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Predicting Adverse Event Risks and Gaining Insights from Disparate Data
Posted on May 17th, 2017 by Neal Katz in Pharma R&D
The upcoming Bio IT World Conference and Expo will feature two talks from Elsevier Life Sciences consultants, focusing on predicting adverse events in clinical trials and extracting knowledge from multiple data sets.
If you plan on attending the conference (May 23-25 at Boston’s Seaport World Trade Center), please be sure to attend these informative sessions, and if you’re not attending look out for updates on this blog:
Wednesday May 24th, 12:40pm
Luncheon Presentation I: Towards the use of bioassays as predictors of adverse events in clinical trials
Matthew Clark, Ph.D., Consultant Research & Development Solutions, Elsevier
To reduce clinical trial failures we have studied how inexpensive bioassays can predict adverse event risks in clinical trials. We used data from FDA submissions and bioactivities from journals and patents to create 2×2 contingency tables for each target/event combination. The relationships were then studied with pathway analysis to understand the models.
To find out how this image of connected relationships among drugs, targets, and diseases related to cholestasis was created, attend this discussion.
Wednesday May 24th, 5:00pm
Transforming Disparate Data into Collective Insights
Frederik van den Broek, Ph.D., Consultant, Research & Development Solutions, Elsevier
Gregory Landrum, Ph.D., Vice President, Life Sciences, KNIME.com AG
Big data in R&D is simply today’s data. Efficiently and reproducibly learning from this data requires us to combine different types of information from various sources and to apply advanced analytics and visualisation to the resulting data set(s) using integrated workflow and analytics platforms.
This talk will present use cases showing how one can obtain these insights which are vital for R&D decision-making in today’s competitive drug discovery environment.
All opinions shared in this post are the author’s own.
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