Artículo
Machine Learning in Drug Discovery and Development Part 1: A Primer
Talevi, Alan
; Morales, Juan Francisco
; Hather, Gregory; Podichetty, Jagdeep T.; Kim, Sarah; Bloomingdale, Peter C.; Kim, Samuel; Burton, Jackson; Brown, Joshua D.; Winterstein, Almut G.; Schmidt, Stephan; White, Jensen Kael; Conrado, Daniela J.
Fecha de publicación:
03/2020
Editorial:
American Society for Clinical Pharmacology and Therapeutics
Revista:
CPT: Pharmacometrics and Systems Pharmacology
ISSN:
2163-8306
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
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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Articulos(CCT - LA PLATA)
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - LA PLATA
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - LA PLATA
Citación
Talevi, Alan; Morales, Juan Francisco; Hather, Gregory; Podichetty, Jagdeep T.; Kim, Sarah; et al.; Machine Learning in Drug Discovery and Development Part 1: A Primer; American Society for Clinical Pharmacology and Therapeutics; CPT: Pharmacometrics and Systems Pharmacology; 9; 3; 3-2020; 129-142
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