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Wed, Sep 23

SC1 Adaptive Designed Clinical Trials

8:00 AM - 12:00 PM
Presidential Ballroom

Instructor(s): Martin Posch, University at Vienna; Sue Jane Wang, CDER


SC2 Benefit: Risk Assessment

8:00 AM - 12:00 PM

Instructor(s): Scott Evans, Harvard

The monitoring and evaluation of benefit:risk is a fundamental element of clinical trials and drug, biologic, and device development. Regulators weigh the benefits and risks when evaluating drugs for approval, sponsors assess the benefit:risk profile of their drugs to aid development decisions, and data monitoring committees make recommendations regarding study conduct based on benefit:risk assessment during interim data analyses. Despite benefit:risk assessment lying at the heart of the development process, there is a need for a more systematic, creative, and informative approaches to evaluation. We discuss the challenges to benefit:risk assessment, evaluate elements of trial design and conduct that affect benefit:risk evaluation, present methods for analyses including within-patient analyses and potential for personalized medicine, and present ideas for reporting benefit:risk analyses. We discuss keys to improved benefit:risk assessment including detailed interactions between statisticians, clinicians, and other researchers.


SC3 Analysis of Longitudinal Studies with Missing Data

8:00 AM - 12:00 PM
Federal AB Room

Instructor(s): Diane Fairclough, UCHSC

This workshop will provide an introduction to the analysis of longitudinal studies with missing data. I will focus on 1) avoiding methods that assume that data are missing completely at random, and 2) methods for sensitivity analyses that can be considered when the data are suspected to be non-ignorable with an emphasis on the use of auxiliary/surrogate data. I will also address the practical issue of the statistical analysis plan in the environment of registration trials. After completing this workshop, participants will be able to: 1. Avoid method that assume that data are missing completely at random (MCAR) 2. Understand the value of auxiliary/surrogate data. 3. Choose between various strategies for sensitivity analyses when missing data are suspected to be non-ignorable. 4. Understand the challenges of developing a statistical analysis plan for studies with missing data. Participants should have some experience with mixed effects or hierarchal models. Diane Fairclough received her doctoral degree (DrPH) in Biostatistics from the University of North Carolina. She has held appointments at St. Jude Children's Research Hospital, Harvard School of Public Health, and AMC Cancer Research Center. She is currently a Professor in Department of Biostatistics and Informatics at the Colorado School of Pubic Health, University of Colorado Denver. She is a well know researcher in health-related quality of life and her interests include the design and analysis of longitudinal studies with missing data due to disease morbidity or mortality. She has over 160 peer reviewed publications and a published book Design and Analysis of Quality of Life Studies in Clinical Trials .


SC4 Cox Regression in Practice

8:00 AM - 12:00 PM
South American AB Room

Instructor(s): Brenda Gillespie, University of Michigan

This workshop will cover the basics of fitting and interpreting a Cox regression model and checking assumptions. It explains the Cox partial likelihood function as a tool to easily understanding time-dependent covariates, left-truncation, and the analysis of recurrent events. Examples using time-dependent covariates, stratified Cox models, and diagnostic methods will be presented. Problems of separation, and the generalized R-squared, will also be covered. SAS software will be used for most examples, and R-Excel will be introduced.


SC5 Special Topics in Survival Analysis

1:00 PM - 5:00 PM

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

The short course will target audience with basic background in survival analysis. We will discuss practical solutions to problems beyond usual cox-proportional hazards regressions. Topics will include evaluating and comparing survival models via prediction; calibrating subject-specific model-based (competing) risks prediction via establishing a risk scoring system and how to utilize the standard survival analysis techniques to analyze repeated measures data with informative missing in comparative clinical trials. If time permits, we will also discuss how to monitor clinical trials based on data simulation as an alternative to pre-specified stopping boundary for superiority and futility. Computer programs for all topics will be provided.


SC6 Bootstrap Methods and Permutation Tests

1:00 PM - 5:00 PM
South American AB Room

Instructor(s): Tim Hesterberg, Google

This workshop begins with a graphical approach to bootstrapping and permutation testing, illuminating basic statistical concepts of standard errors, confidence intervals, p-values and significance tests. We consider graphical and numerical diagnostic checks for the validity of traditional Gaussian-based inferences. We then broaden our scope to a wider variety applications, including cases where bootstrapping fails, and additional sampling methods. The emphasis is on practical applications, with occasional comments about the underlying theory.


SC7 Recent Advances I Bayesian Adaptive Methods for Clinical Tests

1:00 PM - 5:00 PM
Federal AB Room

Instructor(s): Peter Thall, MD Anderson

This half-day short course will cover some recent advances in practical Bayesian adaptive methods for clinical trial design and conduct. Attendees should have at least a Masters degree in statistics, or equivalent experience, and an understanding of elementary Bayesian concepts. Most of the methods are “hybrid” designs that combine conventional phases of clinical development or that deal with multiplicities in the treatment, the clinical outcome, or both. Each method will be illustrated by an actual oncology trial. As time permits, depending on the amount of time spent on questions during the lectures, topics will include: dose-finding based on efficacy and toxicity, patient covariate-specific dose-finding, jointly optimizing dose and schedule based on time to toxicity, choosing an optimal dose pair based on elicited utilities of (efficacy, toxicity) outcomes, accounting for heterogeneity in phase I/II and phase II trials, a doubly optimal adaptive group sequential design for phase III trials that uses Bayesian model selection, a design to compare two-component dynamic treatment regimes based on successive treatment failure times, and a two-stage select-and-test design based on posterior probabilities of two-dimensional parameter sets.


SC8 Data Monitoring Committees

1:00 PM - 5:00 PM
Presidential Ballroom

Instructor(s): Thomas Fleming, University of Washington; Janet Wittes, Statistics Collaborative, Inc.

The organization structure of many modern clinical trials include a Data Monitoring Committee (DMC),-also known as a Data Safety Monitoring Committees (DSMC) or an Independent Data Monitoring Committee (IDMC), charged with protecting the safety of the participants in the study and ensuring the integrity of the trial itself. The Committee performs these functions by monitoring the ongoing data from the trial for which it is responsible. This four-part course will present an overview of the role and function of these committees. We will start with theoretical considerations and move to very practical issues. Part 1 will focus on statistical aspects of the DMC. We will present basic statistical methodology underlying group sequential designs. We will discuss the construction of standard statistical boundaries for efficacy, definitions of use functions, and approaches to futility. Part 2 will move from the purely statistical aspect to the DMC itself. We will discuss the Committee’s roles and responsibilities. We will address the question of when a DMC is needed, what its charter should include, and how its meeting should run. Finally, we will describe the difference in cultures of DMCs in the private and public sectors. Part 3 will focus on some controversies surrounding DMCs: for example, how to define “independence”, who should present data to the DMC, whether the DMC should be masked or unmasked, and how the DMC should communicate its recommendations. Finally, Part 4 will address some practical issues faced by industry in setting up and managing a DMC. This Part will discuss such issues as how to schedule meetings, who should program the tables, what the DMC’s report should include, and how to ensure that data are sufficiently current to allow the DMC to make timely relevant recommendations.


Thu, Sep 24

PL1 Regulatory Issues in Global Harmonization of Clinical Studies

8:00 AM - 9:45 AM
Presidential/Congressional Ballrooms

Organizer(s): Bruce Binkowitz, Merck, PhrMa; Hope Knuckles, Abbott Laboratories, NIC-ASA; Richard Kotz, FDA-OSB/CDRH

Chair(s): Hope Knuckles, Abbott Laboratories, NIC-ASA

This will be a general session to present how the international health regulatory requirements impact efforts towards global harmonization of clinical studies. Obtaining approvals from multiple oversight regulators results in issues that impact the design and analysis of a clinical study and therefore statisticians should be aware of these differences. This session will apply to all areas of oversight, such as drugs, biologics, medical devices and foods. There will be three speakers, presenting an overview of Global Harmonization and regulatory and operational issues from the FDA, Academic, and Industry perspective.

Welcome and Introduction
View Presentation View Presentation Carmen Mak, Schering Plough; Tammy Massie, FDA

Global Harmonization - Global Harmonization
View Presentation View Presentation Murray Lumpkin, Deputy Commissioner Internal Affairs, FDA

Global Harmonization – Ethical and Scientific Considerations
View Presentation View Presentation Robert Califf, Duke University Translational Medicine Institute

Global Harmonization – Global Regulatory and Clinical Affairs for Drug Development
View Presentation View Presentation Mark Bach, Merck


PL2 The World is (almost) Flat: Statistical Considerations as Clinical Development Goes Global

10:00 AM - 11:30 AM
Presidential/Congressional Ballrooms

Organizer(s): Yoko Adachi, U.S. Food and Drug Administration; Brent Burger, Vislation; Margaret Minkwitz, AstraZeneca

Chair(s): Peter Ouyang, Celgene Corporation

Many statistical issues related to the conduct of multi-regional clinical trials (MRCTs) for the development of medical products have been identified at statistical and clinical development conferences in recent years. A sample of these issues include the definition and assessment of regional consistency, sample size requirements that enable meaningful assessment, the impact on power calculations given regional differences in treatment effect, the statistical interpretation of the overall conclusion with or without satisfactory regional consistency, and inconsistent regulatory requirements on clinical endpoints. This session will feature assessments of existing approaches that address these issues as well as new approaches. This session will apply to areas including drugs, biologics, and medical devices.

Statistical Issues in Multiple-Regional Clinical Trials
View Presentation View Presentation Robert O'Neill, FDA, CDER

Assessing Consistency of Treatment Effects in Multiple-Regional Clinical Trials: A Systematic Review and Case Study
View Presentation View Presentation Joshua Chen, Merck

Implication of Asian Studies in Simultaneous Global Clinical Trials
View Presentation View Presentation Masahiro Takeuchi, Kitasato University, Japan

Statistical Considerations for Clinical Development in China
View Presentation View Presentation William Wang, Merck Sharp &Dohme Ltd., China


RT1 Roundtable: Design and Implementation of Clinical Studies - Thursday

11:30 AM - 12:45 PM
Federal AB Room

Power and Sample Size for Multiple Endpoints
Jie Chen, Abbott Labs

Medical Device Non-Inferiority Trials
Phyllis Silverman, FDA

Multiplicity Issues in Insomnia trials
Tristan Massie, FDA

Use of sample size re-estimation in confirmatory trials
Jeff Maca, Novartis Pharmaceuticals

Assessing confidence of go/no-go decision in clinical trial program
Guanghan (Frank) Liu, Merck Research Laboratories

#1 Utility and use of PD biomarkers for making development decisions in early phase oncology clinical
Jane Fridlyand, Genentech

IVRS kit supply strategies for blinded randomized clinical trials
Ron Yu, Genentech

Implementation of Adaptive Trials
Kenneth Liu, Merck; Eva Miller, ICON Clinical Research

Global Trial Harmonization Issues
Bruce Binkowitz, Merck, PhrMa

How to Consolidate Information from Multiple Endpoints in a Dose Finding Study
Fei Wang, Boehringer-Ingelheim

Improving the Quality of Clincal Trials
Vance Berger, NIH

Assessing Clinical Significance - Implications for Protocols and Clinical Study Reports
Michael Friedman, Genzyme

Efficacy Interim Analysis in Futility/Interim Analysis
Edmund Luo, Merck & Co.

Adaptive Designs in the Real World
Steven Gilbert, Rho, Inc.

Statistical Issues in Solid Tumor Response Assessment
Mithat Gonen, Memorial Sloan-Ketterig Cancer Center; Rajeshwari Sridhara, FDA

Placebo Response in CNS Clinical Trials
Pilar Lim, Johnson & Johnson PRD; Isaac Nuamah, Johnson & Johnson PRD

Improving Clinical Trials in Imaging: endpoints and data collection
Brandon Gallas, FDA, CDRH

Selection of primary analysis sets for trials with non-inferiority/superiority tests
Boguang Zhen, FDA

Switch from Rx to OTC: Design and Analysis Issues
Shiling Ruan, Food and Drug Administration


RT2 Roundtable: Anaylsis of Clinical Trials - Thursday

11:30 AM - 12:45 PM
Senate Room

#1 Cross-over and follow-up issues in time-to-event endpoints
John Zhong, Human Genome Sciences

#2 Opportunities to Apply Bayesian Methods in Phase III of Drug Development
Melissa Spann, Eli Lilly & Company

#3 Adequacy of Patient followup and sensitivity analysis in the presence of missing data for PFS in oncology trials
Laura (Hong) Lu, FDA/CDER/OB/DB5

#4 Some issues in oncology trials with Progression-free survival (PFS) and Overall Survival (OS) as endpoints
Gang Chen, Johnson & Johnson; Xiaoping (Janet) Jiang, FDA; Xiaolong Luo, Celgene

#5 Longitudinal Analysis, Missing Data and Assessment of Durability of Treatment Effect
Dana L. Creanga, Independent Consultant

#6 Is center (or region) pooling necessary to avoid excluding patients in a stratified analysis by center (or region)?
Zhengning Lin, Eisai Medical Research, Inc.

#7 Surrogate Markers in Oncology
Aloka Chakravarty, FDA, CDER

#8 Handling Missing Values
Kooros Mahjoob, FDA/CDER/OTS/OB/DB1

#9 Analysis of Patient-Reported Outcomes in Oncology Clinical Trials
Yuan-Li Shen, FDA; Yihua (Mary) Zhao, Boehringer Ingelheim Pharmaceuticals, Inc.

#10 Monitoring Safety During Drug Development
Anita Abraham, FDA; Jane Porter, Millennium Pharmaceuticals

#11 The Independent Statistician - More than the Custodian of the Treatment Codes
Heidi Christ-Schmidt, Statistics Collaborative, Inc.

#12 Proactive and Systemic Approaches for the Planning, Evaluation and Presentation of Safety Data
Seta Shahin, Amgen

#13 Follow up from the Meta Analysis with a Focus on Safety Session
Irmarie Reyes, Genentech


RT3 Roundtable: Center Specific - Thursday

11:30 AM - 12:45 PM
Statler AB Room

#1 Typing Food-Borne Bacteria Using Microarrays, Repeats, and SNPs
Errol Strain, Center for Food Safety and Applied Nutrition

#2 Comparing statistics used by CVM and CVB
David Whiteman, Intervet

#3 Deciding to Transform Data
Veronica Taylor, FDA

#4 Baseline Value in Repeated Measures Analysis
Scott Miller, FDA/CDRH

#5 Concerns and Issues of IVD Post approval Studies
Songbai Wang, Ortho-clincial Diagnostics, a J&J Company

#6 The Statisticians Role in Safety Evaluation
Amelia Dale Horne, FDA


RT4 Roundtable: CMC/Early Clinical - Thursday

11:30 AM - 12:45 PM
New York Room

#1 Assessing the Quality of Hybridized RNA in Affymetrix GeneChips
Meijaun Li, FDA, CDRH

#2 Sharing experiences with use of biomarkers in clinical trials
Jitendra (Jeetu) Ganju, Amgen, Inc.

