Use of Patient Health Records to Quantify Drug-Related Pro-arrhythmic Risk.

ABSTRACT: There is an increasing expectation that computational approaches may supplement existing human decision-making. Frontloading of models for cardiac safety prediction is no exception to this trend, and ongoing regulatory initiatives propose use of high-throughput in vitro data combined with computational models for calculating proarrhythmic risk. Evaluation of these models requires robust assessment of the outcomes. Using FDA Adverse Event Reporting System reports and electronic healthcare claims data from the Truven-MarketScan US claims database, we quantify the incidence rate of arrhythmia in patients and how this changes depending on patient characteristics. First, we propose that such datasets are a complementary resource for determining relative drug risk and assessing the perfor

SUBMITTER: Davies MR 

PROVIDER: S-EPMC7659582 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature