1.
CPT Pharmacometrics Syst Pharmacol
; 9(3): 129-142, 2020 03.
Article
in English
| MEDLINE
| ID: mdl-31905263
ABSTRACT
Artificial intelligence, in particular machine learning (ML), has emerged as a key promising pillar to overcome the high failure rate in drug development. Here, we present a primer on the ML algorithms most commonly used in drug discovery and development. We also list possible data sources, describe good practices for ML model development and validation, and share a reproducible example. A companion article will summarize applications of ML in drug discovery, drug development, and postapproval phase.