#3 Failure-Time Mixture Models for Evaluating Efficacy in the Presence of a Biomarker
Kallappa M. Koti, Food & Drug Administration

#4 The Promises and Challenges of Biomarker Utility in Developing Drugs and Obtaining Regulatory Approval
Deepak Khatry, MedImmune

#5 On Clinical Utility and Biomarkers
Maha Karnoub, Wyeth Research


RT5 Roundtable: Other Technical/Statistical Topics - Thursday

11:30 AM - 12:45 PM
Massachusetts Room

#1Value of Assessing the Impact of Treatment on Healthcare Resource Utilization
Shannon Allen Ferrante, Merck & Co., Inc.

#2 Applied Adaptive Designs - Software in Use (What is available & how are people using it)
Tad Archambault, VirtuStat, Ltd.

#3 Emerging Methods and Research Directions for AE Identification in SRS: Data Mining and More
Robert Ball, FDA; Marianthi Markatou, FDA

#4 How can statisticians contribute more actively to ensure data quality?
Yunfan Deng, FDA


RT6 Roundtable: Professional and Personal Development - Thursday

11:30 AM - 12:45 PM
Ohio Room

#1 Tips on steeking for hand painted yarn projects, bring a project and questions or tips to share
Margaret Minkwitz, AstraZeneca

#2 Communication skills for New statisticians in Industry
Sibabrata (Raja) Banerjee, Schering Plough Research Institute; Venkata Goteti, Schering Plough Research Institute

#3 Professional Development: Effective Communication
Kit Roes, Schering Plough, Netherlands

#4 Work/Life Balance – Alternatives to the 36-hour day
Sonya Vartivarian, Mathematica Policy Research, Inc.


CS1a Practical Considerations of Futility Analysis and Regulatory Case Sharing on Interim Analysis

12:45 PM - 2:00 PM
Presidential Ballroom

Organizer(s): Edmund Luo, Merck & Co.; Vivian Yuan, FDA

Chair(s): Xiaolin Wang, Genentech

The primary objective of this session is to have a rich discussion of the practical considerations on futility analyses and interim efficacy analyses with key stake holders. This session will focus on real examples and lessons learned rather than theoretical aspects of futility or interim efficacy analyses. This session consists of two 20-minute oral presentations. One speaker from industry will focus on futility analyses from a risk and benefit perspective and one speaker from the FDA will share some examples and bring up thought-provoking questions as the prelude for the panel discussion. The presentations are followed by a 35-minute panel discussion with representations of industry, FDA, academia and DMCs. The target audience includes statisticians from industry, FDA, academia, and DMCs, as well as other key stake holders impacted by the use of interim efficacy or futility analyses.

Futility Analysis: Practical Considerations
View Presentation View Presentation Benjamin Trzaskoma, Genentech

Case Sharing on Interim Analysis
View Presentation View Presentation Jialu Zhang, FDA

Panel Discussions of Practical Considerations of Futility Analysis
Keaven Anderson, Merck & Company; Susan Ellenberg, University of Pennsylvania; Scott Evans, Harvard; John Lawrence, FDA; Benjamin Trzaskoma, Genentech; Jialu Zhang, FDA


CS1b Survival Analysis – Issues Related to Follow-up in Time to Event Endpoints

12:45 PM - 2:00 PM
Congressional Room

Organizer(s): Zhenming Shun, sanofi-aventis; Qiang (Casey) Xu, FDA-CDER; John Zhong, Human Genome Sciences

Chair(s): Pabak Mukhopadhyay, Novartis Oncology

Time-to-event endpoint, such as overall survival, is often used to evaluate efficacy of new drug products in different therapeutic areas. However, the true survival effect of an experimental treatment often gets confounded when patients cross-over from a controlled treatment regimen to the experimental drug. In this session, statistical methodologies for time-to-event analysis in “cross-over” setting will be presented, together with some examples of their applications in drug development. Regulatory suggestions for the design of future studies will be discussed.

Correcting for Non-Compliance in Randomized Trials
James Robins, Harvard School fo Public Health

Sensitivity Analysis for Treatment Drop-in in Oncology Clinical Trials
View Presentation View Presentation Alan Rong, Amgen

View Presentation View Presentation Rajeshwari Sridhara, FDA

Discussant(s): Rajeshwari Sridhara, FDA


CS1c Food Safety and Validation Method

12:45 PM - 2:00 PM
South American AB Room

Organizer(s): Geraldine E. Baggs, Abbott Nutrition R&D - Statistical Services; Qian Graves, FDA

Chair(s): Curtis Barton, CFSAN/FDA

Characterization of bacterial contamination in a food product involves identifying the type of bacteria and quantifying the amount present in the sample. Pathogen typing is often performed using DNA based assays, while the concentration of bacteria in a sample can be estimated using techniques like serial dilution tests. The presentations in this session provide examples of how to type bacterial food pathogens using microarrays and SNPs, and also how the concentration of living microbes in a sample can be calculated using the most probable number (MPN). Finally, with the European adoption of (CEN ISO 16140), a uniform protocol for the validation of proprietary microbiology methods is feasible. The current AOAC International Official Methods of Analysis process as well as the AOAC Research Institute; Performance Tested protocols will be discussed and compared to the ISO16140 protocol.

Typing Food-Borne Bacteria Using Microarrays and SNPs
View Presentation View Presentation Errol Strain, Center for Food Safety and Applied Nutrition

Validated Methods for US and International Trade
View Presentation View Presentation Robert E. Koeritzer, 3M Food Safety

Serial Dilutions
View Presentation View Presentation Robert Blodgett, Center for Food Safety and Applied Nutrition


CS1d Concepts in the Planning and Analyses of Target Animal Safety Studies for Veterinary Products

12:45 PM - 2:00 PM
Pan American Room

Organizer(s): Anna Nevius, FDA

Chair(s): Stephine Keeton, FDA

Focusing on safety studies in veterinary clinical trials, this session addresses design issues and analysis problems. This session will begin with an overview of safety studies, current practices and issues from a regulatory, academic and industry viewpoint. These presentations will set the stage for the hands-on discussions to follow. Questions will be posed and each panel member will provide a short response to facilitate audience participation. Vigorous interaction with the audience is expected and encouraged.

An Overview of Safety Studies
View Presentation View Presentation Veronica Taylor, FDA

Current Practices in Safety Studies
View Presentation View Presentation Louis Luempert, Novartis Animal Health

Theoretical Considerations in Safety Studies
George Milliken, Milliken Associates/KSU


CMC1 CMC Panel Discussion Series I: Shelf Life Determination

12:45 PM - 2:00 PM
California Room

The PQRI Stability Shelf Life Working Group has proposed a strategy for defining shelf life based on a percentile of the distribution of stability measurements for a pharmaceutical product. While a former FDA guidance and ICH have proposed the use of a one sided 95% confidence interval on the mean, the PQRI initiative has opened the door to considering other conventions based on tolerance intervals. In this session the PQRI SSLWG will present their proposal for utilizing tolerance intervals to define shelf life, and the panel will discuss the merits and risks of this versus the historical approach.


CS2a Multiplicity Adjustment in Clinical Trials with Multiple (Primary and Secondary) Endpoints: Issues and Concerns

2:15 PM - 3:30 PM
Presidential Ballroom

Organizer(s): Jie Chen, Abbott Labs; Kooros Mahjoob, FDA/CDER/OTS/OB/DB1; Lanju Zhang, MedImmune, Inc.

