Events

DSECT/DSEN Monthly Seminar Series - Apr 28, 2016

“Leveraging post-market big data using integrative statistical methods: advancing drug safety and effectiveness research”

Presented by
Joseph Beyene1, Mateen Shaikh2, and Ashley Bonner3 

1Professor of Biostatistics, 2Post-doctoral Fellow, 3PhD Candidate
Department of Clinical Epidemiology & Biostatistics, McMaster University

Thursday, April 28th at 3-4pm EST

Online via GoToWebinar

 

Abstract:

Knowledge gained about drug safety and effectiveness from controlled environments (e.g. clinical trials), although essential, does not provide a complete picture of the impact of drugs in the larger population. Post-market research can fill this gap by tracking unexpected adverse events associated with particular drugs and drug combinations, as well as measuring new biological sources that may better indicate drug toxicity. Such data sources are massive in size and pose significant analytical challenges. We illustrate integrative statistical methods applied on these types of massive data in post-market research to gain insight into drug toxicity and underlying biological mechanisms.

Learning Objectives:

  1. To demonstrate the application of association rules to mine adverse event reporting databases.
  2. To illustrate the use of novel sparse multivariate statistical methods to uncover cross-correlations in toxicogenomics data.
  3. To highlight challenges in high-dimensional drug safety data analysis.

Resources:

Shaikh M.  Beyene J. Testing genotypes-phenotype relationships using permutation tests on association rules. Statistical applications in genetics and molecular biology 14.1 (2015): 83-92.

Bonner A.  Beyene J. Detecting networks of genes associated with human drug induced liver injury (DILI) concern using sparse principal components. Systems Biomedicine, 2(1), (2014) e29413.

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