louis, PhD Department of Biostatistics Johns Hopkins Bloomberg.
A Flexible Two Stage Design in Active Control Non-inferiority Trials Gang Chen, Yong-Cheng Wang, and George Chi † Division of Biometrics I, CDER, FDA Qing.
Data Monitoring Models and Adaptive Designs: Some Regulatory Experiences Sue-Jane Wang, Ph.D. Associate Director for Adaptive Design and Pharmacogenomics,
Statistical Analysis for Two-stage Seamless Design with Different Study Endpoints Shein-Chung Chow, Duke U, Durham, NC, USA Qingshu Lu, U of Science and.
Bayesian posterior predictive probability - what do interim analyses mean for decision making? Oscar Della Pasqua & Gijs Santen Clinical Pharmacology Modelling.
A new group-sequential phase II/III clinical trial design Nigel Stallard and Tim Friede Warwick Medical School, University of Warwick, UK
1 Statistical and Practical Aspects of a Non-Stop Drug Development Strategy Karen L. Kesler and Ronald W. Helms Rho, Inc. Contact:
Elements of a clinical trial research protocol
Impact of Dose Selection Strategies on the Probability of Success in the Phase III Zoran Antonijevic Senior Director Strategic Development, Biostatistics.
Large Phase 1 Studies with Expansion Cohorts: Clinical, Ethical, Regulatory and Patient Perspectives Accelerating Anticancer Agent Development and Validation.
Adaptive Designs for Clinical Trials
Adaptive designs as enabler for personalized medicine
Background to Adaptive Design Nigel Stallard Professor of Medical Statistics Director of Health Sciences Research Institute Warwick Medical School
Aligning Trial Design and Key Processes in Phase III Event Driven Trials: Protocol (via a Special Protocol Assessment), Data Monitoring Committee Charter.
How much can we adapt? An EORTC perspective Saskia Litière EORTC - Biostatistician.
Consumer behavior studies1 CONSUMER BEHAVIOR STUDIES STATISTICAL ISSUES Ralph B. D’Agostino, Sr. Boston University Harvard Clinical Research Institute.
1 Statistical Review Dr. Shan Sun-Mitchell. 2 ENT Primary endpoint: Time to treatment failure by day 50 Placebo BDP Patients randomized Number.
Mass BioTech Council DMC Presentation Statistical Considerations Philip Lavin, Ph.D. October 30, 2007.
1 An Interim Monitoring Approach for a Small Sample Size Incidence Density Problem By: Shane Rosanbalm Co-author: Dennis Wallace.
Traditional vs novel trial designing .
1 Keaven Anderson, Ph.D. Amy Ko, MPH Nancy Liu, Ph.D. Yevgen Tymofyeyev, Ph.D. Merck Research Laboratories June 9, 2010 Information-Based Sample Size Re-estimation.
Investigational Devices and Humanitarian Use Devices June 2007.
Sample Size Determination
Session 6: Other Analysis Issues In this session, we consider various analysis issues that occur in practice: Incomplete Data: –Subjects drop-out, do not.
Adaptive trial designs in HIV vaccine clinical trials Morenike Ukpong Obafemi Awolowo University Ile-Ife, Nigeria.
Sample Size Determination
FDA’s IDE Decisions and Communications
Statistical Approaches to Support Device Innovation- FDA View
Within Trial Decisions: Unblinding and Termination
Watching From Above: The Role of the DSMB
Strategies for Implementing Flexible Clinical Trials Jerald S. Schindler, Dr.P.H. Cytel Pharmaceutical Research Services 2006 FDA/Industry Statistics Workshop.
Data Monitoring Committees: Current Issues and Challenges Some Discussion Points Jim Neaton University of Minnesota.
Aiying Chen, Scott Patterson, Fabrice Bailleux and Ehab Bassily
Data Monitoring committees and adaptive decision-making
DOSE SPACING IN EARLY DOSE RESPONSE CLINICAL TRIAL DESIGNS
Statistical considerations for the Nipah virus treatment study
Hui Quan, Yi Xu, Yixin Chen, Lei Gao and Xun Chen Sanofi June 28, 2019
David Manner JSM Presentation July 29, 2019
Finding a Balance of Synergy and Flexibility in Master Protocols
Presentation transcript:

Flexible designs for pivotal clinical trials Vlad Dragalin, RSU-SDS-BDS-GSK FDA/Industry Workshop Session: Flexible Designs – Are We Ready Yet? Washington, D.C., September 14-16, 2005

2 2 Declaimer The views expressed in this presentation are not necessarily those of PhRMA The views expressed in this presentation are not necessarily those of GlaxoSmithKline The views expressed in this presentation are not necessarily my

3 3 Acknowledgment Judith Quinlan for inviting me to work on this trial GSK Clinical Team for compound SBx for giving me the opportunity to design this trial Compound SBx

4 4 Outline Overview of adaptive designs GSK experience Details of Design Points to Consider

5 5 What are Adaptive Designs? Adaptive Design uses accumulating data to decide on how to modify aspects of the study without undermining the validity and integrity of the trial PROTOCOL AMENDMENTS