Chair(s): Sonia M. Davis, Quintiles

Issues associated with multiple testing in maintaining the family-wise type I error rate are long standing. This session will address some key issues regarding multiplicity adjustment methods in complex clinical trial settings, e.g., multiple doses with multiple primary and/or secondary endpoints. Some frequently used multiplicity-adjustment methodologies may be overly restrictive and hence impractical. Speakers will evaluate the applicability of existing methods, and propose alternative methods which may be less restrictive from a regulatory and industry perspective. The session will have three presentations, from academia, industry, and the FDA, followed by Q & A including comments or discussions from the audience.

Partition Decision Paths to Test for Efficacy with Multiple Endpoints
View Presentation View Presentation Jason Hsu, Ohio State Unviersity, Department of Statistics

Handling Multiplicity Issues in Primary and Secondary Endpoints
View Presentation View Presentation Ivan Chan, Merck Research Laboratory

Challenges to Multiple Comparison Problems in Regulatory Applications
View Presentation View Presentation H.M. James Hung, FDA/CDER/OTS/OB/DB1


CS2b PK/PD Model-based Drug Development

2:15 PM - 3:30 PM
Congressional Room

Organizer(s): Li Chen, Amgen; Harry Yang, MedImmune

Chair(s): Yaning Wang, U.S. Food and Drug Administration, CDER

Model-based drug development is the new paradigm outlined in the Critical Path Initiative published by the FDA. As the core of this new paradigm, pharmacokinetic/pharmacodynamic (PK/PD) models serve as a powerful tool to accumulate knowledge gained during drug development and provide quantitative justification for many key decisions along the drug development process. PK/PD models bridge data from animals, healthy subjects and patients through mechanism-based pharmaco-statistical models. In this session, case studies will be presented to demonstrate the opportunities and challenges of utilizing PK/PD models to predict first-time-in-man dose based on preclinical data, target reasonable dose range based on biomarker data from early phase clinical trials, and optimize dosing regimen for phase 3 trials based on phase 1/2 data. The session is targeted towards the general audience of the preclinical and clinical statisticians and PK/PD modelers involved in the decision making at any stage of clinical development of the drug.

Using PK-PD modeling to support selection of First-Time-In-Man dose and Phase I Trial Design
View Presentation View Presentation Liang Zhao, MedImmune

Exploring Biomarker/Pharmacokinetics Relationships in Early Clinical Studies to Enable Good Decisions
View Presentation View Presentation Mike Hale, Amgen

Leveraging Prior Knowledge to Drive Drug Development Decision
View Presentation View Presentation Christoffer Tornoe, U.S. Food and Drug Administration


CS2c Recent Issues in CNS Drug Development

2:15 PM - 3:30 PM
South American AB Room

Organizer(s): Craig Mallinckrodt, Eli Lilly; Tristan Massie, FDA

Chair(s): Susan Huyck, Schering-Plough

This session will take an applied, example-oriented approach to examine current statistical issues in the following topics of broad interest: multiplicity, patient reported outcomes, and missing data. Examples will primarily come from the CNS (Central Nervous System) clinical research arena but will be applicable to other disease areas as well. The three speakers will present on: new considerations for multiplicity problems in insomnia, an NIH Roadmap initiative project related to patient reported outcomes, and approaches to missing data due to dropout or non-compliance with examples in the CNS area, respectively.

Design of Insomnia Drug Trials and Related Statistical Issues
View Presentation View Presentation Kun Jin, FDA

Science of Endpoint Selection and Patient Reported Outcomes (PROs)
View Presentation View Presentation Laura Lee Johnson, National Institutes of Health

Drop-out and Related Issues in CNS trials
View Presentation View Presentation Suna Barlas, Wyeth


CS2d Vet Medicine I – Design and Analysis

2:15 PM - 3:30 PM
Pan American Room

Organizer(s): Diane Sweeney, Intervet/Schering-Plough Animal Health

Chair(s): Todd Blessinger, FDA, CVM

The theory and applications involved in analyzing data from veterinary medicine studies will be discussed. The main focus of the presentations will be on the analysis of binomial and count variables. These kinds of variables often occur in drug effectiveness studies and studies for determining the presence of disease in animal populations. Generalized linear mixed models (GLMMs) are frequently used in these cases because random effects are often present in the study designs. To be discussed are issues involved with GLMMs such as overdispersion due to clustering; negative covariance estimates and their effects on inference; low prevalence of disease, resulting in a shortage of informative data; determining the appropriate statistic to be used to estimate efficacy; and investigating the appropriateness of GLMMs in certain studies. The theoretical implications of these phenomena will be discussed and examples provided in the context of animal pharmaceutical research and the investigation of animal diseases such as E. coli and Salmonella.

On the Problem of Negative Variance Component Estimates in Mixed Models
View Presentation View Presentation Walter Stroup, University of Nebraska, Lincoln

Challenges Associated with E. coli O157 and Salmonella Studies Conducted in Real-World Settings
View Presentation View Presentation Guy H. Loneragan, West Texas A&M University

Study Design Considerations in Veterinary Biologics
View Presentation View Presentation Brian J. Fergen, U.S. Department of Agriculture, Animal and Plant Health Inspection Service


CMCII CMC Panel Discussion Series II: Method Validation and Transfer

2:15 PM - 3:30 PM
California Room

A total error approach has been proposed as the basis for method validation and transfer, which is based on the premise that industry and regulators wish to guarantee that a suitably high proportion of the individual measurements performed in routine practice will be ”sufficiently close” to the unknown true value of the sample. This is in contrast to ICH and USP which focus on parameters of a method such as accuracy and precision. In this panel Boulanger will outline his proposed strategy for a total error approach to method validation and transfer, while the panel will discuss this in the context of other routinely applied procedures.


CS3a Adaptive Designs: Theory and Methods

3:45 PM - 5:00 PM
Presidential Ballroom

Organizer(s): Yeh-Fong Chen, FDA; Weili He, Merck Pharmaceuticals

Chair(s): Jeff Maca, Novartis Pharmaceuticals

An adaptive design, by definition, entails the modification of the trial design, adjusting to the possibility of revealing the accrued data before the end of the trial. Thus, a serious prospective plan is crucial to prevent jeopardizing the trial integrity. Because the adaptation of the trial designs may extend over almost all stages of the trials, a prospective plan would normally include the considerations of patient allocation, sample size planning, stopping rules for efficacy and futility, and the final decision. In this session, a plan is to invite speakers who develop methodologies for problems encountered in different phases of clinical trials. Topics will include the adaptive selection of doses used for confirmatory trials, two-stage adaptively designed trials, sample size re-estimation after interim analyses as well as the discussion of logistic, operational and regulatory issues. The main focus of these presentations will be on the development of theories and methods for clinical trials. All developed methodologies discussed in the session have been utilized in real clinical trials and their applications to some trial examples will be demonstrated.

Adaptive Patient Enrichment Designs in Therapeutic Trials
View Presentation View Presentation Sue Jane Wang, FDA

Type I Error Rate Control in Adaptive Designs for Confirmatory Clinical Trials withTtreatment Selection at Interim
View Presentation View Presentation Martin Posch, University at Vienna

Adaptive Dose Ranging Studies: An Update from the PhRMA Working Group
View Presentation View Presentation Jose Pinheiro, Novartis Pharmaceuticals

Discussant(s): Keaven Anderson, Merck & Company


CS3b Quantitative Approaches to Decision Making in Clinical Development

3:45 PM - 5:00 PM
Congressional Room

Organizer(s): Li Chen, Amgen; Jane Fridlyand, Genentech; Shiling Ruan, Food and Drug Administration; Stephen Wilson, FDA/CDER

Chair(s): David Li, Wyeth Research Division

The development of a drug/device often involves multiple clinical trials in different stages. It is critical to the success of the overall development program to accurately evaluate the information from current and prior stage of the clinical trials and to make informative decisions for future developments. This session will discuss quantitative approaches to tackle the challenges of decision making under uncertainty in both earlier and later stage of the clinical development, including regulatory decision making. The talks will consist of discussions on metrics setup and decision criteria at different stages, early phase decision making to inform the choice of safe and effective dose, go/no-go decisions to phase III/pivotal trial and regulatory decision making in medical device evaluation. The session encompasses a broad range of decision making challenges in the clinical trial arena, and will be suitable for a general audience.

