Prediction of clinical risks by analysis of preclinical and clinical adverse events

Journal of Biomedical Informatics
Matthew Clark

Abstract

This study examines the ability of nonclinical adverse event observations to predict human clinical adverse events observed in drug development programs. In addition it examines the relationship between nonclinical and clinical adverse event observations to drug withdrawal and proposes a model to predict drug withdrawal based on these observations. These analyses provide risk assessments useful for both planning patient safety programs, as well as a statistical framework for assessing the future success of drug programs based on nonclinical and clinical observations. Bayesian analyses were undertaken to investigate the connection between nonclinical adverse event observations and observations of that same event in clinical trial for a large set of approved drugs. We employed the same statistical methods used to evaluate the efficacy of diagnostic tests to evaluate the ability of nonclinical studies to predict adverse events in clinical studies, and adverse events in both to predict drug withdrawal. We find that some nonclinical observations suggest higher risk for observing the same adverse event in clinical studies, particularly arrhythmias, QT prolongation, and abnormal hepatic function. However the lack of these events in no...Continue Reading

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Citations

Sep 16, 2015·Journal of Biomedical Informatics·Zhengxing HuangHuilong Duan
Jan 10, 2018·Basic & Clinical Pharmacology & Toxicology·Thomas Steger-Hartmann, Francois Pognan
Jul 11, 2020·BMC Medical Informatics and Decision Making·Ming ChengYafeng Ren
Oct 18, 2020·British Journal of Clinical Pharmacology·Sören SieversDaniel Strech
Sep 2, 2021·Drug Discovery Today·Lap Hing ChiRobin L Anderson

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