In Silico Approach to Predict Severe Cutaneous Adverse Reactions Using the Japanese Adverse Drug Event Report Database.

ABSTRACT: Severe cutaneous adverse reactions (SCARs), such as Stevens-Johnson syndrome/toxic epidermal necrolysis and drug-induced hypersensitivity syndrome, are rare and occasionally fatal. However, it is difficult to detect SCARs at the drug development stage, necessitating a new approach for prediction. Therefore, in this study, using the chemical structure information of SCAR-causative drugs from the Japanese Adverse Drug Event Report (JADER) database, we tried to develop a predictive classification model of SCAR through deep learning. In the JADER database from 2004 to 2017, we defined 185 SCAR-positive drugs and 195 SCAR-negative drugs using proportional reporting ratios as the signal detection method, and the total number of reports. These SCAR-positive and SCAR-negative drugs were randomly d

SUBMITTER: Ambe K 

PROVIDER: S-EPMC7993315 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature