Predicting the Addition of Information Regarding Clinically Significant Adverse Drug Reactions to Japanese Drug Package Inserts Using a Machine-Learning Model.

Takashi WatanabeKaori AmbeMasahiro Tohkin

Published in: Therapeutic innovation & regulatory science (2023)

Our model accurately predicted PI revisions using information on ADR cases that occurred 6 months before. This is the first ML model that can predict the necessary safety measures and is an efficient method for guiding the decision to adopt additional safety measures early.

Keyphrases

adverse drug
machine learning
emergency department
electronic health record
artificial intelligence
drug induced
deep learning
big data