| Autor: |
Alan Talevi, Juan Francisco Morales, Gregory Hather, Jagdeep T. Podichetty, Sarah Kim, Peter C. Bloomingdale, Samuel Kim, Jackson Burton, Joshua D. Brown, Almut G. Winterstein, Stephan Schmidt, Jensen Kael White, Daniela J. Conrado |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
CPT: Pharmacometrics & Systems Pharmacology, Vol 9, Iss 3, Pp 129-142 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
2163-8306 |
| DOI: |
10.1002/psp4.12491 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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