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MegaTrans-machine learning models for drug transporters corresponding to the FDA guidance.

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Bibliographic Details
Title: MegaTrans-machine learning models for drug transporters corresponding to the FDA guidance.
Authors: Vignaux PA; Collaborations Pharmaceuticals Inc., Raleigh, North Carolina., Tojong M; Collaborations Pharmaceuticals Inc., Raleigh, North Carolina., Kyu A; Collaborations Pharmaceuticals Inc., Raleigh, North Carolina., Martinez-Guerrero LJ; College of Pharmacy, Department of Pharmacology & Toxicology, University of Arizona, Tucson, Arizona., Harris JS; Collaborations Pharmaceuticals Inc., Raleigh, North Carolina., Lane TR; Collaborations Pharmaceuticals Inc., Raleigh, North Carolina., Wright SH; College of Pharmacy, Department of Pharmacology & Toxicology, University of Arizona, Tucson, Arizona; College of Medicine, Department of Physiology, University of Arizona, Tucson, Arizona., Cherrington NJ; College of Pharmacy, Department of Pharmacology & Toxicology, University of Arizona, Tucson, Arizona., Ekins S; Collaborations Pharmaceuticals Inc., Raleigh, North Carolina. Electronic address: sean@collaborations.com.
Source: Drug metabolism and disposition: the biological fate of chemicals [Drug Metab Dispos] 2026 May; Vol. 54 (5), pp. 100293. Date of Electronic Publication: 2026 Apr 06.
Publication Type: Journal Article
Journal Info: Publisher: American Society for Pharmacology and Experimental Therapeutics, etc.] Country of Publication: Netherlands NLM ID: 9421550 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1521-009X (Electronic) Linking ISSN: 00909556 NLM ISO Abbreviation: Drug Metab Dispos Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1521-009X
DOI:10.1016/j.dmd.2026.100293