Online Program
Wed, Sep 23 |
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SC1 Adaptive Designed Clinical Trials |
09/23/09 |
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Instructor(s): Martin Posch, University at Vienna; Sue Jane Wang, CDER |
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SC2 Benefit: Risk Assessment |
09/23/09 |
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Instructor(s): Scott Evans, Harvard |
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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. |
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SC3 Analysis of Longitudinal Studies with Missing Data |
09/23/09 |
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Instructor(s): Diane Fairclough, UCHSC |
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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 . |
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SC4 Cox Regression in Practice |
09/23/09 |
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Instructor(s): Brenda Gillespie, University of Michigan |
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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. |
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SC5 Special Topics in Survival Analysis |
09/23/09 |
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Instructor(s): Lee-Jen Wei, Harvard University |
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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. |
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SC6 Bootstrap Methods and Permutation Tests |
09/23/09 |
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Instructor(s): Tim Hesterberg, Google |
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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. |
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SC7 Recent Advances I Bayesian Adaptive Methods for Clinical Tests |
09/23/09 |
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Instructor(s): Peter Thall, MD Anderson |
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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. |
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SC8 Data Monitoring Committees |
09/23/09 |
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Instructor(s): Thomas Fleming, University of Washington; Janet Wittes, Statistics Collaborative, Inc. |
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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. |
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Thu, Sep 24 |
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PL1 Regulatory Issues in Global Harmonization of Clinical Studies |
09/24/09 |
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Organizer(s): Bruce Binkowitz, Merck, PhrMa; Hope Knuckles, Abbott Laboratories, NIC-ASA; Richard Kotz, FDA-OSB/CDRH |
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Chair(s): Hope Knuckles, Abbott Laboratories, NIC-ASA |
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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. |
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Welcome and Introduction
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Global Harmonization - Global Harmonization
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Global Harmonization – Ethical and Scientific Considerations
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Global Harmonization – Global Regulatory and Clinical Affairs for Drug Development
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PL2 The World is (almost) Flat: Statistical Considerations as Clinical Development Goes Global |
09/24/09 |
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Organizer(s): Yoko Adachi, U.S. Food and Drug Administration; Brent Burger, Vislation; Margaret Minkwitz, AstraZeneca |
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Chair(s): Peter Ouyang, Celgene Corporation |
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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. |
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Statistical Issues in Multiple-Regional Clinical Trials
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Assessing Consistency of Treatment Effects in Multiple-Regional Clinical Trials: A Systematic Review and Case Study
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Implication of Asian Studies in Simultaneous Global Clinical Trials
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Statistical Considerations for Clinical Development in China
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RT1 Roundtable: Design and Implementation of Clinical Studies - Thursday |
09/24/09 |
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Power and Sample Size for Multiple Endpoints
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Medical Device Non-Inferiority Trials
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Multiplicity Issues in Insomnia trials
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Use of sample size re-estimation in confirmatory trials
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Assessing confidence of go/no-go decision in clinical trial program
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#1 Utility and use of PD biomarkers for making development decisions in early phase oncology clinical
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IVRS kit supply strategies for blinded randomized clinical trials
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Implementation of Adaptive Trials
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Global Trial Harmonization Issues
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How to Consolidate Information from Multiple Endpoints in a Dose Finding Study
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Improving the Quality of Clincal Trials
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Assessing Clinical Significance - Implications for Protocols and Clinical Study Reports
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Efficacy Interim Analysis in Futility/Interim Analysis
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Adaptive Designs in the Real World
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Statistical Issues in Solid Tumor Response Assessment
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Placebo Response in CNS Clinical Trials
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Improving Clinical Trials in Imaging: endpoints and data collection
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Selection of primary analysis sets for trials with non-inferiority/superiority tests
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Switch from Rx to OTC: Design and Analysis Issues
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RT2 Roundtable: Anaylsis of Clinical Trials - Thursday |
09/24/09 |
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#1 Cross-over and follow-up issues in time-to-event endpoints
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#2 Opportunities to Apply Bayesian Methods in Phase III of Drug Development
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#3 Adequacy of Patient followup and sensitivity analysis in the presence of missing data for PFS in oncology trials
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#4 Some issues in oncology trials with Progression-free survival (PFS) and Overall Survival (OS) as endpoints
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#5 Longitudinal Analysis, Missing Data and Assessment of Durability of Treatment Effect
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#6 Is center (or region) pooling necessary to avoid excluding patients in a stratified analysis by center (or region)?
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#7 Surrogate Markers in Oncology
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#8 Handling Missing Values
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#9 Analysis of Patient-Reported Outcomes in Oncology Clinical Trials
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#10 Monitoring Safety During Drug Development
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#11 The Independent Statistician - More than the Custodian of the Treatment Codes
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#12 Proactive and Systemic Approaches for the Planning, Evaluation and Presentation of Safety Data
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#13 Follow up from the Meta Analysis with a Focus on Safety Session
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RT3 Roundtable: Center Specific - Thursday |
09/24/09 |
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#1 Typing Food-Borne Bacteria Using Microarrays, Repeats, and SNPs
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#2 Comparing statistics used by CVM and CVB
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#3 Deciding to Transform Data
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#4 Baseline Value in Repeated Measures Analysis
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#5 Concerns and Issues of IVD Post approval Studies
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#6 The Statisticians Role in Safety Evaluation
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RT4 Roundtable: CMC/Early Clinical - Thursday |
09/24/09 |
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#1 Assessing the Quality of Hybridized RNA in Affymetrix GeneChips
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#2 Sharing experiences with use of biomarkers in clinical trials
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#3 Failure-Time Mixture Models for Evaluating Efficacy in the Presence of a Biomarker
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#4 The Promises and Challenges of Biomarker Utility in Developing Drugs and Obtaining Regulatory Approval
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#5 On Clinical Utility and Biomarkers
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RT5 Roundtable: Other Technical/Statistical Topics - Thursday |
09/24/09 |
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#1Value of Assessing the Impact of Treatment on Healthcare Resource Utilization
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#2 Applied Adaptive Designs - Software in Use (What is available & how are people using it)
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#3 Emerging Methods and Research Directions for AE Identification in SRS: Data Mining and More
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#4 How can statisticians contribute more actively to ensure data quality?
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RT6 Roundtable: Professional and Personal Development - Thursday |
09/24/09 |
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#1 Tips on steeking for hand painted yarn projects, bring a project and questions or tips to share
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#2 Communication skills for New statisticians in Industry
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#3 Professional Development: Effective Communication
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#4 Work/Life Balance – Alternatives to the 36-hour day
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CS1a Practical Considerations of Futility Analysis and Regulatory Case Sharing on Interim Analysis |
09/24/09 |
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Organizer(s): Edmund Luo, Merck & Co.; Vivian Yuan, FDA |
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Chair(s): Xiaolin Wang, Genentech |
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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. |
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Futility Analysis: Practical Considerations
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Case Sharing on Interim Analysis
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Panel Discussions of Practical Considerations of Futility Analysis
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CS1b Survival Analysis – Issues Related to Follow-up in Time to Event Endpoints |
09/24/09 |
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Organizer(s): Zhenming Shun, sanofi-aventis; Qiang (Casey) Xu, FDA-CDER; John Zhong, Human Genome Sciences |
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Chair(s): Pabak Mukhopadhyay, Novartis Oncology |
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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. |
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Correcting for Non-Compliance in Randomized Trials
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Sensitivity Analysis for Treatment Drop-in in Oncology Clinical Trials
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Discussion
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Discussant(s): Rajeshwari Sridhara, FDA |
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CS1c Food Safety and Validation Method |
09/24/09 |
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Organizer(s): Geraldine E. Baggs, Abbott Nutrition R&D - Statistical Services; Qian Graves, FDA |
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Chair(s): Curtis Barton, CFSAN/FDA |
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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. |
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Typing Food-Borne Bacteria Using Microarrays and SNPs
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Validated Methods for US and International Trade
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Serial Dilutions
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CS1d Concepts in the Planning and Analyses of Target Animal Safety Studies for Veterinary Products |
09/24/09 |
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Organizer(s): Anna Nevius, FDA |
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Chair(s): Stephine Keeton, FDA |
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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. |
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An Overview of Safety Studies
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Current Practices in Safety Studies
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Theoretical Considerations in Safety Studies
