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Kramer, C, Ting, A, Zheng, H, Hert, J, Schindler, T, Stahl, M, Robb, G, Crawford, JJ, Blaney, J, Montague, S, Leach, AG, Dossetter, AG and Griffen, EJ (2017) Learning Medicinal Chemistry Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) Rules from Cross-Company Matched Molecular Pairs Analysis (MMPA). Journal of Medicinal Chemistry. ISSN 0022-2623
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Abstract
The first large scale analysis of in vitro absorption, distribution, metabolism, excretion, and toxicity (ADMET) data shared across multiple major pharma has been performed. Using advanced matched molecular pair analysis (MMPA), we combined data from three pharmaceutical companies and generated ADMET rules, avoiding the need to disclose the full chemical structures. On top of the very large exchange of knowledge, all companies involved synergistically gained approximately 20% more rules from the shared transformations. There is good quantitative agreement between the rules based on shared data compared to both individual companies' rules and rules published in the literature. Known correlations between log D, solubility, in vitro clearance, and plasma protein binding also hold in transformation space, but there are also interesting exceptions. Data pools such as this allow focusing on particular functional groups and characterizing their ADMET profile. Finally the role of a corpus of robustly tested medicinal chemistry knowledge in the training of medicinal chemistry is discussed.
| Item Type: | Article |
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| Uncontrolled Keywords: | 0304 Medicinal And Biomolecular Chemistry, 1115 Pharmacology And Pharmaceutical Sciences, 0305 Organic Chemistry |
| Subjects: | Q Science > QD Chemistry R Medicine > R Medicine (General) |
| Divisions: | Pharmacy & Biomolecular Sciences |
| Publisher: | American Chemical Society |
| Related URLs: | |
| Date Deposited: | 05 Oct 2017 09:39 |
| Last Modified: | 04 Sep 2021 03:46 |
| DOI or ID number: | 10.1021/acs.jmedchem.7b00935 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/7283 |
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