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213748 - Statistical Analysis of Medical Product Safety Data and Benefit-Risk Assessment (ADDED FEE)
Type: Professional Development
Date/Time: Monday, July 31, 2017 : 8:30 AM to 5:00 PM
Sponsor: ASA
Abstract #325481
Title: Statistical Analysis of Medical Product Safety Data and Benefit-Risk Assessment (ADDED FEE)
Author(s): Jie Chen* and Joseph Heyse* and Tze Leung Lai*
Companies: Novartis Pharmaceutical Corporation and Merck & Co., Inc. and Stanford University
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Abstract:

Over the past decade there has been a greatly increased focus on the safety evaluation of medical products. Safety data are routinely collected throughout preclinical in-vitro and in-vivo experiments (e.g., living cells and animal models), clinical development (e.g., randomized clinical trials) and post-approval studies and monitoring. While the majority of clinical studies are designed to investigate the hypothesized efficacy of a compound, safety outcomes, on the other hand, are not generally defined a priori (with exceptions to be discussed in the short course). This brings a number of challenges to statisticians on how to best analyze the high-dimensional safety data, in order to detect safety signals earlier, and at the same time, reduce the rates of false signals and false non-signals. Depending on the questions of interest and the systems for collecting safety data, statistical methods applied to safety data analysis could differ dramatically. This one-day short course will present the commonly used, as well as the cutting-edge statistical methods that are tailored for specific objectives and data types for safety signal detection and benefit-risk assessment. Some frequently encountered issues and challenges in safety data analysis are discussed. Examples are given throughout the presentation of the statistical methods.


Authors who are presenting talks have a * after their name.

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