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Mon, Sep 19

SC1 Statistical Issues in Drug Development

8:30 AM - 12:00 PM
Thurgood Marshall North/East

Instructor(s): Stephen Senn, University of Glasgow

There is no aspect of drug development in which statistics cannot intrude: from screening chemicals for activity to forecasting sales. Because the efficacy and safety of treatments has to be judged against a background of considerable biological variability, all of the judgments of efficacy boil down in the end to a numerical summary of evidence whose message can only be understood with the help of the science of statistics. The objective of this course is to encourage thinking about genuine statistical controversies affecting clinical trials. Despite the title, the focus is not solely on issues pertaining to drug development.


SC2 Group Sequential and Adaptive Clinical Trial Design

8:30 AM - 12:00 PM
Thurgood Marshall South/West

Instructor(s): Scott Emerson, University of Washington

Increasingly, clinical trials are conducted using group sequential methods or, more recently, adaptive designs in order to address the ethical and efficiency issues that arise when performing experiments with human volunteers. The design, conduct, and analysis of a sequential clinical trial is necessarily more involved than that for a clinical trial in which the data would only be analyzed at the end of the study. In this short course I present the additional issues that must be considered when conducting a sequential trial with or without response adaptive modifications. I quantify the ways in which adaptive modification might complement the benefits provided by standard group sequential methods and the extent to which such adaptive modification of a trial design can lead to improved design. The evaluation of sequential and adaptive designs are illustrated using RCTdesign, an R module for the design, monitoring, and analysis of clinical trials.


SC3 Study Design for Biomarker Development and Validation

8:30 AM - 12:00 PM
Wilson ABC

Instructor(s): Sumithra Mandrekar, Mayo Clinic; Gene Pennello, FDA; Juergen von Frese, Data Analysis Solutions DA-SOL GmbH

Any biomarker or molecular signature can only be as good as the data it was derived from. Therefore, study design critically determines biomarker performance, reliability and ultimate regulatory acceptance. This course will outline the whole process from general principles and practical aspects in the developmental phase to the incorporation of biomarker validation into clinical trials as well as regulatory considerations and requirements. It will demonstrate pitfalls with real examples and discuss the importance and appropriate handling of confounding factors. The merits and limitations of various designs (e.g. unselected, enriched or adapted) for the validation of predictive markers within clinical trials will be considered using examples from ongoing or completed oncology trials. Regulatory considerations to be addressed will include scenarios in which the drug and the companion diagnostic are not developed in parallel, analytical and clinical validation of the diagnostic, handling of missing test results, prospectively planned retrospective analysis, and bridging from one companion diagnostic to another for the same intended use.


SC4 Monte Carlo Simulation for the Pharmaceutical Industry: Concepts, Algorithms, and Case Studies

1:30 PM - 5:00 PM
Wilson ABC

Instructor(s): Mark Chang, AMAG Pharmaceuticals; Sandeep M Menon, Pfizer Inc./ Boston university

There is an acute need for the pharmaceutical industry to seek innovative and cost-effective approaches in the overall drug development due to the rising costs. Monte Carlo (MC) Simulations have started playing a critical role during this evolutionary process. MC is the technique of simulating a dynamic system or process using a computer program. This short course will provide an overview of MC simulations with simple examples, including clinical trial simulation (CTS), prescription drug commercialization, molecular design & simulation, disease modeling & biological pathway, and PK/ PD simulations. The topics will include (1) model building - to translate a clinical trial problem into a CTS problem, (2) execution - to implement the simulation, and (3) interpretation - to interpret and utilize the simulation results. Examples of Classic and adaptive trial simulations and a simulation study to optimize adaptive design criteria will be discussed. Attendees will learn the overall landscape of MC and basic simulations techniques necessary to carryout simulation effectively.


SC5 Key Multiplicity Problems in Clinical Trials

1:30 PM - 5:00 PM
Thurgood Marshall North/East

Instructor(s): Alex Dmitrienko, Eli Lilly and Company

The short course will give a review of key multiplicity issues arising in clinical trials with multiple endpoints, dose-control comparisons and patient populations, etc. It will present traditional multiplicity adjustment methods as well as recent advances in this area, including methods for "multidimensional" multiplicity problems known as gatekeeping procedures. Gatekeeping procedures have been widely used in clinical trials with multiple objectives due to the fact that they control the overall Type I error rate and enable trial sponsors to enrich product labels by including information on relevant secondary objectives. The short course will offer a well-balanced mix of theory and applications with case studies based on real clinical trials and discuss regulatory considerations, including the FDA guidance on multiple endpoints (expected to be released in 2011). It will also discuss software implementation of commonly used multiplicity adjustment methods using SAS and R software.


SC6 Bayesian Adaptive Methods for Clinical Trials

1:30 PM - 5:00 PM
Thurgood Marshall South/West

Instructor(s): Scott Berry, Berry Consultants; Bradley P Carlin, University of Minnesota

In submissions to the U.S. FDA Center for Devices and Radiological Health, Bayesian methods have been in common use for over a decade and in fact were the subject of a recently-released FDA guidance document. Statisticians in earlier phases (especially Phase I oncology trials) have long appreciated Bayes' ability to get good answers quickly. Moreover, an increasing desire for adaptability in clinical trials has also led to heightened interest in Bayesian methods. This half-day course, taught jointly with Dr. Scott Berry, introduces Bayesian methods, computing, and software, and elucidates their use in Phase I, II, and III trials. We include descriptions of how the methods can be implemented in various stand-alone packages, as well as our own code written in R, WinBUGS, and BRugs. In particular, we will illustrate how a Bayesian procedure may be calibrated to guarantee good long-run frequentist performance (i.e., low Type I and II error rates), a subject of keen interest to the FDA.


Tue, Sep 20

PS1a Key Multiplicity Issues in Clinical Drug Development

8:40 AM - 10:15 AM
Thurgood Marshall North

Organizer(s): Paul Gallo, Novartis Pharmaceuticals; Ghideon Ghebregiorgis, FDA; George Kordzakhia, FDA; Brian Wiens, Alcon Laboratories, Inc

Chair(s): Brian Wiens, Alcon Laboratories, Inc

This session will discuss key multiplicity topics in drug development, including analysis of multiple endpoints, composite endpoints, subgroup analyses, gatekeeping strategies, etc. Key multiplicity issues will be presented by experts from the FDA, academia and industry. The session will be aimed at a broad audience of statisticians involved in the design and analysis of clinical trials, including statisticians working in the industry and regulatory agencies.

A regulatory perspective on multiplicity issues in clinical trials
View Presentation View Presentation Mohammad F Huque, FDA

Multiple endpoints and multiple testing: An academic’s view of issues and solutions
Ralph B. D'Agostino, Boston University

Analysis of clinical trials with multiple objectives
View Presentation View Presentation Alex Dmitrienko, Eli Lilly and Company


PS1b Personalized Medicine: Separating the Hope from the Hype

8:40 AM - 10:15 AM
Thurgood Marshall South

Organizer(s): Shanti V Gomatam, FDA/CDRH/DBS; Michael Man, Eli Lilly and Company; Sandeep M Menon, Pfizer Inc./ Boston university

Chair(s): Gregory Campbell, Food and Drug Administration

The sequencing of the human genome brought with it the hope that the greater understanding of genetic components of disease would allow for more specific targeting of therapies. The hope is that it will allow sponsors to run "cleaner" clinical trials with less variability and a consequent saving in patient numbers. The speaker and panelists in this session will discuss statistical and other issues relating to trial design and analysis from the perspective of academia, industry and the FDA.

