Assessing and predicting drug-induced anticholinergic risks: an integrated computational approach.

ABSTRACT: BACKGROUND:Anticholinergic (AC) adverse drug events (ADEs) are caused by inhibition of muscarinic receptors as a result of designated or off-target drug-receptor interactions. In practice, AC toxicity is assessed primarily based on clinician experience. The goal of this study was to evaluate a novel concept of integrating big pharmacological and healthcare data to assess clinical AC toxicity risks. METHODS:AC toxicity scores (ATSs) were computed using drug-receptor inhibitions identified through pharmacological data screening. A longitudinal retrospective cohort study using medical claims data was performed to quantify AC clinical risks. ATS was compared with two previously reported toxicity measures. A quantitative structure-activity relationship (QSAR) model was established for rapid ass

SUBMITTER: Xu D 

PROVIDER: S-EPMC5638173 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature