Machine learning in drug discovery and development part 1: a primer
A Talevi, JF Morales, G Hather… - CPT …, 2020 - Wiley Online Library
CPT: pharmacometrics & systems pharmacology, 2020•Wiley Online Library
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.
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.
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.
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