Personalized Medicine: Separating the Hope from the Hype
View Presentation View Presentation Stephen Senn, University of Glasgow

View Presentation View Presentation Gene Pennello, FDA; Somnath Sarkar, Genentech Inc.; Rajeshwari Sridhara, FDA; Juergen von Frese, Data Analysis Solutions DA-SOL GmbH


PS1c Current Issues in the Design and Analysis of Non-Inferiority Trials

8:40 AM - 10:15 AM
Thurgood Marshall East

Organizer(s): Yoko Adachi, FDA; Norm Bohidar, Johnson & Johnson; Greg Soon, FDA; Qing Xu, FDA

Chair(s): Qi Jiang, Amgen; Qing Xu, FDA

Despite the release in 2010 of an FDA draft guidance on non-inferiority trials, controversies still exist. Perhaps the most difficult issue in designing non-inferiority trials has been specification of the non-inferiority (NI) margin, particularly when there’s insufficient historical placebo-controlled information. The subjectivity of the currently used approaches for margin specification is also a source of the controversies. This session is to provide a platform for further dialogue on some special topics such as considerations in evaluating the effect of the active control therapy in a non-inferiority trail, and outcome-based biases involving non-inferiority trials, as well as the inferiority index and covariate adjustment approaches for NI margin specification.

Remaining Challenges in Assessing Non-Inferiority
Steven Snapinn, Amgen

Outcome-based Biases and Other Issues Involving Non-inferiority Trials
View Presentation View Presentation Mark D Rothmann, U. S. Food and Drug Administration

Inferiority Index and Non-inferiority Margin Specification
View Presentation View Presentation Gang Li, Johnson & Johnson

Current Issues in the Design and Analysis of Non-Inferiority Trials
View Presentation View Presentation Lei Nie, FDA


PS1d Early Phase Study Designs in Oncology

8:40 AM - 10:15 AM
Thurgood Marshall West

Organizer(s): Jonathan Denne, Eli Lilly & Co.; Chris Holland, MacroGenics, Inc.; Shenghui Tang, FDA; Qing Xu, FDA

Chair(s): Jonathan Denne, Eli Lilly & Co.

As a result of a large unmet medical need and growing range of new therapeutic targets, oncology drug development has seen a remarkable growth in the number of new chemical entities and an abundance of new clinical trial activity. This incredible growth combined with limited patient participation in clinical trials and limited financial resources are motivating the development of better and more efficient early phase designs. The objective of this session is to provide an overview of novel designs for Phase 1 and Phase 2 trials in oncology, highlighting the opportunities they bring for improving the likelihood of successful drug development. We will present two case studies of their application, discuss innovative designs from an expert consultant, and provide thoughts from a regulatory perspective all with a particular focus on how to address and overcome clinical concerns

Bayesian Early Phase Trials
View Presentation View Presentation Scott Berry, Berry Consultants

Oncology Phase I dose escalation design guided by Bayesian model based approach
View Presentation View Presentation Suman Kumar Sen, Novartis Pharmaceuticals Corporation

Efficient Concurrent Controls for Phase II Studies: Case Studies
View Presentation View Presentation Nathan H Enas, Eli Lilly and Company

Regulatory Aspects of Phase I Designs in Oncology Trials
Somesh Chattopadhyay, FDA


PS1e Statistical Issues in Medical Device Trials

8:40 AM - 10:15 AM
Balcony C/D

Organizer(s): Chul Ahn, FDA; Peter Lam, Boston Scientific; Nelson Lu, FDA; Zhen Zhang, Abbott Vascular

Chair(s): Chul Ahn, FDA

This session deals with statistical problems unique to medical device clinical trials. It includes single-arm trial, Bayesian strategy, non-inferiority, sham control, patient blinding, and survival model projections and validation among others.

A Case Study of a Medical Device Trial Using a Bayesian Hierarchical Model with a ‘Conditional Borrowing’ Strategy
View Presentation View Presentation Scott Wehrenberg, Boston Scientific

A Free Gift: An Adaptive Strategy in a Single Arm Trial Using an Exact Test Through the Binomial Distribution
View Presentation View Presentation Jin Wang, Abbott Vascular

A Predictive Model for Cancer and Non- Cancer Mortality in Beagle Dog Study
View Presentation View Presentation Changsheng Lao, FDA\CDRH


PS2a Decision Making and Safety in Clinical Trials - Graphs Make a Difference

10:30 AM - 11:45 AM
Thurgood Marshall North

Organizer(s): Robert Gordon, Johnson & Johnson; Mat Soukup, FDA/CDER

Chair(s): Robert Gordon, Johnson & Johnson

Approximately 1 year ago a Working Group was formed with over 30 members between the FDA, Academia and the Pharmaceutical Industry, charged with creating and promoting a standard palette of graphics for visualization of clinical trial safety data. We would like to share our experiences over the past year and our development plans for the future. This session will be given by representatives of the Industry/FDA/Academia Safety Graphics Working. The work stream consists of four sub teams (General Principles, General Adverse Events, Labs/Liver, and ECG/Vital Signs) Efforts of each sub team will be presented, including innovative graphical approaches to address key safety issues arising in the development of biologics and drugs. Graphical displays presented will emphasize the advantages of using data visualization approaches over traditional use of tabular summaries. Additionally, information on the use of a wiki environment for collaborative development of data visualizations will be shown. Such a collaborative environment allows continual development of new approaches along with information and software or code to implement the graphical approaches in each participating organization.

Wiki Resources for Answering Common Clinical Safety Questions with Graphs
View Presentation View Presentation Susan Duke, GlaxoSmithKline

Wiki Resources for Answering Common Clinical Safety Questions with Graphs – Part 2
View Presentation View Presentation Richard Forshee, U.S. Food and Drug Administration


PS2b Suicidal ideation and behavior in clinical trials: points of interest and statistical challenges for industry and regulators

10:30 AM - 11:45 AM
Thurgood Marshall South

Organizer(s): Mark Levenson, FDA/CDER; Lev Sirota, FDA/CDER; Shailaja Suryawanshi, Merck & Co., Inc.

Chair(s): Cristiana Gassmann-Mayer, Johnson & Johnson

In the last two decades the potential association between an increased risk of suicidal ideation/behavior and pharmaceuticals has been the center of intense debate among industry, regulators, and academia. The most recent FDA draft guidance (September 2010) on “suicidality” outlines the need for prospective collection of suicide-related events in clinical trials using a scale that maps to the Columbia Classification Algorithm of Suicide Assessment (C-CASA). The speakers will discuss the outstanding challenges on the specific aspects of assessment, analysis, and regulatory submission of suicide-related data. One speaker from industry will present a proposal for a statistical analysis plan for data collected by the Columbia Suicide Severity Rating Scale (C-SSRS). Statistical approaches will be outlined for data within individual clinical trials as well as for meta-analyses across trials. Another speaker will discuss issues with suicide-related data standards and statistical methods in accordance with the FDA technical guidance being developed to address recommendations for submission. The third speaker will focus on issues with prospective data collection by the C-SSRS instrument.

Analytical and Statistical Considerations for Prospectively Collected Data on Suicidal Thoughts and Behaviors
View Presentation View Presentation Mary Nilsson, Eli Lilly & Company

Suicidality Assessment across Multiple Indications using the C-SSRS: Improved Outcomes, Increased Precision with Decreased Burden
View Presentation View Presentation Kelly Posner, Columbia University

Title: On the Statistical Challenges Associated with Prospective Assessment of Suicidality in Clinical Trails
Antonio Paredes, Food and Drug Administration


PS2c Biomarker implements for advancing stratified medicine: statistical considerations for R&D and regulatory approval

10:30 AM - 11:45 AM
Thurgood Marshall East

Organizer(s): Jae K Lee, University of Virginia; Yang Yang, FDA; Jingjing Ye, Food and Drug Administration (FDA)

Chair(s): Deepak B. Khatry, MedImmune

Advances in biotechnology have made it possible to contemplate an era of stratified medicine—an era of personalized healthcare in which benefit/risk of available treatment options will be maximized for disease subgroups through judicial use of specialized drug development tools such as biomarkers. Investments in biomarker-based R&D and clinical development will need to be guided by appropriate statistical considerations. Study designs and statistical requirements for a company’s internal decision-making may differ from those seeking regulatory approval. Specific statistical considerations associated with qualification of biomarker tools and regulatory approval of their use as companion diagnostics will depend upon intended use. This session will bring together a panel of prominent statisticians from the FDA, academics, and industry to share their perspectives and experiences on the topic. The speakers will focus on study designs, statistical requirements, and regulatory expectations aligned with intended use of the biomarker tools. The presentations will be followed by Q&A and discussion.