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CMC1 CMC Panel Discussion Series I: Shelf Life Determination |
09/24/09 |
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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. |
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CS2a Multiplicity Adjustment in Clinical Trials with Multiple (Primary and Secondary) Endpoints: Issues and Concerns |
09/24/09 |
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Organizer(s): Jie Chen, Abbott Labs; Kooros Mahjoob, FDA/CDER/OTS/OB/DB1; Lanju Zhang, MedImmune, Inc. |
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Chair(s): Sonia M. Davis, Quintiles |
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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. |
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Partition Decision Paths to Test for Efficacy with Multiple Endpoints
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Handling Multiplicity Issues in Primary and Secondary Endpoints
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Challenges to Multiple Comparison Problems in Regulatory Applications
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CS2b PK/PD Model-based Drug Development |
09/24/09 |
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Organizer(s): Li Chen, Amgen; Harry Yang, MedImmune |
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Chair(s): Yaning Wang, U.S. Food and Drug Administration, CDER |
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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. |
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Using PK-PD modeling to support selection of First-Time-In-Man dose and Phase I Trial Design
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Exploring Biomarker/Pharmacokinetics Relationships in Early Clinical Studies to Enable Good Decisions
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Leveraging Prior Knowledge to Drive Drug Development Decision
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CS2c Recent Issues in CNS Drug Development |
09/24/09 |
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Organizer(s): Craig Mallinckrodt, Eli Lilly; Tristan Massie, FDA |
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Chair(s): Susan Huyck, Schering-Plough |
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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. |
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Design of Insomnia Drug Trials and Related Statistical Issues
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Science of Endpoint Selection and Patient Reported Outcomes (PROs)
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Drop-out and Related Issues in CNS trials
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CS2d Vet Medicine I – Design and Analysis |
09/24/09 |
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Organizer(s): Diane Sweeney, Intervet/Schering-Plough Animal Health |
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Chair(s): Todd Blessinger, FDA, CVM |
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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. |
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On the Problem of Negative Variance Component Estimates in Mixed Models
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Challenges Associated with E. coli O157 and Salmonella Studies Conducted in Real-World Settings
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Study Design Considerations in Veterinary Biologics
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CMCII CMC Panel Discussion Series II: Method Validation and Transfer |
09/24/09 |
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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. |
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CS3a Adaptive Designs: Theory and Methods |
09/24/09 |
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Organizer(s): Yeh-Fong Chen, FDA; Weili He, Merck Pharmaceuticals |
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Chair(s): Jeff Maca, Novartis Pharmaceuticals |
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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. |
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Adaptive Patient Enrichment Designs in Therapeutic Trials
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Type I Error Rate Control in Adaptive Designs for Confirmatory Clinical Trials withTtreatment Selection at Interim
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Adaptive Dose Ranging Studies: An Update from the PhRMA Working Group
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Discussant(s): Keaven Anderson, Merck & Company |
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CS3b Quantitative Approaches to Decision Making in Clinical Development |
09/24/09 |
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Organizer(s): Li Chen, Amgen; Jane Fridlyand, Genentech; Shiling Ruan, Food and Drug Administration; Stephen Wilson, FDA/CDER |
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Chair(s): David Li, Wyeth Research Division |
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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. |
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Choosing right metrics to enable sound decisions
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If I Were a VP or a VC…
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Using Decision Analysis to Regulate Medical Devices
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CS3c Preserving Integrity of Clinical Trials: Drug Supply, Patient Randomization and Data Verification |
09/24/09 |
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Organizer(s): Jane Fridlyand, Genentech; David Li, Wyeth Research Division; Karen Qi, FDA/CDER; Stephen Wilson, FDA/CDER |
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Chair(s): Daphne T.Y. Lin, FDA/CDER |
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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. |
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Kit Supply Algorithms to Protect the Integrity of Blinded Randomized Clinical Trials
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Dynamic Allocation: A Case Study
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A Regulatory Perspective of the Statistician’s Role in the Data Verification and Inspection Process
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CS3d Aspects of Missing Data Unique to Medical Device Trials |