Choosing right metrics to enable sound decisions
View Presentation View Presentation Christy Chuang-Stein, Pfizer

If I Were a VP or a VC…
View Presentation View Presentation Cong Chen, Merck Research Laboratories

Using Decision Analysis to Regulate Medical Devices
View Presentation View Presentation Telba Irony, FDA


CS3c Preserving Integrity of Clinical Trials: Drug Supply, Patient Randomization and Data Verification

3:45 PM - 5:00 PM
South American AB Room

Organizer(s): Jane Fridlyand, Genentech; David Li, Wyeth Research Division; Karen Qi, FDA/CDER; Stephen Wilson, FDA/CDER

Chair(s): Daphne T.Y. Lin, FDA/CDER

The Goal of this session is to discuss the statistician’s role, statistical challenges, and strategies to assess and preserve integrity of clinical trials. Three special topics are presented: (1) A discussion of the risk of the partial unblinding of the patients when standard drug supply approaches are used, followed by the presentation of the alternative supply strategies; (2) A demonstration with the case example of how different statistical tests may lead to non-concordant conclusions for the studies that use minimization algorithm to allocate subjects to the treatment arms; (3) A discussion of two recent NDAs/BLAs submission to illustrate the statistician’s and other members’ of the review team role verifying data which appear irregular or too good to be true. This session will be useful for statisticians who are involved in design and analysis of clinical trials.

Kit Supply Algorithms to Protect the Integrity of Blinded Randomized Clinical Trials
View Presentation View Presentation Ron Yu, Genentech

Dynamic Allocation: A Case Study
View Presentation View Presentation Lisa Kammerman, FDA/CDER

A Regulatory Perspective of the Statistician’s Role in the Data Verification and Inspection Process
View Presentation View Presentation Fraser Smith, FDA/CDER


CS3d Aspects of Missing Data Unique to Medical Device Trials

3:45 PM - 5:00 PM
Pan American Room

Organizer(s): Terri Johnson, FDA/CDRH; Peter Lam, Boston Scientific

Chair(s): Scott Miller, FDA/CDRH

Clinical trials conducted to evaluate the performance of medical devices can differ in fundamental ways from the more traditional trials conducted to evaluate pharmaceutical agents. This session will focus on aspects of clinical trials for medical devices that can lead to missing data which may not be as common in trials for pharmaceuticals. The target audience for this session is individuals involved in the design, conduct, analysis, or evaluation of such trials. Beyond briefly introducing the importance of the topic, the speakers will provide case studies and practical advice on handling missing data from both an industry and FDA perspective.

Missing Data in Orthopedic Implant Clinical Trials: A case for Sensible LOCF (Last Observation Carried Forward)
View Presentation View Presentation Jianxiong (George) Chu, FDA

The Problem of Missing Data in Medical Device Trials
View Presentation View Presentation

The Missing Details of Your Missing Data Analysis Plan
View Presentation View Presentation Alvin VanOrden, FDA


CMCIII CMC Panel Discussion Series III: Design Space Definition

3:45 PM - 5:00 PM
California Room

A Bayesian approach has been proposed for the ICH Q8 definition of design space by Peterson and Stockdale. Measurement and prediction are coupled with reliability to define factor space contours which relate to the probability of an out of specification (OOS) result. In this session Peterson will outline the proposed strategy for defining design space based on the posterior probability of an OOS result, while the panel will discuss this and other potential definitions of reliability.


Fri, Sep 25

CS4a Meta Analysis with a Focus on Safety

8:00 AM - 9:15 AM
Presidential Ballroom

Organizer(s): Patience Ajongwen, Johnson & Johnson; Jesse Berlin, Johnson & Johnson Pharmaceutical Research and Development; Irmarie Reyes, Genentech

Chair(s): Yu-te Wu, FDA

Typically clinical trials are designed to have adequate statistical power to detect clinically important effects of a new treatment on an efficacy endpoint. While such trials may be adequate to demonstrate efficacy and safety regarding frequently-occurring AEs, they are often inadequate to detect infrequent but potentially serious safety signals. This session will focus on meta-analysis methods and interpretation through real case examples and computer simulation. It will also highlight some of the challenges for identifying and evaluating safety signals. This session will be useful for all statisticians in attendance at the FDA/Industry meeting regardless of their area of expertise based on disease or indication studied. Statisticians that support products that are submitted to all 6 centers within the FDA should benefit from this session.

Meta Analysis of Stroke Rates using Patient Level Data in Age-Related Macular Degeneration in Patients treated with Ranibizumab
View Presentation View Presentation Steven Francom, Genentech

Current Status of Drug-Eluting vs Bare-Metal Stents: Interpreting the Data
View Presentation View Presentation Zhong Yuan, Johnson & Johnson

Key Issues in Meta-Analysis with Applications to Safety Data
View Presentation View Presentation Richard Forshee, U.S. Food and Drug Administration


CS4b Views on Integrated Summary of Effectiveness and Integrated Summary of Safety: From FDA and Industry Perspective

8:00 AM - 9:15 AM
Congressional Room

Organizer(s): Patrick Liu, UCB; Kooros Mahjoob, FDA/CDER/OTS/OB/DB1

Chair(s): Jingyee Kou, FDA/CBER/OBE/DB/VEB

The objective of this session is to discuss, from the FDA and industry perspective, the need for and utility of inclusion of Integrated Summary of Effectiveness (ISE) and Safety (ISS) in the NDA/BLA submission based on recent draft guidance released for public comments in August 2008. The target audience will be the FDA multi-discipline reviewers as well as industry clinician and statistician who are either preparing or reviewing the ISE and ISS reports. The session includes two 15-minute presentations by Howard D. Chazin, M.D., from FDA; and Mary E. Nilsson, a statistician from Eli Lily, followed by a 45 minutes panel discussion. The 6-member panel consists of four statisticians and three clinicians from CDER, CBER, and industry. The panel discussion will address 6 key questions, provided to the panel prior to the workshop, as well questions rose by the audience during the session.

Updates on the Guidances for Industry: Integrated Summaries of Effectiveness and Safety
View Presentation View Presentation Howard D. Chazin, FDA/CDER/OND

Integrated Summary of Effectiveness/Safety: Statistical Implementation Suggestions
View Presentation View Presentation Mary E. Nilsson, Eli Lilly & Company

Panel Discussion
View Presentation View Presentation Howard D. Chazin, FDA/CDER/OND; Nisha Jain, FDA/CBER; Jessica Kim, FDA/CBER; Mary E. Nilsson, Eli Lilly & Company; George Rochester, FDA, CDER; Konrad Tomaszewski, Pfizer


CS4c Endpoint Issues in Oncology Trials

8:00 AM - 9:15 AM
South American AB Room

Organizer(s): Sudeep Kundu, Sanofi-Aventis; Laura (Hong) Lu, FDA/CDER/OB/DB5; Pabak Mukhopadhyay, Novartis Oncology

Chair(s): Mark Rothmann, FDA

The goal of many phase 3 clinical trials is to obtain a statistically reliable evaluation of the benefits and the risks for an intended use of an experimental agent. There are several challenging and often controversial issues which arise in oncology phase 3 clinical trials. These issues include (i) the definition of the endpoint, (ii) challenges in surrogate endpoints, (iii) criteria for sizing the trial, (iv) trial monitoring, (v) loss to follow-up and censoring rules, (vi) concerns when patients in a control arm can cross-in at progression to the trial’s experimental therapy when it has not yet been established to be effective “rescue” treatment, and (vii) the robustness of the results. In this session experts from academia, industry and government will give presentations that discuss many or all of these issues.