Translating cancer genomics to effective treatments with companion diagnostics
View Presentation View Presentation Richard Simon, National Cancer Institute

A Regulatory Perspective on the Evaluation Companion Diagnostic Devices for Targeting Therapy
Thomas E Gwise, Center for Devices and Radiological Health, FDA

A Systems Approach to Clinical Trial Development with Selection Biomarkers
Robert Sikorski, Medimmune


PS2d New Paradigms for Statistical Support in R&D

10:30 AM - 11:45 AM
Thurgood Marshall West

Organizer(s): Judy X. Li, FDA; David Petulo, FDA; Xiongce Zhao, NIH

Chair(s): Xiongce Zhao, NIH

In most Pharmaceutical and oher research settings, it is expected that the industry statistician has "specialist" knowledge in all fields of statistics as well as therapeutic area expertise so clinical or scientific needs can be "translated" to statistical design and analysis contributions." An alternative paradigm is suggested where the industry statistician concentrates on understanding the therapeutic area, current regulatory trends, functions of other R&D team members, Company processes and Company culture, all "translational" functions, as well as most common statistical methodologies. But in addition, they would have adequate technical knowledge of both new and conventional statistical procedures and be able to, when needed, identify the "specialist" statistician, usually residing within academic departmetents, who have dedicated their careers to develop or apply the given procedure. This would provide the best technical knowlege to the Company and promote use of more current analysis approaches that may provide increased precision or power to evaluate treatment endpoints.

New Paradigms for Statistical Support in Pharmaceutical R&D
Dennis Cosmatos, Strategic Statistical Consulting

Beyond tables and P-values: Enhancing the role of the clinical trial team statistician
Sonia Davis, Quintiles

Collaboration of Statisticians: A perspective
Rajeshwari Sridhara, FDA


PS2e Confounding Issues: How to interpret and how to avoid

10:30 AM - 11:45 AM
Balcony C/D

Organizer(s): Judy X. Li, FDA/CVM; Junshan Qiu, FDA/CVM; Terry Settje, Bayer

Chair(s): Judy X. Li, FDA/CVM

During the evaluation process of veterinary products, confounding issues have been observed in the efficacy and safety studies. In this session, we will mainly focus on how to avoid confounding issues, especially during the stage of design. How to interpret the data generated from the study with confounding issues will also be discussed. The session will have speakers from both FDA and industry sharing their expertise and facilitating discussion on typical confounding issues in the study design and statistical methodologies for analyzing and interpreting the data with confounding parameters.

Salvaging a Statistical Analysis from a Confounded Design
View Presentation View Presentation Joseph F Boucher, Pfizer Animal Health

Confounding Variables in Poorly Designed Experiments
View Presentation View Presentation Junshan Qiu, FDA/CVM

Some examples of unrecognized confounding by researchers
William Lawrence Bryson, Boehringer Ingelheim Vetmedica, Inc.


Roundtable Topic: Adaptive Design

11:45 AM - 1:00 PM

TL01: Logistics and Implementation of Adaptive Trial Design
Eva R Miller, ICON Clinical Research

TL02: Adaptive Design - Experiences from Clincial Trials
Min Yao, Covance

TL03: Adaptive Design’s Past, Current, and Future
Xiaoyin (Frank) Fan, Vertex Pharmaceutical

TL04: Adaptive Design Execution: Being GCP Compliant
Philip T Lavin, Aptiv Solutions (formerly Averion Intl Corp)

TL05: Adaptive Design Trials for Preventive Vaccines
Amelia Dale Horne, FDA


Roundtable Topic: Biomarkers

11:45 AM - 1:00 PM

TL06: Biomarker Development, Validation Standards, and Reproducible Biomedical Research
Maha C Karnoub, Pfizer


Roundtable Topic: Collaboration

11:45 AM - 1:00 PM

TL07: Cross Pharma Initiatives
Herbert Thijs, Hasselt University - I-Biostat

TL08: Industry Standards for Analysis and Reporting
Mary Nilsson, Eli Lilly & Company

TL09: Biostatistics in Academia versus Industry
Christine Margaret Blasey, 1) Stanford University 2) Corcept Therapeutics

TL10: Statistical Programmer and Statistician - Are these Roles Interchangeable?
Nfii K Ndikintum, i3Statprobe; Eshetu T. Wondmagegnehu, Eli Lilly and Company


Roundtable Topic: Comparative Effectiveness

11:45 AM - 1:00 PM

TL11: Head-to-Head Studies: Comparing risks/benefits, or, risking a comparison?
CV Damaraju, J&J PRD, LLC

CANCELED - TL12: Value of Medicine - how can industry & regulators help in assessing the value to a Payer

TL13: How to meet the needs for high quality health outcome (HO) or patient-reported outcome (PRO) data in oncology trials?
Dachuang Cao, Eli Lilly and Company


Roundtable Topic: Devices/Diagnostics

11:45 AM - 1:00 PM

TL14: Statistical issues in companion diagnositcs
Rong Tang, FDA

TL15: Statistical Design and Analysis Challenges for Monitoring Devices
Shanti V Gomatam, FDA/CDRH/DBS

TL16: Improving Communications Between FDA, Sponsor and Advisory Panel
Gary Lynn Kamer, FDA/CDRH/OSB/DBS

TL17: Evaluation of diagnostic tests/devices with imperfect reference standard
Bipasa Biswas, FDA

TL18: Analytical studies in In Vitro Diagnostics
Yuqun Abigail Luo, FDA\CBER

TL19: Sensitivity/Specificity with a Inadequate Truth
Hope Baskerville Knuckles, Abbott


Roundtable Topic: DSMC/DSMB

11:45 AM - 1:00 PM

TL20: Safety Monitoring of Events of Interest in Placebo-Controlled Clinical Trials
Bradley McEvoy, CDER, FDA; Elena Polverejan, Johnson & Johnson

TL21: Practical Issues While Conducting a Clinical Trial DSMB
Mohammad Bsharat, Vertex Pharmaceuticals

TL22: IRB and DSMC: Who is responsible for what?
Charles Anello, Applied Statistical Concepts, LLC

TL23: Continuous Safety Monitoring for Randomized Controlled Clinical Trials with Blinded Treatment Information
Greg Ball, Astellas; Ken Gerald, Westat


Roundtable Topic: Futility

11:45 AM - 1:00 PM

TL24: Futility analysis and conditional power: Common practice in clinical trials
Somesh Chattopadhyay, FDA; Qi Jiang, Amgen; Li-an Xu, Bristol-Myers Squibb

TL25: Sample Size Re-estimation and Futility Analysis Based on Blinded Assessment of Interim Data
Wei Li, Daiichi Sankyo, Inc.; Jie (Jack) Zhou, FDA CDRH


Roundtable Topic: Methodology (Efficacy)

11:45 AM - 1:00 PM

TL26: Advance Methodologies and Available Softwares (SAS) in Analysing Overdispersed Count Data
Santosh C Sutradhar, Pfizer Inc.

TL27: Multiplicity Adjustments for Testing Endpoints in Clinical Trials - A Check-Up on Current Practice
Davis F Gates, Merck

TL28: Super-superiority trial with the consideration of clinical significance
Shiling Ruan, FDA/CDRH

TL29: Methods for handling composite endpoints: advantages and disadvantages
Jennifer Rogers, London School of Hygiene and Tropical Medicine; Janet Wittes, Statistics Collaborative

TL30: How to define the minimum clinically important difference for a clinical trial
Amy T Ko, Merck & Co., Inc.