09/24/09 |
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Organizer(s): Terri Johnson, FDA/CDRH; Peter Lam, Boston Scientific |
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Chair(s): Scott Miller, FDA/CDRH |
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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. |
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Missing Data in Orthopedic Implant Clinical Trials: A case for Sensible LOCF (Last Observation Carried Forward)
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The Problem of Missing Data in Medical Device Trials
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The Missing Details of Your Missing Data Analysis Plan
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CMCIII CMC Panel Discussion Series III: Design Space Definition |
09/24/09 |
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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. |
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Fri, Sep 25 |
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CS4a Meta Analysis with a Focus on Safety |
09/25/09 |
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Organizer(s): Patience Ajongwen, Johnson & Johnson; Jesse Berlin, Johnson & Johnson Pharmaceutical Research and Development; Irmarie Reyes, Genentech |
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Chair(s): Yu-te Wu, FDA |
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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. |
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Meta Analysis of Stroke Rates using Patient Level Data in Age-Related Macular Degeneration in Patients treated with Ranibizumab
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Current Status of Drug-Eluting vs Bare-Metal Stents: Interpreting the Data
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Key Issues in Meta-Analysis with Applications to Safety Data
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CS4b Views on Integrated Summary of Effectiveness and Integrated Summary of Safety: From FDA and Industry Perspective |
09/25/09 |
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Organizer(s): Patrick Liu, UCB; Kooros Mahjoob, FDA/CDER/OTS/OB/DB1 |
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Chair(s): Jingyee Kou, FDA/CBER/OBE/DB/VEB |
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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. |
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Updates on the Guidances for Industry: Integrated Summaries of Effectiveness and Safety
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Integrated Summary of Effectiveness/Safety: Statistical Implementation Suggestions
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Panel Discussion
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CS4c Endpoint Issues in Oncology Trials |
09/25/09 |
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Organizer(s): Sudeep Kundu, Sanofi-Aventis; Laura (Hong) Lu, FDA/CDER/OB/DB5; Pabak Mukhopadhyay, Novartis Oncology |
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Chair(s): Mark Rothmann, FDA |
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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. |
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Issues in Using ‘Progression-free Survival’ when Evaluating Interventions in Oncology
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Some Statistical Issues and Misunderstandings in the Assessment of PFS
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Use of blinded independent central review for auditing purposes
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CS4d Statistical Issues for Diagnostic Devices |
09/25/09 |
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Organizer(s): Patience Ajongwen, Ortho-Clinical Diagnostics; Rong (Rona) Tang, FDA/CDRH |
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Chair(s): Vicki Petrides, Abbott Laboratories |
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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. |
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n-Market Statistical Support
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Meta-analysis for Diagnostic Devices
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Heterogeneity in Meta-Analysis of Diagnostic Test Accuracy
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CS5a Longitudinal Analysis, Missing Data and Assessment of Durability of Treatment Effect |
09/25/09 |
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Organizer(s): Phillip Dinh, FDA; Yongman Kim, FDA; Pat O'Meara, Pat O'Meara Associates, Inc.; Gosford Sawyerr, Purdue Pharma L.P. |
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Chair(s): Greg (Guoxing) Soon, FDA |
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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. |
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Issues in Assessment of Durability of Success in HIV Clinical Trials
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A Bias Correction in Testing Treatment Efficacy under Informative Dropout in Clinical Trials
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Defining and Evaluating Bias in Longitudinal Trials with NMAR Missing Data
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Discussant(s): Tom Permutt, FDA |
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CS5b Design and Analysis for Non-inferiority Trial: A Practical Perspective |
09/25/09 |
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Organizer(s): Terri Johnson, FDA/CDRH; Misook Park, FDA; Yuan-Li Shen, FDA |
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Chair(s): Gang Chen, Johnson & Johnson |
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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. |
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Covariate-adjusted Putative Placebo Analysis in Active-controlled Clinical Trials
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A Case Study for The Design and Conduct of Non-Inferiority Clinical Trials
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Panel Discussion
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CS5c Bayesian Methods throughout the Lifecycle of Medical Products |
09/25/09 |
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Organizer(s): Andrew Mugglin, University of Minnesota; Yunling Xu, CDRH/FDA; Jeffrey Zhang, Schering Plough |
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Chair(s): Brenda Gaydos, Eli Lilly |