Issues in Using ‘Progression-free Survival’ when Evaluating Interventions in Oncology
View Presentation View Presentation Thomas Fleming, University of Washington

Some Statistical Issues and Misunderstandings in the Assessment of PFS
View Presentation View Presentation Kevin J. Carroll, Astra Zeneca Pharmaceuticals

Use of blinded independent central review for auditing purposes
View Presentation View Presentation Lori Dodd, National Institute of Allergy and Infectious Diseases


CS4d Statistical Issues for Diagnostic Devices

8:00 AM - 9:15 AM
Pan American Room

Organizer(s): Patience Ajongwen, Ortho-Clinical Diagnostics; Rong (Rona) Tang, FDA/CDRH

Chair(s): Vicki Petrides, Abbott Laboratories

Much time is spent planning and preparing for studies in the pre-clinical and clinical phases of diagnostic device development. Could some of these studies be combined for a meta-analysis to better understand a product? How should one address the heterogeneity of the studies when performing a meta-analysis? What kinds of studies should be conducted and how should performance be measured once the device is on-market? This session will attempt to answer these and other questions through presentations on meta-analysis and post-approval studies for diagnostic devices.

n-Market Statistical Support
Patrick Meyers, Abbott Laboratories

Meta-analysis for Diagnostic Devices
View Presentation View Presentation Martin Ho, FDA/CDRH

Heterogeneity in Meta-Analysis of Diagnostic Test Accuracy
View Presentation View Presentation Donna McClish, Virginia Commonwealth University


CS5a Longitudinal Analysis, Missing Data and Assessment of Durability of Treatment Effect

9:30 AM - 10:45 AM
Presidential Ballroom

Organizer(s): Phillip Dinh, FDA; Yongman Kim, FDA; Pat O'Meara, Pat O'Meara Associates, Inc.; Gosford Sawyerr, Purdue Pharma L.P.

Chair(s): Greg (Guoxing) Soon, FDA

In many clinical trials, data are obtained on several measurements over time, and a primary endpoint may be specified for inferential purposes. Efficacy or clinical benefit may be established in terms of a metric and/or statistical method based on all time-points, or on some function of time-points, e.g., final measurement. To properly assess efficacy or clinical benefit, missing data due to early terminations must not be ignored, as they may be related to the response to the treatment modalities under study (e.g., dropout due to cure, or due to a treatment related adverse event or treatment failure). This session discusses some of the statistical challenges that arise when assessing durability of treatment effect using longitudinal data with modifications of therapy along the way and/or with varying degrees of missingness. For example, in some settings, a time to event approach is used, (e.g., time to treatment failure) whereas in others, a general linear model (e.g., mixed effects analysis) is employed. Some of the traditional ways of assessing efficacy and durability in these settings will be discussed, as well as newer ideas related to causal inference, and some methods for evaluating and correcting bias in the presence of informative dropout.

Issues in Assessment of Durability of Success in HIV Clinical Trials
View Presentation View Presentation Victor DeGruttola, Harvard School of Public Health

A Bias Correction in Testing Treatment Efficacy under Informative Dropout in Clinical Trials
View Presentation View Presentation Fanhui Kong, FDA

Defining and Evaluating Bias in Longitudinal Trials with NMAR Missing Data
View Presentation View Presentation Ronald W. Helms, Rho Inc. and UNC

Discussant(s): Tom Permutt, FDA


CS5b Design and Analysis for Non-inferiority Trial: A Practical Perspective

9:30 AM - 10:45 AM
Congressional Room

Organizer(s): Terri Johnson, FDA/CDRH; Misook Park, FDA; Yuan-Li Shen, FDA

Chair(s): Gang Chen, Johnson & Johnson

Design and analysis of non-inferiority trial face many challenging issues. In a situation where a placebo-controlled trial is not feasible, a non-inferiority trial is conducted using active-control with certain underlying assumption, such as the constant effect of control relative to placebo across studies or similar assay sensitivity in drug clinical trial. Use of intent-to-treat population in clinical trial maintains the integrity of the randomization and generally known to be a conservative analytic approach; however, such conservativeness may not be true for the non-inferiority. Furthermore, the effect from a poor study conduct may make the study arms too similar to reject the non-inferiority. The analysis methods in the non-inferiority trial can also impact the trial size and the overall chance of success. In this session experts from academics, industry, and government will give presentations and discussion on these issues that often occur in practice.

Covariate-adjusted Putative Placebo Analysis in Active-controlled Clinical Trials
View Presentation View Presentation Zhiwei Zhang, DESPR/NICHD/NIH

A Case Study for The Design and Conduct of Non-Inferiority Clinical Trials
View Presentation View Presentation Valerie Durkalski, Medical University of South Carolina

Panel Discussion
Kevin J. Carroll, Astra Zeneca Pharmaceuticals; Thomas Fleming, University of Washington; Mark Rothmann, FDA


CS5c Bayesian Methods throughout the Lifecycle of Medical Products

9:30 AM - 10:45 AM
South American AB Room

Organizer(s): Andrew Mugglin, University of Minnesota; Yunling Xu, CDRH/FDA; Jeffrey Zhang, Schering Plough

Chair(s): Brenda Gaydos, Eli Lilly

What are the potential applications of Bayesian methods throughout the lifecycle of medical products? This session will cover Bayesian adaptive design in a phase II biologics development, relevant frequency calculations for Bayesian design in medical device trials and detection of safety signals from routinely collected adverse event data in drug clinical trials.

Maximally Flexible Bayesian Designs in Randomized Clinical Trials
View Presentation View Presentation Frank Harrell, Jr., Vanderbilt University

Bayesian methods in the premarket approval of medical devices
View Presentation View Presentation Gerry W. Gray, FDA, Center for Devices and Radiological Health

Bayesian Hierarchical Modeling for Detecting Safety Signals in Clinical Trials
View Presentation View Presentation Bradley P. Carlin, University of Minnesota; Haijun Ma, Amgen; H. Amy Xia, Amgen, Inc.


CS5d Statistical Issues in Vaccine Clinical Trials

9:30 AM - 10:45 AM
Pan American Room

Organizer(s): Kerry Go, Sanofi Pasteur; Allen Izu, Novartis Vaccines

Chair(s): Jingyee Kou, FDA/CBER/OBE/DB/VEB

In this session, three topics from vaccine clinical trials will be presented. The first topic will be presented by Dr. Bernhard Klingenberg on methods for generating simultaneous confidence bounds for relative risks in multiple comparisons to control. The second topic presented by Dr. Robert Kohberger concerns the practical issues in vaccine interim analysis. He will try to address some of the issues such as “what does ‘stop’ really mean?” This will be followed by Dr. Karen Goldenthal who will discuss issues on selection of secondary endpoints in vaccine efficacy trials with examples. She will bring a clinical perspective to challenge the statisticians who work on vaccine clinical trials.