TL31: Unique Statistical Considerations in Alzheimer's Disease Studies: Delayed Start, Biomarkers and More.
Hong Liu-Seifert, Eli Lilly and Company

Kisook Yoo, Roche

TL33: Empirical Bayes methods in drug dosage individualization based on linear models
Francisco J Diaz, The University of Kansas Medical Center

TL34: Repeated-Measures Mixed Model Building
Changsheng Lao, FDA\CDRH

TL35: Regulatory impact and issues of joint modeling of longitudinal and time-to-event
Mark Ernest Boye, Eli Lilly and Company; Ping Wang, Eli Lilly and Company

TL36: Multi-regional Trials: Design, Analysis, and Interpretation
Susan Huyck, Merck Research Laboratories

TL37: Blinding assessment in randomized clinical trial
Ying Yang, FDA

TL38: Decision analysis in the development of medical products
Bruce Binkowitz, Merck, Sharpe, and Dohme

TL39: Missing Data: Alternatives to Imputation
Bob Abugov, FDA

TL40: Clinical Experiment and Statistical challenges to analyze and report Composite Endpoints
Tianhui Zhou, Pfizer

TL41: Beyond RECIST, enhancing the clinical relevance of Progression-Free Survival in oncology
James T Love, Boehringer Ingelheim Pharmaceuticals

TL42: Bayesian nonparametrics: Potentially useful or a playground for mathematicians?
Steven Frank Thomson, Food and Drug Administration

TL43: Are global tests a practical option for regulatory clinical trials?
Pablo E. Bonangelino, FDA/CDRH/OSB/DBS

TL44: Predictions in Clinical Trials
Gui-shuang Ying, University of Pennsylvania

TL45: Logitudinal ANCOVA vs. Constrained Longitudinal Data Analysis Model
Xiaoming Li, Merck Research Laboratories; Jiajun Liu, Merck Research Laboratories

TL46: Working Together to Achieve the Promise of Personalized Medicine
Donald E. Stull, United BioSource Corporation; Kathleen W. Wyrwich, United BioSource Corporation

TL47: Handling protocol violations... do you use gloves?
Daniel Cotton, Boehringer Ingelheim Pharmaceuticals, Inc

CANCELED - TL48: Practical Challenges arising from Study Assumption Deviations

TL49: Evidence-based medicine - the issues/limitations in determining standard of care
Arlene S. Swern, Celgene Corporation


Roundtable Topic: Non Inferiority

11:45 AM - 1:00 PM

CANCELED - TL50: The Stochastic Curtailment and Its Visualization For Non-inferiority Case vs. Superiority Case
Shaoyi Li, ASA Member

TL51: Margin selection in non-inferiority trials
Chul Ahn, FDA

TL52: Some Practical Issues on Designing Non-inferiority Trial
Xia Xu, Merck Research Laboratories

TL53: Statistical Issues in Designing Non-Inferiority Studies with an Emphasis on Veterinary Medical Issues
Anna Nevius, FDA/CVM


Roundtable Topic: Safety

11:45 AM - 1:00 PM

TL54: Safety Evaluation: When, What, How?
Aloka G Chakravarty, US FDA

TL55: Benefit and risk assessments in comparison of anticoagulants
James Hung, FDA; Susan Qiuzhen Wang, Boehringer-Ingelheim Pharmaceuticals, Inc.

TL56: Program Safety Analysis Plan and Safety Reporting Rules
Wei Wang, Eli Lilly And Company

TL57: Small Event Rates, Big Outcome Studies
Jennifer Elisabeth Hamer-Maansson, AstraZeneca

TL58: Strategic Issues in Meeting Cardiovascular Risk Assessment Requirements for Diabetes Drug Development
Shailaja Suryawanshi, Merck & Co., Inc.


Roundtable Topic: Study Design

11:45 AM - 1:00 PM

TL59: Design and Analysis of Non-Interventional/ Observational Clinical Trials
Shankar Srinivasan, Merck

TL60: High Placebo Response - Recent Trend in Psychiatric Clinical Trials, Design and Analysis
Yeh-Fong Chen, US Food and Drug Administration; Lu Zhang, Eli Lilly and Company

TL61: Some Design Issues in Biologic Product Applications
Shiowjen Lee, FDA\CBER\OBE\DB

TL62: Oncology Phase I Clinical Trial Designs: Can Current Approaches Be Improved To Increase Efficiency and Effectiveness?
Serap Sankoh, Millennium Pharmaceuticals: The Takeda Oncolgy Company


PS3a The New Topology of Safety - Program Safety Analysis Plan and Safety Reporting Rules

1:00 PM - 2:15 PM
Thurgood Marshall North

Organizer(s): Andreas Brueckner, Bayer Pharmaceuticals; Mary Nilsson, Eli Lilly & Company; LaRee Tracy, FDA

Chair(s): Mary Nilsson, Eli Lilly & Company

Better planning and implementation of meta-analysis of safety data early in drug development is becoming increasingly important. This session will provide insights, experiences and perspective regarding implementation of a program safety analysis plan (PSAP) as recommended by Safety Planning, Evaluation and Reporting Team (SPERT). In addition, an FDA speaker will provide further guidance on the new rules/requirements for safety reporting given in the draft FDA Guidance titled Safety Reporting Requirements for INDs and BA/BE Studies.

Development of a Program-Wide Safety Analysis Plan
View Presentation View Presentation Amy Xia, Amgen, Inc.

Safety Analysis Planning for Treatments Used in Multiple Indications
View Presentation View Presentation Achim Guettner, Novartis Pharma AG

Lilly Program Safety Analysis Plan Implementation and Bayesian Dose Response
View Presentation View Presentation Wei Wang, Eli Lilly And Company

Safety Reporting Requirements for INDs and BA/BE Studies
Robert Temple, FDA


PS3b Addressing Bias in the Evaluation of Diagnostics

1:00 PM - 2:15 PM
Thurgood Marshall South

Organizer(s): Brandon D Gallas, FDA/CDRH/OSEL/DIAM; Thomas E Gwise, Center for Devices and Radiological Health, FDA; Vicki H. Petrides, Abbott Diagnostics; Alicia Toledano, Statistics Collaborative, Inc.

Chair(s): Thomas E Gwise, Center for Devices and Radiological Health, FDA

Diagnostic effectiveness has two components that are at odds with each other: the ability to correctly identify diseased patients and the ability to correctly identify non-diseased patients. One of the challenges encountered in diagnostic trials is how to minimize the often unavoidable bias inherent in these trials. There are many sources for potential bias in diagnostic studies – instrument bias, reader bias, spectrum bias, etc. The speakers in this session will share their perspectives on the different types of bias that can occur in diagnostic studies and discuss the merits and shortcomings of methods to address bias.

Enriched designs for assessing predictive performance – analysis of bias and variance.
View Presentation View Presentation Paul Pinsky, DIAM, OSEL, CDRH,FDA

Reader Bias in Imaging Clinical Trials: Are Independent Central Readers the Answer or Problem
View Presentation View Presentation David L Raunig, Pfizer

Reducing Bias and Increasing Diagnostic Utility Through Diagnostic Risk Models
View Presentation View Presentation Frank Eanes Harrell, Vanderbilt University


PS3c Issues on Correlates of Protection in Vaccine Development

1:00 PM - 2:15 PM
Thurgood Marshall East

Organizer(s): Charles Liss, Merck; Guoying Sun, FDA; Lihan Yan, USFDA

Chair(s): Xiaoming Li, Merck Research Laboratories

Biomarkers are frequently used in clinical trials as predictors for clinical outcomes, in an effort to reduce time and cost of the development of drugs and vaccines. In vaccine studies, immunogenicity results often play an important role in helping the investigators to understand biological responses to vaccines, and can potentially be used as indicators for the clinical outcomes if correlates with vaccine protection are established. In practice, it could be challenging to evaluate and establish the surrogacy of a biomarker with clinical outcome(s), or in the case of vaccine studies, determine the immunological correlates of protection. This session will address some of the statistical issues involved in evaluating correlates of protection, focusing on vaccine clinical trials. Speakers from the US FDA and pharmaceutical industry (Drs. Robert Kohberger, Tsai-Lien Lin, and Ivan S.F. Chan) will discuss the latest development on correlates of protection methods for vaccines.

Inferences From Tests of Biodefense Vaccines
View Presentation View Presentation Michael P Fay, NIAID-NIH

Experimental Designs and Statistical Methods for Post-licensure Immunological Correlates of Protection
View Presentation View Presentation Andrew Dunning, Sanofi Pasteur

Assessing the predictive value of Immunological markers in vaccines
Ivan Chan, Merck & Co., Inc.

Correlates of Protection: What have we done, What do we do now?
Tsai-Lien Lin, CBER/FDA


PS3d Primary Endpoint in Oncology Trials - OS or PFS?

1:00 PM - 2:15 PM
Thurgood Marshall West

Organizer(s): Huanyu Chen, FDA; Linda Sun, Merck & Co.; Kathy Zhang, Amgen Inc.

Chair(s): Jodi Rylance, Quintiles

Although Overall Survival (OS) is the gold standard of demonstrating clinical benefit for anti-cancer therapies, Progression Free Survival (PFS) has been also used as a key endpoint. However, results from many trials indicate that the use of PFS as a surrogate endpoint for OS is questionable. In this session, issues related to this surrogacy will be discussed.

Predictability of Overall Survival by Progression-Free Survival: A Simulation Study
View Presentation View Presentation Lijun Zhang, FDA

Quantification of PFS effect for oncology drug approvals
View Presentation View Presentation Cong Chen, Merck & Co., Inc.


CMC1: Finding Meaningful Links between CMC Quality Attributes and Clinical Outcomes in a QbD Framework

1:00 PM - 2:15 PM
Balcony C/D

Organizer(s): Meiyu Shen, FDA; Charles Tan, Pfizer

Chair(s): Anthony Lonardo, ImClone Systems

One important goal of QbD is to develop a deeper scientific understanding of methods and processes leading to pharmaceutical products that will ultimately benefit patients through advanced control strategies. A major consideration in achieving this goal, which remains elusive nearly 10 years into the QbD era, is to find linkages between acceptance criteria of manufacturability factors/performance measures with clinical endpoints or surrogates (eg particle size of API with PK parameters). This session will explore joint industry and agency collaborations and individual company initiatives to address the difficulties in establishing these linkages.

Establishing Acceptance Criteria of Quality Attribute Based on QbD Principles
View Presentation View Presentation Harry Yang, MedImmune

Integrating QbD and Biopharmaceutics: The Nine Synergistic Areas for Optimizing Product Quality for Patient Benefit
Arzu Selen, FDA

Discussant(s): John Crison, BMS; Yi Tsong, CDER, FDA


PS4a Statistical Challenges Encountered in Assessing Immunogenicity Data from Vaccine Trials

2:30 PM - 3:45 PM
Thurgood Marshall North

Organizer(s): Andrew Dunning, Sanofi Pasteur; Barbara Krasnicka, FDA

Chair(s): Mridul K Chowdhury, FDA; Anthony Homer, Sanofi Pasteur

In vaccine clinical trials, both the efficacy of the vaccine and the consistency of vaccine production (lot-to-lot consistency) are routinely assessed based on the immunogenicity data. Multi-dimensional responses of the human immune system to vaccination, as well as lot-to-lot consistency are often evaluated using titer levels measured by validated assays. However, many factors that have influence on the immunogenicity data are not always properly taken into account in the statistical methods utilized in vaccine clinical studies. In this session, statistical methodologies for addressing problems such as (1) titer variability and its association with assay runs, (2) missing data, and (3) appropriate design of lot-to-lot consistency studies will be discussed and their applications illustrated by some examples. Many of the issues presented during the session might have relevance to other products for which assays are used to determine primary efficacy endpoints. Speakers: Niel Hens (Univ. Leuven, Belgium), Yunda Huang (Fred Hutchinson Cancer Research Center), John Jezorwski (Sanofi Pasteur)and Jitendra Ganju (Amgen Inc.).

Dealing with Missing Data in Vaccine Clinical Trials: from Academics to the Industry
View Presentation View Presentation Niel Hens, I-BioStat, Hasselt University

Application of Recent Guidance on Missing Data to Truncated Immunogenicity Data
View Presentation View Presentation John Jezorwski, Sanofi Pasteur

Comparing and Combining Data across Laboratories after Correcting for Inter-laboratory Variation via Integration of Paired-sample Data
View Presentation View Presentation Yunda Huang, Fred Hutchinson Cancer Research Center

Robust inference from multiple statistics via permutations
Jitendra Ganju, Amgen Inc.


PS4b Propensity Score Analysis and Observational Studies

2:30 PM - 3:45 PM
Thurgood Marshall South

Organizer(s): Alan J. Menius, GlaxoSmithKline R&D; Raj Nair, CDRH, FDA; Xiting Cindy Yang, CDRH, FDA; Xiaohua Douglas Zhang, Merck Research Laboratories

Chair(s): Roger Frank Liddle, GlaxoSmithKline R&D

For drug and medical device safety assessment, observational studies are widely used to study the post-approval drug exposed population. In design stage, when randomized control trial is not possible due to ethical or practical reasons, carefully designed observational studies with historical or contemporary controls are more preferable than a single arm study design with a performance goal because the former does not have the burden of having to come up with an agreed number and can better approximate results from randomized experiments. The propensity score, which is the probability of treatment exposure conditional on covariates can be used in observational studies to adjust for confounding. In this session, observational studies with propensity score analysis will be reported and discussed. Organizers: Xiting Cindy Yang (FDA); Xiaohua Douglas Zhang (Merck); Rajesh Nair (FDA); Alan Menius (GlaxoSmithKline) Speakers: Lilly Yue (FDA, confirmed); Don Rubin (Harvard University, confirmed); Vinay Mehta(Merck Research Laboratories);

The Use of Propensity Scores (PS) in Observational Research
View Presentation View Presentation Vinay Mehta, Merck

Designing Observational Studies for Causal Effects Using Propensity Scores
Donald Rubin, Harvard University

Issues with Observational Clinical Studies and Application of Propensity Score Methodology in Regulatory Settings
Lilly Yue, U.S. Food and Drug Administration


PS4c Bayesian analysis in the context of small clinical trials

2:30 PM - 3:45 PM
Thurgood Marshall East

Organizer(s): Matthew Guo, Amgen; Jiang Hu, FDA/CBER/OBE; Estelle Russek-Cohen, US Food and Drug (CBER); Yanping Wang, Eli Lilly and Company

Chair(s): Estelle Russek-Cohen, US Food and Drug (CBER)

Statistical methods for clinical trials that are currently used and broadly available were developed to analyze relatively large clinical trials. Historically no special attention has been paid to small clinical trials and clinical trials with rare events. This session will discuss statistical issues for small clinical trials and clinical trials with rare events. Recent statistical methodologies including Bayesian methods and exact statistics may be promising in studying small clinical trials. Case studies for small clinical trials will also be presented and discussed.

Bayesian Augmented Control: Borrowing Information from Historical Control Data to Enhance a Trial
View Presentation View Presentation Kert Viele, Berry Consultants

Bayesian Sample Size Estimates in Clinical Trials with Dichotomous Outcomes
View Presentation View Presentation Boris G Zaslavsky, FDA

Experience of Subgroup Analysis in Small Clinical Trials
View Presentation View Presentation Kun Nie, Amgen Inc.


PS4d Cognitive and Surrogate Biomarkers Endpoints in Clinical Trials of Early Alzheimer’s Disease

2:30 PM - 3:45 PM
Thurgood Marshall West

Organizer(s): Richard Entsuah, Merck Reserach Labs; Xiang Ling, FDA; Jingyu (Julia) Luan, FDA

Chair(s): Richard Entsuah, Merck

Alzheimer’s disease (AD) trials have traditionally assessed the ability of treatments to slow cognitive and functional decline within patients with clinically diagnosed disease. However, the AD neurodegenerative process is well established by the time clinical diagnostic criteria for dementia are met, by which point the disease may not be responsive to therapy. Therefore industry is actively pursuing trial designs targeting the earliest stages of disease. These designs present challenges, including finding appropriate outcomes for assessing treatment effects. The standard cognitive cognitive measure, the ADAS-Cog, has well-known ceiling effects that limit its ability to measure progression in the early stages of the disease. Alternative endpoints, including cerebrospinal fluid and neuroimaging biomarkers responsive to the earliest stages of disease are being actively pursued. This session will examine the ADAS-Cog as a clinical endpoint for pre-symptomatic and early AD, and will explore the challenges and potential utility of surrogate biomarkers as endpoints for clinical trials. FDA representatives will discuss regulatory perspectives on these issues.

Optimizing The ADAS-Cog For MCI And Early AD
Nandini Raghavan, Johnson & Johnson Pharmaceutical Research & Development

Biomarker Endpoints for Clinical Trials in Alzheimer's Disease
Steven D. Edland, University of California, San Diego

Discussant(s): Russell Katz, FDA/CDER; Sue-Jane Wang, US FDA


CMC2: Making QbD Work (Small Molecules Focus)

2:30 PM - 3:45 PM
Balcony C/D

Organizer(s): Anthony Lonardo, ImClone Systems; Jinglin Zhong, FDA/CDER

Chair(s): Stan Altan, Johnson and Johnson

This session will explore some of the specific challenges associated with QbD when working with small molecules. This will include an examination of contrasting case studies and modern control methodologies.

Statistical Issues in QbD and Design Space
Meiyu Shen, FDA

Statistical Considerations when Evaluating Content Uniformity
View Presentation View Presentation James Bergum, Bristol-Myers Squibb

Discussant(s): David Christopher, Merck; Yi Tsong, CDER, FDA


PS5a Challenges and Opportunities for Designing and Analyzing Cancer Vaccine/Immunotherapy Clinical Trials

4:00 PM - 5:15 PM
Thurgood Marshall North

Organizer(s): Xue Lin, FDA; Lianng Yuh, Endo Pharmaceuticals

Chair(s): Lianng Yuh, Endo Pharmaceuticals; Boquang Zhen, FDA

2. There are many critical challenges in designing and analyzing cancer vaccine/immunotherapy studies. Currently, only one oncology product is approved by FDA. Traditional efficacy endpoints (tumor response or disease progression) may not be optimal to examine the treatment effects and commonly acceptable biomarkers or immune responses have not been identified. It takes a longer time and more resources to utilize the survival data. The Proportional hazard function assumption may not hold and the treatment effect may be highly correlated with the patient baseline disease stage. The objective of this plenary session is to share current clinical and statistical issues and discuss potential solutions to address unmet clinical study and analysis needs. Both clinicians and statisticians from FDA and industry will participate in this session.

Clinical Trial Design and Analysis Issues for Cancer Vaccines - Clinical Perspective
View Presentation View Presentation Peter Bross, CBER, FDA

Clinical Trial Design and Analysis Issues for Cancer Vaccines - Statistical Perspective
View Presentation View Presentation Brent A. Blumenstein, TriArc Consulting

Discussant(s): Lee-Jen Wei, Harvard University


PS5b Regulatory impact and issues of joint modeling of longitudinal and time-to-event

4:00 PM - 5:15 PM
Thurgood Marshall South

Organizer(s): Steven Bai, FDA; Ping Wang, Eli Lilly and Company

Chair(s): Wei Shen, Eli Lilly and Company

Many clinical trials and observational studies collect both time-to-event data and longitudinal phenotypic data (e.g. biomarkers, quality of life measurements). Joint modeling of these two types of data has gained its popularity recently because of its ability to reveal the relationship between a longitudinal response process and a time-to-event variable as well as its ability to eliminate the bias in two-stage methods and improve efficiency. However, joint modeling has not been commonly used in designing or in the primary analysis of clinical trials (Ibrahim et al. 2010). This session will have a rich discussion on impact/value and issues/concerns with increasing joint modeling use in clinical trials. This session will start with a general introduction of joint modeling with a short review of the joint modeling approaches available (e.g. EM and Bayesian), then focus on real examples and conceptual utilization of joint modeling under various circumstances, and end with discussion. Presenters from the FDA, academia, and industry will share their thoughts based on their research and trial experience.

Testing Treatment Efficacy in Clinical Studies Consisting of Multiple Subpopulations
Fanhui Kong, FDA

Sample Size and Power Determination in Joint Models of Survival and Longitudinal Data]
View Presentation View Presentation Joseph G Ibrahim, UNC

Discussant(s): Mark Ernest Boye, Eli Lilly and Company


PS5c Challenges of Using Meta-Analyses in Drug Safety and other Evaluations

4:00 PM - 5:15 PM
Thurgood Marshall East

Organizer(s): Paul DeLucca, Merck; Xiaoping Jiang, FDA; Qian Li, FDA; Deborah Shapiro, Merck

Chair(s): Xiaoping Jiang, FDA

We have encountered many statistical and logistical challenges in meta-analyses using clinical trial data in drug safety evaluation and other evaluations. In this session, we discuss statistical methods and models in Meta-Analyses that can be used to handle rare event data, dose-response trend assessment, varying risk overtime, studies with zero events, and other challenging issues. Two case studies of drug safety evaluation will be used to address these challenges.

Atrial fibrillation and Alendronate: Meta-Analysis
View Presentation View Presentation Arvind K Shah, Merck & Co

Addressing the Issues of Dose-Response Assessment and Varying Risk in Drug Safety Evaluation Using Meta-Analysis
Qian Li, FDA

Discussant(s): Kay Dickersin, Johns Hopkins University


PS5d Exposure-Response Modeling to Facilitate Future Study Designs of Drug Development Programs

4:00 PM - 5:15 PM
Thurgood Marshall West

Organizer(s): Li Chen, Amgen; Junshan Qiu, FDA/CVM; Harry Yang, MedImmune

Chair(s): Li Chen, Amgen

In phase II clinical trials, exposure-response modeling and analysis plays a critical role in the determination of drug safety and efficacy. It allows for studying the relationship of drug exposure and effects of efficacy and safety, integrating knowledge from various drug development stages, and selecting an appropriate dosing regimen(s) for confirmatory studies. However, exposure-response modeling and analysis can be very challenging. Potential Issues which may impact the outcome of the analysis include delay between exposure and response measurements, confounding relationship between exposure and risk factors for response endpoints, and informative missing exposure data for a subgroup. This session will cover several case studies of exposure-response modeling and analysis from early/mid-phase trials to guide dose-selection in late phase trials. Both impact and limitations of exposure-response modeling and analysis on study designs will be discussed.

Mechanistic pharmacokinetic-pharmacodynamic modeling to facilitate the design of proof-of-concept clinical trials
Bing Wang, MedImmune

Case Study in Oncology of Exposure-Response Modeling Guiding Choice of Dosing Regimen for Confirmatory Studies
Eric Rasmussen, Amgen, Inc.

Novel Application of Case-Control Analysis in Confounded Exposure-Response
Yaning Wang, U.S. Food and Drug Administration


CMC3: Making QbD Work (Large Molecules Focus)

4:00 PM - 5:15 PM
Balcony C/D

Organizer(s): Martha Lee, FDA; Anthony Lonardo, ImClone Systems

Chair(s): Tsia- Lien, FDA

This session will explore both the unique characteristics of making QbD work with large molecules and the areas where there is overlap with the small molecule world.

Regression To The Rescue: The Use Of Statistical Doe To Derive A Novel Manufacturing Control Strategy For Ensuring The Quality Of An Antibody-Drug Conjugate
Daniel A. Coleman, Genentech Inc.

Quality by Design for Biotechnology Products
View Presentation View Presentation Steven Kozlowski, FDA

Discussant(s): Harry Yang, MedImmune; Jinglin Zhong, FDA/CDER


Wed, Sep 21

PS6a Multi-Regional Trials with Different Endpoint Requirements by Region

8:30 AM - 9:45 AM
Thurgood Marshall North

Organizer(s): Brent Burger, Cytel, Inc.; CHIA-WEN KO, FDA; Daphne Lin, FDA; Shailendra Menjoge, Boehringer Ingelheim

Chair(s): Brent Burger, Cytel, Inc.

In multi-regional clinical trials, different regulatory agencies within different regions often have different requirements for endpoints. In addition, therapeutic area guidances can recommend different endpoints for hypothesis testing. Differences may include what endpoints or time-points are considered primary or secondary, choice of analysis populations or non-inferiority margins, etc. Different regional requirements for endpoints can result in challenges in the design, conduct and analysis of multi-regional trials within global drug development programs. One interesting and challenging question is - do differences in endpoints required by different regions lead to multiple testing issues? Because each analysis is carried out separately to satisfy specific regional regulatory needs, should a multiplicity adjustment be applied for the number of tests performed? Since each regional health authority is only examining one specific endpoint as primary, is multiplicity adjustment necessary?

Handling Different Regulatory Authority Endpoint Requirements in Multi-Regional Clinical Trials
View Presentation View Presentation Cynthia Girman, Merck Research Laboratories

Designing MRCTs with Different Regional Required Primary Endpoint
Yi Tsong, FDA

View Presentation View Presentation Alex Dmitrienko, Eli Lilly and Company; Sue-Jane Wang, US FDA


PS6b Recent Developments in Adaptive Design Methodology

8:30 AM - 9:45 AM
Thurgood Marshall South

Organizer(s): Vladimir Dragalin, Quintiles Innovation; Cristiana Gassmann-Mayer, Johnson & Johnson; Kooros Mahjoob, FDA/CDER; Gene Pennello, FDA

Chair(s): Pilar Lim, Johnson&Johnson

The statistical theory and methods for adaptation in clinical trial planning and execution has become an important segment of statistical methodology to design clinical studies more efficiently as also highlighted in the 2010 FDA guidance. One speaker will present new developments in two-stage designs with sample size adaptation to highlight that this new design can be more efficient than group sequential ones. This will resolve the controversial debate on efficiency of adaptive designs, control of the Type 1 error, gain in power. Another speaker will address the potential utilities and pitfalls of adaptive designs from a regulatory perspective. Of these designs, illustrations of adaptive selection designs seen in regulatory applications will be provided eg selection of a subgroup of patients for statistical testing, and selection of dosing regimens. The third speaker will present a Hierarchical Bayesian model in a phase II oncology clinical trial where the disease is categorized into multiple subtypes and the primary outcome is binary. The hierarchical model allows treatment effects to differ across subtypes assuming a priori that the effects are exchangeable and correlated.

On Efficient Two-Stage Adaptive Designs for Clinical Trials with Sample Size Adjustment
Qing Liu, Statistical Science, J&J

Adaptive Selection Designs in Regulatory Applications
James Hung, FDA

Hierarchical Bayesian Approach to Phase II Trials in Diseases with Multiple Subtypes
View Presentation View Presentation J. Kyle Wathen, Johnson & Johnson


PS6c Sensitivity Analyses of Incomplete Longitudinal Clinical Trial Data

8:30 AM - 9:45 AM
Thurgood Marshall East

Organizer(s): Steven Bai, FDA; Jiajun Liu, Merck Research Laboratories; Qi Zhang, Eli Lilly and Company

Chair(s): Steven Bai, FDA

It has been recently emphasized that when analyzing the longitudinal clinical trial data, the assumption of missing at random (MAR) is not necessary true. Therefore, appropriate sensitivity analyses under MNAR (missing not at random) assumption are warranted. Although the methods for sensitivity analysis under MNAR are being developed quite extensively in academic paper, the application of those methods in real clinical trials are currently limited. Especially, the selection of the most appropriate sensitivity analysis method, the details of how those methods are implemented, and interpretation of results are still not clear, which imposed the difficulties to both Industry and FDA for data analysis and decision making for drug approval. Therefore, it is urgent and necessary to have open dialogue between industry, academic and FDA to share experience and to provide guidance and suggestions for the future clinical trials.

Placebo Multiple Imputation and Other Sensitivity Analyses for Incomplete Longitudinal Clinical Trial Data
View Presentation View Presentation Craig H Mallinckrodt, Eli Lilly and CO

Assessment of Participants’ Intent to Attend Clinical Trial Sessions: Roles and Limitations
View Presentation View Presentation Andrew C. Leon, Weill Cornell Medical College

Sensitivity Analysis for Non-Monotone Missing Data with Application to Tuberculosis Studies
Daniel Oscar Scharfstein, Johns Hopkins University

Discussant(s): Thomas Permutt, FDA


PS6d Statistical Considerations for Assessing Biosimilarity and Interchangeability of Follow-on Biologics

8:30 AM - 9:45 AM
Thurgood Marshall West

Organizer(s): Eric Chi, Amgen Inc; Stella C. Grosser, FDA; Sandeep M Menon, Pfizer Inc./ Boston university; Casey Xu, FDA

Chair(s): Eric M Chi, Amgen Inc

As a regulatory pathway for follow-on biologics (FoBs) is being established, many statistical issues and considerations need to be addressed. Sound and objective statistical evaluations of, and practical design for, biosimilarity and interchangeability between FoBs and their reference innovators are the objective of this proposed session. A balance is the desired goal between reward for innovation and affordable medicines for patients, without compromising patients’ safety.

Biosimilar Regulations
View Presentation View Presentation Stella C. Grosser, FDA

Statistical Considerations for the Development of Follow-on Biologics – An Industry Statistician’s Perspective
View Presentation View Presentation Patrick Darken, Teva Pharmaceuticals

Scientific Factors for Assessing Biosimilarity and Drug Interchangeability of Follow-on Biologics
View Presentation View Presentation Shein-Chung Chow, Duke University


PS6e Problems Associated with Unbalanced Center Enrollment

8:30 AM - 9:45 AM
Balcony C/D

Organizer(s): Louis G Luempert, Novartis Animal Health

Chair(s): Wei Zhang, FDA/CVM

Animal health studies involve relatively few subjects. The distribution of patients over clinics is an important factor in the power to detect treatment differences. If centers are considered random effects and reduced effectiveness is observed at any of the small centers, the contribution of the results from the small centers to the overall evaluation of effectiveness can be serious. This session will discuss statistical and clinical methods to minimize the effect of imbalance.

Unequal Clinic Size – Issues and Potential Solutions
Theresa Real, Novartis Animal Health

Generalized Linear Mixed Models in Veterinary Studies
View Presentation View Presentation James R Schwenke, Applied Research Consultants

The Impact of Unequal Site Sizes in Multi-site Studies
View Presentation View Presentation Virginia F Recta, Food and Drug Administration


PS7a Challenges in Subgroup Analyses in Multi-Regional Clinical Development

10:00 AM - 11:15 AM
Thurgood Marshall North

Organizer(s): Yoko Adachi, FDA; Brent Burger, Cytel, Inc.; Joshua Chen, Merck

Chair(s): Joshua Chen, Merck

Increasingly, diverse regions (Asia, South America, Eastern Europe) are included in global MRCT trials. Two of the key challenges are how to define "region” and assessing consistency of treatment effect. Careful prospective planning of regional subgroup analysis taking into account ethnic factors be more important than geography in defining a region. Once regions/subgroups are defined, other challenges include: pre-specification and sample size planning, methods and criteria for assessing consistency of treatment effect among regions, interpretation/exploration of regional subgroup findings, product labeling.

Multi-regional Clinical Trial: Challenging Issues and Steps Forward
James Hung, FDA

Points to Consider in Defining Region and Consistency Assessment in Multi-Regional Clinical Trials
Yoko Tanaka, Eli Lilly and Company

Discussant(s): David DeMets, University of Wisconsin-Madison


PS7b Implementation and Conduct of Adaptive Trials

10:00 AM - 11:15 AM
Thurgood Marshall South

Organizer(s): Jessica Kim, FDA/CBER

Chair(s): Susan Huyck, Merck Research Laboratories

Recent high-profile events have increased interest in the conduct of clinical trials including: the Feb. 2010 release of the FDA guidance Adaptive Design Clinical Trials for Drugs and Biologics and the Oct. 2010 retraction of the Journal of Clinical Oncology 2007 genomics article by Nevins et al from Duke University due to data management issues. Study conduct in all types of clinical trials can derail scientific research and lead to questionable data of limited value for analysis. This session will focus on points-to-consider when planning and conducting adaptive design trials not only from an analysis perspective, but also taking into account planning for more complex randomizations, enrollment, blinding issues, clinical supplies, data management, results dissemination and FDA guidance. Specific attention will be paid to who and when access is granted to trial data which may be used for adaptations to the design. Based on their involvement and experiences with the implementation and operation of adaptive trials, the speakers will share their insights into the checks and balances, lessons learned, and proactive approaches to ensure smooth trial conduct and data integrity.