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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. |
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Maximally Flexible Bayesian Designs in Randomized Clinical Trials
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Bayesian methods in the premarket approval of medical devices
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Bayesian Hierarchical Modeling for Detecting Safety Signals in Clinical Trials
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CS5d Statistical Issues in Vaccine Clinical Trials |
09/25/09 |
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Organizer(s): Kerry Go, Sanofi Pasteur; Allen Izu, Novartis Vaccines |
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Chair(s): Jingyee Kou, FDA/CBER/OBE/DB/VEB |
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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. |
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Simultaneous Confidence Bounds for Relative Risks in Multiple Comparisons to Control
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Practical Issues in Vaccine Interim Analysis
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Secondary Endpoints in Vaccine Efficacy Trials: Not Just an Afterthought
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CS6a Evaluation of Efficacy and Safety in the Presence of Subgroup Heterogeneity |
09/25/09 |
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Organizer(s): Sudeep Kundu, Sanofi-Aventis; Daphne T.Y. Lin, FDA/CDER |
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Chair(s): Rajeshwari Sridhara, FDA |
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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. |
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Subgroup Heterogeneity in Drug Efficacy
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Assessment of Treatment Effect Non-Homogeneity in a Regulatory Setting: Practices, Pitfalls and Some Suggested Approaches
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Understanding the Heterogeneity of the Patients Populations by Subgroup Analyses from the Past Trials to Improve Future Study Design
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CS6b Adaptive Design: Applications and Examples |
09/25/09 |
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Organizer(s): Ning Li, FDA; Annpey Pong, Schering-Plough Corporation; Yong-Cheng Wang, Biogen Idec |
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Chair(s): Eva Miller, ICON Clinical Research |
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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. |
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Case Study: An Adaptive Design that Uses a Utility Function to Identify the Best Dose in a Crossover Setting
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Implementing a Bayesian Outcome-Adaptive Randomization Trial (A Case Study)
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On Sample Size Calculation for Two-Stage Seamless Adaptive Trial Designs
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Discussion
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Discussant(s): Boguang Zhen, FDA |
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CS6c Effective Communication and Collaboration between FDA and Industry Statisticians in the Regulatory Environment |
09/25/09 |
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Organizer(s): Tammy Massie, FDA; Jennifer Schumi, Statistics Collaborative, Inc. |
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Chair(s): Fan-fan Yu, Statistics Collaborative, Inc. |
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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. |
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Overview of Communication including Negotiation skills
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Regulatory processes from Industry/FDA Statisticians’ perspectives
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Brief Panel Discussion: What I wish I knew…Top suggestions for Effective Communication and Interaction in a Regulatory Environment
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CS6d Biomarkers in Drug-Diagnostic Co-Development |
09/25/09 |
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Organizer(s): Yu-Ling Chang, FDA; Deepak Khatry, MedImmune; May Mo, Amgen |
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Chair(s): Howard Mackey, Genentech |
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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. |
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Points to Consider in Design of Trials for Drug-Diagnostic Co-Development in Oncology
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Issues Involving the Determination of Efficacy in Biomarker Subgroups
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The Promise of Personalized Medicine: The Challenges for Statistics
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RF1 Roundtable: Design and Implementation of Clinical Studies-Friday |
09/25/09 |
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#1 Multistage gatekeeping procedures
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#2 Challenges & Issues faced by non-inferiority trials
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#3 Implementation Issues for Adaptive Trials
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#4 Designing clinical trials with diagnostics in mind
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#5 Working Experiences with Adaptive Design in Clinical Trials
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#6 Issues Encountered in the Design and Implementation of Multi-Regional Clinical Trials
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#7 Biostatistics Education for Global Drug Development
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#8 Futility Analysis in Futility/Interim Analysis
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#9 Consequences of Asymmetry in Progression Assessments
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#10 Disease network and personalized medicine
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#11 Clinical Trial Disclosure
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#12 Multi-Regional Trials Sample Size Considerations
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#13 Statistical Issues in the Design of Clinical Trials for Alzheimer's Disease
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#14 One or two, that's the question?