Simultaneous Confidence Bounds for Relative Risks in Multiple Comparisons to Control
View Presentation View Presentation Bernard Klinggenberg, Williams College, Department of Mathematics and Statistics

Practical Issues in Vaccine Interim Analysis
View Presentation View Presentation Robert C. Kohberger, Blair and Company, LLC

Secondary Endpoints in Vaccine Efficacy Trials: Not Just an Afterthought
View Presentation View Presentation Karen Goldenthal, Bethesda Biologics Consult


CS6a Evaluation of Efficacy and Safety in the Presence of Subgroup Heterogeneity

11:00 AM - 12:15 AM
Presidential Ballroom

Organizer(s): Sudeep Kundu, Sanofi-Aventis; Daphne T.Y. Lin, FDA/CDER

Chair(s): Rajeshwari Sridhara, FDA

Subgroup analyses defined by various baseline characteristics such as, biomarkers or disease classifiers, are usually treated as hypothesis generating analyses as they are often unplanned/post-hoc analyses. However such subgroup results may provide valuable information in the selection of therapeutic regimens for the treatment of a given disease. In the era of targeted and individualized therapy, combining existing information from independent studies in the evaluation of efficacy and safety of a drug product in the presence of subgroup heterogeneity is challenging. In this session methods used to address this challenge in different therapeutic areas will be discussed. This session will be useful for statisticians who are involved in design and analysis of clinical trials.

Subgroup Heterogeneity in Drug Efficacy
View Presentation View Presentation Qiang (Casey) Xu, FDA-CDER

Assessment of Treatment Effect Non-Homogeneity in a Regulatory Setting: Practices, Pitfalls and Some Suggested Approaches
View Presentation View Presentation Larry Roi, Sanofi-Aventis

Understanding the Heterogeneity of the Patients Populations by Subgroup Analyses from the Past Trials to Improve Future Study Design
View Presentation View Presentation Yunfan Deng, FDA


CS6b Adaptive Design: Applications and Examples

11:00 AM - 12:15 PM
Congressional Room

Organizer(s): Ning Li, FDA; Annpey Pong, Schering-Plough Corporation; Yong-Cheng Wang, Biogen Idec

Chair(s): Eva Miller, ICON Clinical Research

The general goals for this session are (i) to present some real examples of adaptive design in clinical trials for drug development, (ii) to address the challenges from both sponsors and regulatory agencies, and (iii) to discuss practical applications in adaptive designs. The following topics are proposed. (1). An Adaptive Design that Uses a Utility Function to Identify the Best Dose in a Crossover Setting; (2) Implementing a Bayesian Outcome-Adaptive Randomization Trial (A Case Study); (3) On Sample Size Calculation for Two-Stage Seamless Adaptive Trial Designs; (4) A discussant from FDA to address regulator’s expectations and experiences. The focus of the section is for applications instead of theoretical methods. The presentations in this session cover different therapeutic areas for Phase I, II, and III studies.

Case Study: An Adaptive Design that Uses a Utility Function to Identify the Best Dose in a Crossover Setting
View Presentation View Presentation Kenneth Liu, Merck

Implementing a Bayesian Outcome-Adaptive Randomization Trial (A Case Study)
View Presentation View Presentation Kye Gilder, Biogen Idec

On Sample Size Calculation for Two-Stage Seamless Adaptive Trial Designs
View Presentation View Presentation Annpey Pong, Schering-Plough Corporation

View Presentation View Presentation Boguang Zhen, FDA

Discussant(s): Boguang Zhen, FDA


CS6c Effective Communication and Collaboration between FDA and Industry Statisticians in the Regulatory Environment

11:00 AM - 12:15 PM
South American AB Room

Organizer(s): Tammy Massie, FDA; Jennifer Schumi, Statistics Collaborative, Inc.

Chair(s): Fan-fan Yu, Statistics Collaborative, Inc.

Do you wonder what others do to ensure seamless communications within a regulatory environment? Have communications with fellow statisticians, review teams, regulatory or industry colleagues not progressed in the right direction or as smoothly as you hoped? If so, this session is for you! This session will start with a brief introductory talk on effective communication and negotiation in general. A more in-depth case study of an effective interaction between statisticians at FDA and statisticians from outside of the agency will be presented next. We will conclude with an interactive panel discussion that seamlessly transitions into roundtable discussions with statisticians from industry and multiple FDA centers and divisions. Panelists and attendees will be encouraged to share perspectives and experiences from their own communications and interactions. The session will be primarily applied, with examples from an actual FDA submission guiding the majority of the time in the session. Although the examples may address specific therapeutic areas and product classes, most likely from Phase III studies, the issues discussed will be more generally applicable to the broader audience of statisticians from FDA, industry, and other organizations.

Overview of Communication including Negotiation skills
View Presentation View Presentation Joann Boughman, American Society of Human Genetics

Regulatory processes from Industry/FDA Statisticians’ perspectives
View Presentation View Presentation Hope Knuckles, Abbott Laboratories, NIC-ASA; Marina Kondratovich, FDA-CDRH

Brief Panel Discussion: What I wish I knew…Top suggestions for Effective Communication and Interaction in a Regulatory Environment
Martin Ho, FDA/CDRH; Jessica Kim, FDA/CBER; Qian Mao, Wright Medical Technology


CS6d Biomarkers in Drug-Diagnostic Co-Development

11:00 AM - 12:15 PM
Pan American Room

Organizer(s): Yu-Ling Chang, FDA; Deepak Khatry, MedImmune; May Mo, Amgen

Chair(s): Howard Mackey, Genentech

The revolution of individualized medicine has not kept pace with the hype presented in the scientific literature and mainstream media. Patients have long heard about individualized medicine but are wondering when the steady stream of molecularly targeted therapeutics, specially tailored to their disease, is due to arrive. Science and technology have outpaced our ability to design and accrue the clinical studies necessary to gain regulatory approval. While drug developers are burdened with the increased cost and complexity of drug/dx co-development, regulatory agencies are pressured to act on imperfect data without compromising their legal mandate to ensure that marketed drugs show substantial evidence of efficacy and safety. This session will focus on some of the challenges in drug/dx co-development along with possible strategies for addressing them. A December 2008 Oncologic Drugs Advisory Committee meeting raised issues about clinical trial designs, diagnostic tests, and retrospective analyses. These issues will motivate perspectives from academia, industry, and government regarding: • analytical and clinical characterization of a dx • optimal dx cut-off points • ascertainment and bias related to retrospective subgroup analyses • ways to address improvements in dx technology post approval and • design challenges to enable prospective or retrospective confirmation of the clinical utility of a biomarker for patient selection.

Points to Consider in Design of Trials for Drug-Diagnostic Co-Development in Oncology
Michael Wolf, Amgen

Issues Involving the Determination of Efficacy in Biomarker Subgroups
View Presentation View Presentation Mark Rothmann, FDA

The Promise of Personalized Medicine: The Challenges for Statistics
View Presentation View Presentation Gregory Campbell, Center for Devices and Radiological Health, FDA


RF1 Roundtable: Design and Implementation of Clinical Studies-Friday

12:30 PM - 1:30 PM
Statler AB Room

#1 Multistage gatekeeping procedures
George Kordzakhia, FDA

#2 Challenges & Issues faced by non-inferiority trials
Misook Park, FDA

#3 Implementation Issues for Adaptive Trials
Weili He, Merck Pharmaceuticals

#4 Designing clinical trials with diagnostics in mind
Jane Fridlyand, Genentech

#5 Working Experiences with Adaptive Design in Clinical Trials
Eva Miller, ICON Clinical Research; Annpey Pong, Schering-Plough Corporation

#6 Issues Encountered in the Design and Implementation of Multi-Regional Clinical Trials
Yeh-Fong Chen, FDA; Peter Ouyang, Celgene Corporation

#7 Biostatistics Education for Global Drug Development
Yoko Adachi, U.S. Food and Drug Administration; William Wang, Merck Sharp &Dohme Ltd., China

