In Silico Estimation of the Safety of Pharmacologically Active Substances Using Machine Learning Methods: A Review

In Silico Estimation of the Safety of Pharmacologically Active Substances Using Machine Learning Methods: A Review

Scientific relevance. Currently, machine learning (ML) methods are widely used in the research and development of new pharmaceuticals. ML methods are particularly important for assessing the safety of pharmacologically active substances early in the research process because such safety assessments s...

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Bibliographic Details
Main Authors: V. V. Poroikov, A. V. Dmitriev, D. S. Druzhilovskiy, S. M. Ivanov, A. A. Lagunin, P. V. Pogodin, A. V. Rudik, P. I. Savosina, O.  A. Tarasova, D. A. Filimonov
Format: Article
Language:Russian
Published: Ministry of Health of the Russian Federation, Federal State Budgetary Institution «Scientific Centre for Expert Evaluation of Medicinal Products» 2023-12-01
Series:Безопасность и риск фармакотерапии
Subjects:
pharmacologically active substances
safety
in silico studies
structure–activity relationship
sar
computer-aided drug design
machine learning
way2drug
Online Access:https://www.risksafety.ru/jour/article/view/397
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