The explosive growth in medical devices, imaging and diagnostics, computing, and
communication and information technologies in drug development and healthcare has …

Drug–drug interactions (DDIs) constitute an important concern in drug development and
postmarketing pharmacovigilance. They are considered the cause of many adverse drug …

Objective To summarize applications of natural language processing (NLP) in model
informed drug development (MIDD) and identify potential areas of improvement. Materials …

This paper examines the transformative impact of artificial intelligence (AI) on
pharmacogenomics, signaling a paradigm shift in personalized medicine. With a focus on …

Ecology and evolutionary biology, like other scientific fields, are experiencing an
exponential growth of academic manuscripts. As domain knowledge accumulates, scientists …

The objective of this article is to review the application of informatics-driven approaches in
the pharmacovigilance field with focus on drug-drug interaction (DDI) safety signal discovery …

Introduction The integration of artificial intelligence (AI) into clinical pharmacology could be a
potential approach for accelerating drug discovery and development, improving patient care …

Pharmacovigilance (PV) databases record the benefits and risks of different drugs, as a
means to ensure their safe and effective use. Creating and maintaining such resources can …

Biocuration is a time-intensive process that involves extraction, transcription, and
organization of biological or clinical data from disjointed data sets into a user-friendly …

Polypharmacy increases the risk of drug–drug interactions (DDIs). Combining
epidemiological studies with pharmacokinetic modeling, we detected and evaluated high …