Computational Predictions of Nonclinical Pharmacokinetics at the Drug Design Stage

Autor:	Raya Stoyanova, Paul Maximilian Katzberger, Leonid Komissarov, Aous Khadhraoui, Lisa Sach-Peltason, Katrin Groebke Zbinden, Torsten Schindler, Nenad Manevski
Rok vydání:	2023
Předmět:	General Chemical Engineering General Chemistry Library and Information Sciences Computer Science Applications
Zdroj:	Journal of Chemical Information and Modeling. 63:442-458
ISSN:	1549-960X 1549-9596
Popis:	Although computational predictions of pharmacokinetics (PK) are desirable at the drug design stage, existing approaches are often limited by prediction accuracy and human interpretability. Using a discovery data set of mouse and rat PK studies at Roche (9,685 unique compounds), we performed a proof-of-concept study to predict key PK properties from chemical structure alone, including plasma clearance (CLp), volume of distribution at steady-state (Vss), and oral bioavailability (F). Ten machine learning (ML) models were evaluated, including Single-Task, Multitask, and transfer learning approaches (i.e., pretraining with
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fe1198a25fc3989d643be5d494cb673b https://doi.org/10.1021/acs.jcim.2c01134 Zobrazit plný text záznamu