Practical Considerations for Adaptive Design Trial Execution
View Presentation View Presentation Weili He, Merck & Co., Inc

Overview, Hurdles, and Future Work in Adaptive Designs
View Presentation View Presentation Christopher S. Coffey, University of Iowa

Adaptive Dose-Finding in First-in-Man: Case Study
View Presentation View Presentation Anastasia Ivanova, University of North Carolina at Chapel Hill

Regulatory Perspectives: Adaptive Design Trial Conduct
View Presentation View Presentation Renee C Rees, FDA/CBER


PS7c Discussion of the 2010 National Research Council's Recommendations for The Prevention and Treatment of Missing Data in Clinical Trials

10:00 AM - 11:15 AM
Thurgood Marshall East

Organizer(s): Kari Brenda Kastango, Sunovion Pharmaceuticals Inc.; Gosford Aki Sawyerr, Purdue Pharma, LP

Chair(s): Bradley P Carlin, University of Minnesota

On July 19, 2010 the National Research Council’s Panel on Handling Missing Data in Clinical Trials released a 134-page report containing 20 recommendations on the prevention and treatment of missing data in clinical trials. This session will include four panelists (from regulatory, academia, and industry) who will discuss the motivation for the report, its findings, relevance, and current and likely future impacts. The discussion will initially focus on some of the recommendations, including how data collected from individuals after they stop study-specific treatment but complete study assessments for the entire trial are to be used and interpreted, trial design strategies to reduce missing data, choice of endpoints and estimand in the presence of treatment changes, choice of statistical models and software to assist in design and analysis. Additionally, the panel will discuss challenges to implementation of the recommendations, and the role of statisticians in this effort. Each panelist will have 8-10 minutes of prepared remarks, followed by questions from the organizers and the floor, as moderated by the chair.

Panel Discussion on the NAS Missing Data Report
View Presentation View Presentation Christy Chuang-Stein, Pfizer Inc; Roderick J. Little, University of Michigan; Thomas Permutt, FDA; Jay P. Siegel, Johnson & Johnson


PS7d Benefit-Risk: Case Studies and Panel Discussion

10:00 AM - 11:15 AM
Thurgood Marshall West

Organizer(s): Bruce Binkowitz, Merck, Sharpe, and Dohme; Nathan Enas, Eli Lilly and Company; Caiyan Li, FDA\CDRH\OSB; Rama Lakshmi Vishnuvajjala, FDA/CDRH/OSB/DBS

Chair(s): Bruce Binkowitz, Merck, Sharpe, and Dohme

Presentation of four or five brief summaries/examples of what has been done in recent submissions around Benefit-Risk (each summary limited to 10 or 15 minutes). Examples could be anonymous and presented by the FDA. This would be followed by an expert panel/discussion where panel members share their thoughts on strengths, weaknesses, and learnings.

Using Decision Analysis to Inform Drug Development
Marilyn A Metcalf, GlaxoSmithKline R&D

Using Quantitative Decision Analysis in the Regulation of Medical Devices
View Presentation View Presentation Telba Irony, Center for Devices and Radiological Health - FDA

Multiattribute Decision Analysis and Benefit-Harm Characterization
View Presentation View Presentation James C. Felli, Eli Lilly & Co.


PS7e Statistical Methods in Non-clinical Data Analysis

10:00 AM - 11:15 AM
Balcony C/D

Organizer(s): Nysia Inet George, FDA/NCTR; Na (Michael) Li, MedImmune

Chair(s): Nysia Inet George, FDA/NCTR

This session will consist of talks covering statistical methodologies for various non-clinical settings. Participants will highlight important issues of current interest to FDA and industry statisticians. The session will focus on analytical needs in non-clinical data analysis and applied methodological approaches that promote safety, efficiency, and accuracy.

Similarity Measurement of Array-based Comparative Genomic Hybridization Data in Evaluation of Whole Genome Amplified DNA
Ching-Wei Chang, NCTR, FDA

Modified exact poly-3 test
View Presentation View Presentation Min Min, FDA

Improving translation of in vivo disease efficacy models
View Presentation View Presentation Peter Ceuppens, AstraZeneca


GS1 Evolving Role of Data Monitoring Committees in the 21st Century

12:30 PM - 2:00 PM
Grand Ballroom Salon 1

Organizer(s): Yeh-Fong Chen, US Food and Drug Administration; Karen L Kesler, Rho, Inc.; Carmen Mak, Merck Research Laboratories; Pabak Mukhopadhyay, Novartis

Chair(s): Tammy Massie, FDA

Given recent high failure rates in clinical trials and advances in adaptive trial methodologies, the question arises whether the DMC should do more to increase the chance of a successful study. This could include selecting doses in adaptive dose-response trial, enriching or reducing one arm of a study or identifying a subset of study participants in which the study product appears to be efficacious. While statistical methods are available to minimize biases due to mid-stream changes to target population or sample size, questions remain how to minimize operational biases. A well appointed DMC may be in an unique position to advise the sponsor and keep the health authorities engaged so valuable resources can be saved in bringing a potentially lifesaving product to patients. Dr. Greg Campbell from the FDA and Dr. Scott Evans from Harvard University will discuss issues which are relevant to drug, device, diagnostic and biologics development and not be limited to any therapeutic area. The speakers will then join a panel of experienced statisticians including Dr. Janet Wittes from Stats Collaborative, Dr. Ram Suresh from Merck and Dr. Paul Gallo from Novartis for a discussion.

Evolving Role of DMCs
Scott Evans, Harvard University

Data Monitoring Committees in the 21st Century: A Regulatory Perspective
View Presentation View Presentation Gregory Campbell, Food and Drug Administration

Panel Discussion
Paul Gallo, Novartis Pharmaceuticals; Kannan Natarajan, Novartis Pharmaceuticals Corporation; Janet Wittes, Statistics Collaborative


GS2 Patient-Centered Outcomes Research and Health Economics Outcomes Research

2:15 PM - 3:45 PM
Grand Ballroom Salon 1

Organizer(s): Bruce Binkowitz, Merck, Sharpe, and Dohme; Hope Baskerville Knuckles, Abbott; Alan J. Menius, GlaxoSmithKline R&D; LaRee Tracy, FDA

Chair(s): Hope Baskerville Knuckles, Abbott

Demands have been placed to provide more information on the economic value and effectiveness of their products to patients, particularly relative to available alternatives. The impact of health care reform on the regulatory approvals and patients access to health care is unknown. An HEOR MD in device/diagnostics will discuss impact of these reforms. An industry statistician will provide an update to the 2011 FDA/PhRMA Biostatistics Leadership meeting concerning: Use observational data to conduct comparative effectiveness studies? Use historical/other data in a Bayesian framework? Progress a clinical program where subgroups of patients with different profiles of benefit/risk are suspected or known? How will the FDA be using the combined clinical trial database? The FDA is similarly focused on research efforts, which will explore existing patient-level data to identify subgroups for whom the benefit to risk is greatest as well as how to leverage new design strategies for estimating treatment effects in subpopulations and improving future trial designs. An FDA representative from the Regulatory Advancing Science Initiative will present a regulatory perspective.

HEOR in the Device and Diagnostic Industry
Donald B Chalfin, Abbott, HEOR Medical Director

Statistical Issues in Using Disparate Data Sources
View Presentation View Presentation Matthew D Rotelli, Eli Lilly and Co., ASA, DIA

Modernizing FDA – Advancing Regulatory Science and Driving Innovation in Medical Products and Devices
Vicki L Seyfert, FDA


Closing Remarks

3:45 PM - 3:50 PM
Grand Ballroom Salon 1