6 6 General Structure of Adaptive Designs An adaptive design requires the trial to be conducted in several stages with access to the accumulated data An adaptive design may have one or more rules: Allocation Rule: how subjects will be allocated to available arms Sampling Rule: how many subjects will be sampled at the next stage Stopping Rule: when to stop the trial (for efficacy, for harm, for futility) Decision Rule: the final decision and interim decisions pertaining to design change not covered by the previous three rules At any stage, the data may be analyzed and subsequent stages redesigned taking into account all available data

7 7 Adaptive Design Process Data

8 8 GSK Experience PoC Study in Neuropathic Pain: Three-stage adaptive design: p-values combination test Allocation Rule: drop the loser Stopping Rule for efficacy/futility Sampling Rule: timing of the 2 nd /3 rd stage depends on data

9 9 Background Compound SBx lead indication in Psychiatry (anxiety & depression) secondary indications in Neuropathic pain, RLS & FMS Objectives : To establish superiority of SBx dose(s) versus placebo Confirm efficacy (and durability of response) 8 week treatment, but expect treatment effect at 2 weeks correlation between early and late treatment effects Establish safety profile Establish dose-response Strategic Aim: pivotal quality to potentially support registration

10 Study Designs Last thing we want is to get to the end only to discover no doses are effective OR we missed obtaining a significant result because our original assumptions were too optimistic Standard Dose Ranging Design known entity, but lacks flexibility Adaptive Design Potential savings in terms of both resource and time if there are clear signs that SBx does not work Allows for addition of more patients to a promising dose Protects against underestimate of variance Potential to get to decision quicker, e.g months Full data package on doses of interest Statistical validity maintained

11 Team Concerns Regulatory acceptance as a pivotal quality study statistical rigor is maintained Thought EU feedback may delay study start up concerns proving unfounded: design accepted by EMEA CPMP after one F2F meeting Patients may be enrolled before you can adapt the study performed simulations use electronic data capture GSK inexperience (e.g. protocol development, electronic data capture) may delay study start Unequal information on all doses

12 Details of the Design Primary Endpoint: Primary Goal: Target Difference: STDeviation: Type I error: Power: Traditional Dsgn: Adaptive Dsgn: Efficacy Bndry: Futility Bndry: Inflation Factor: PI-NRS change from Baseline at 8 th W of treatment Comparison of three SBx doses (LD, MD, HD) with Plb 1.3 units 2.1 units = 0.05 (adjustment for multiplicity = 0.05/3 = 0.017) 90% 4 parallel groups - 72 patients/per arm (total 288) 3 stage inverse-normal combination test OBrien-Fleming type nominal levels: (0.0006, 0.014, ) nominal levels: (0.5, 0.5) maximum 75 patients/arm

Month Enrollment Period 1st Stage Data Plb MD LD HD 3rd IA2nd IA1st IA Randomization CRO 0 8w 2w 1st Stage Decisions: Stop arm for futility 49.5% Stop arm for efficacy 2.9% Stop the study for futility Stop arm(s) for safety Determine Randomization Determine timing of 2nd IA (based on 80% Cond. Power) Timing by 80% CP GSKSteeringCommitteeGSKSteeringCommittee

Month Enrollment Period 1st Stage Data Plb MD HD 3rd IA2nd IA1st IA Randomization CRO 0 8w 2w 2nd Stage 2nd Stage Data GSK Steering Committee Decisions: Stop arm for futility 13.1% Stop arm for efficacy 47.6% Stop the study for futility Stop arm(s) for safety Determine Randomization Determine timing of 3rd IA (based on 80% Cond. Power)

Month Enrollment Period 1st Stage Data Plb MD 3rd IA2nd IA1st IA Randomization CRO 0 8w 2w 3rd Stage 2nd Stage Data GSK Steering Committee 3rd Stage Data Final Analysis Overall p-value Estimate of TRT eff. Confidence Interval

16 Interim Analyses: Data For each arm at each stage

17 Interim Analyses: Test Null Hypothesis: Estimate of mean 8 th W endpoint: Standardized Test Statistics: Reduced Variance:

18 Multiplicity Adjustment Due to interim analyses OBrien-Fleming stopping for superiority nominal levels: (0.0006, 0.014, ) Stopping for futility nominal levels: (0.5, 0.5) Due to multiple comparisons Holm procedure at each stage Due to adaptive design Inverse normal p-value combination rule

19 Design Properties Parallel 4 arm Dsgn: 72 per arm

20 Points to Consider Logistics issues pertaining to traditional group- sequential designs also pertain to adaptive designs Establish an IDMC (charter, contracts) for pivotal trials Have adaptation performed by an independent third party with no conflict of interest issues During interim adaptation, unblind only data that are necessary to be unblinded Patient recruitment is not interrupted

21 Points to Consider Adaptation entails careful planning at the protocol design stage Every detail of the statistical design and analysis that can be fixed in advance is described in the study protocol: number of interim analyses information rates stopping guidelines tests Depending on the information rates, the interim analysis is scheduled. The time of the IA is unknown to the investigators. On IA a snapshot of the DB is made (soft close). All available data are used for IA.