#8 Futility Analysis in Futility/Interim Analysis
Xiaolin Wang, Genentech

#9 Consequences of Asymmetry in Progression Assessments
Shenghui Tang, FDA

#10 Disease network and personalized medicine
Wei Liu, FDA/ CDER

#11 Clinical Trial Disclosure
Marcia Levenstein, Pfizer; Sarah Young, Pfizer

#12 Multi-Regional Trials Sample Size Considerations
Lucy Shneyer, Schering-Plough Research Institute

#13 Statistical Issues in the Design of Clinical Trials for Alzheimer's Disease
Thomas Kelleher, Bristol Myers Squibb Company, Global Biometric Sciences

#14 One or two, that's the question?
Kate Dwyer, FDA


RF2 Roundtable: Anaylsis of Clinical Trials - Friday

12:30 PM - 1:30 PM
Senate Room

#1 Surrogate Endpoints for Overall Survival
Qiang (Casey) Xu, FDA-CDER

#2 Use of Bayesian methods to evaluate safety data in an ongoing fashion
Melissa Spann, Eli Lilly & Company

#3 Quality ofFollow-up in OncologyTrials for Registration
Mark Rothmann, FDA

#4 Design Strategies for Demonstrating Disease-Modifying Effects in Alzheimer’s and Parkinson’s Diseases
Alex Kouassi, Schering-Plough

#5 How to analyze data and present results in clinical study with a titration period or flexible dose
Patrick Liu, UCB

#6 Statistical Contributions in the Integrated Summary of Effectiveness
Lillian Patrician, FDA

#7 Maintenance claim in presence of missing data from chronic pain trial
Yongman Kim, FDA

#8 Risk Management in Food, Drugs, and Devices: Something Old, Something New, Something Borrowed, and Something Blue
Carolyn Carroll, Stat Tech, Inc.

#9 Issues with Safety Studies for Chronic Drugs using Large Simple Trials
Deborah Shapiro, Merck Research Laboratories

#10 Role of Covariate Adjustment in Non-Randomized and Randomized Studies
Pablo Bonangelino, FDA

#11 Subgroup Analysis
Chul Ahn, FDA

#12 Repeated Measures and Recurrent Events
Chang S. Lao, FDA

#13 Methods for Measuring Agreement: Do We Agree?
Radha Railkar, Merck & Company

#14 Meta-analysis in Pharmaceutical Development
Charles L. Liss, Merck research Laboratories

#15 Experience with Meta-analyses
Joy D. Mele, FDA

#16 Risk, Benefit, and Utility in Clinical Trials
Jonathan D. Norton, FDA, CDER, Biometrics II


RF3 Roundtable: Center Specific

12:30 PM - 1:30 PM

#1 Future Direction for Methods and Method Validation
Robert E. Koeritzer, 3M Food Safety

#2 Veterinary Issues for Pharmaceutical Statististics
Todd Blessinger, FDA, CVM; Steven Radecki, Affiliation Needed

#3 Testing non-inferiority of binary outcomes in GLMM
Virginia Recta, FDA/CVM

#4 A view of missing data analysis from a medical device industry perspective
Hsini (Terry) Liao, Boston Scientific

#5 In Vitro Diagnostic (IVD) Device Topics
Angel DeGuzman, Abbott Laboratories

#6 Methods for Estimating and Calculating  Confidence Intervals  for Vaccine Efficacy
Allen Izu, Novartis Vaccines

CANCELLED #7 Diagnostic Reagent Cross Contamination Studies

#8 "3+3", CRM, etc., which approach?
Shiowjen Lee, FDA/CBER; Stan Lin, FDA/CBER

#9 Composite endpoints
Kerry Go, Sanofi Pasteur


RF4 Roundtable: CMC/Early Clinical - Friday

12:30 PM - 1:30 PM
New York Room

#1 Pharmacogenomic Studies
Michael Crager, Genomic Health, Inc.

#2 Statistical issues on thorough QT clinical trials
Yi Tsong, FDA

#3 Translational Medicine
Dennis Cosmatos, Parexel International, Inc.

#4 Implementing Model-based Drug Development- Insight Sharing and Experience Exchange
Yaning Wang, U.S. Food and Drug Administration, CDER; Harry Yang, MedImmune


RF5 Roundtable: Other Technical/Statistical Topics - Friday

12:30 PM - 1:30 PM
Massachusetts Room

#1 Detection of Fraudulent Data in Clinical Trials: What Pharmaceuticals Should and Can Be Expected To Do
Steve Koval, Boehringer-Ingelheim Pharmaceuticals

#2 Validation of SAS® programs supporting submissions
Nora M. Fagan, Boehringer-Ingelheim Pharmaceuticals

#3 Optimizing the DMC Package for Efficient Review
Joan Kempthorne-Rawson, Boehringer-Ingelheim Pharmaceuticals

#4 The Joys of R for Nonclinical and Preclinical Statistics
Bert Gunter, Genentech Nonclinical Statistics


RF6 Roundtable: Professional and Personal Development - Friday

12:30 PM - 1:30 PM
California Room

#1 Favorite Adventure Travel: Undiscovered Places
Robert Abugov, Center for Drug Evaluation and Research

#2 What do baseball photography and statistics have in common?
Lisa Kammerman, FDA/CDER

#3 Working as a Statistician Under a Flexible or Non-traditional Work Arrangement
Stephanie Klopfer, Merck Research Laboratories


RF7 Roundtable: Communication

12:30 PM - 1:30 PM
Ohio Room

#1 Effective Communication and Collaboration between FDA and Industry Statisticians in the Regulatory Environment
Martin Ho, FDA/CDRH; Qian Mao, Wright Medical Technology

#2 Working with the FDA on Submissions with PRO Endpoints
Jenny N. Devenport, Alcon Laboratories; Rima Izem, FDA

#3 Role of the CRO in communications between Industry and the FDA
Sonia M. Davis, Quintiles


PL3 Future Directions in Planning Safety Analysis and Risk Management

1:30 PM - 3:15 PM
Presidential/Congressional Ballrooms

Organizer(s): Henry Hsu, FDA; Deborah Shapiro, Merck Research Laboratories; Sue Jane Wang, FDA; H. Amy Xia, Amgen, Inc.

Chair(s): Qian Graves, FDA

Appropriate assessment of safety throughout a product’s lifecycle is one of the most important issues facing both industry and regulators today. The environment is changing rapidly and drug safety concerns are in the news frequently, but they are not clearly understood by the public or the media. This session will examine potential ways to address drug safety from the planning phases with such FDA initiatives as the Quantitative Safety Analysis Plan (QSAP), to innovative ways to make use of administrative data and such initiatives as the Observational Medical Outcomes Partnership (OMOP), and with a new idea for conducting larger, simpler, randomized treatment trials.

Workshop Wrap up 2009 Cochairs
Carmen Mak, Schering Plough; Tammy Massie, FDA

Workshop Wrap up 2010 Cochairs
View Presentation View Presentation Ivan Chan, Merck Research Laboratory; Qian Graves, FDA

Scope and Context for Lifecycle Safety Planning and Evaluation: Towards A Quantitative Safety Analysis Template
George Rochester, FDA, CDER

Strengths, Limitations, and Suggested Modifications of the Use of Administrative Data in the Assessment of Post-marketing Safety of Pharmaceuticals
View Presentation View Presentation Jesse Berlin, Johnson & Johnson Pharmaceutical Research and Development

Randomized Consumer Trials
View Presentation View Presentation Scott Zeger, The Johns Hopkins University

Discussant(s): Robert Ball, FDA; Jesse Berlin, Johnson & Johnson Pharmaceutical Research and Development; Robert O'Neill, FDA, CDER; George Rochester, FDA, CDER; Scott Zeger, The Johns Hopkins University