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RF2 Roundtable: Anaylsis of Clinical Trials - Friday |
09/25/09 |
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#1 Surrogate Endpoints for Overall Survival
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#2 Use of Bayesian methods to evaluate safety data in an ongoing fashion
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#3 Quality ofFollow-up in OncologyTrials for Registration
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#4 Design Strategies for Demonstrating Disease-Modifying Effects in Alzheimer’s and Parkinson’s Diseases
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#5 How to analyze data and present results in clinical study with a titration period or flexible dose
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#6 Statistical Contributions in the Integrated Summary of Effectiveness
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#7 Maintenance claim in presence of missing data from chronic pain trial
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#8 Risk Management in Food, Drugs, and Devices: Something Old, Something New, Something Borrowed, and Something Blue
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#9 Issues with Safety Studies for Chronic Drugs using Large Simple Trials
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#10 Role of Covariate Adjustment in Non-Randomized and Randomized Studies
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#11 Subgroup Analysis
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#12 Repeated Measures and Recurrent Events
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#13 Methods for Measuring Agreement: Do We Agree?
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#14 Meta-analysis in Pharmaceutical Development
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#15 Experience with Meta-analyses
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#16 Risk, Benefit, and Utility in Clinical Trials
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RF3 Roundtable: Center Specific |
09/25/09 |
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#1 Future Direction for Methods and Method Validation
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#2 Veterinary Issues for Pharmaceutical Statististics
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#3 Testing non-inferiority of binary outcomes in GLMM
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#4 A view of missing data analysis from a medical device industry perspective
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#5 In Vitro Diagnostic (IVD) Device Topics
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#6 Methods for Estimating and Calculating Confidence Intervals for Vaccine Efficacy
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#8 "3+3", CRM, etc., which approach?
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#9 Composite endpoints
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RF4 Roundtable: CMC/Early Clinical - Friday |
09/25/09 |
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#1 Pharmacogenomic Studies
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#2 Statistical issues on thorough QT clinical trials
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#3 Translational Medicine
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#4 Implementing Model-based Drug Development- Insight Sharing and Experience Exchange
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RF5 Roundtable: Other Technical/Statistical Topics - Friday |
09/25/09 |
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#1 Detection of Fraudulent Data in Clinical Trials: What Pharmaceuticals Should and Can Be Expected To Do
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#2 Validation of SAS® programs supporting submissions
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#3 Optimizing the DMC Package for Efficient Review
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#4 The Joys of R for Nonclinical and Preclinical Statistics
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RF6 Roundtable: Professional and Personal Development - Friday |
09/25/09 |
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#1 Favorite Adventure Travel: Undiscovered Places
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#2 What do baseball photography and statistics have in common?
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#3 Working as a Statistician Under a Flexible or Non-traditional Work Arrangement
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RF7 Roundtable: Communication |
09/25/09 |
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#1 Effective Communication and Collaboration between FDA and Industry Statisticians in the Regulatory Environment
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#2 Working with the FDA on Submissions with PRO Endpoints
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#3 Role of the CRO in communications between Industry and the FDA
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PL3 Future Directions in Planning Safety Analysis and Risk Management |
09/25/09 |
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Organizer(s): Henry Hsu, FDA; Deborah Shapiro, Merck Research Laboratories; Sue Jane Wang, FDA; H. Amy Xia, Amgen, Inc. |
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Chair(s): Qian Graves, FDA |
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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. |
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Workshop Wrap up 2009 Cochairs
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Workshop Wrap up 2010 Cochairs
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Scope and Context for Lifecycle Safety Planning and Evaluation: Towards A Quantitative Safety Analysis Template
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Strengths, Limitations, and Suggested Modifications of the Use of Administrative Data in the Assessment of Post-marketing Safety of Pharmaceuticals
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Randomized Consumer Trials
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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 |
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Key Dates
-
April 30 - May 22, 2013
Invited Abstract Submission Open -
June 4, 2013
Online Registration Opens -
August 9 - August 23, 2013
Invited Abstract Editing -
August 23, 2013
Short Course materials due from Instructors -
August 26, 2013
Housing Deadline -
September 9, 2013
Cancellation Deadline and Registration Closes @ 11:59 pm EDT -
September 16 - September 18, 2013
Marriott Wardman Park, Washington, DC