ArticleMolecular pharmaceutics2025
Metabolite Identification Data in Drug Discovery, Part 1: Data Generation and Trend Analysis.
Article in Molecular pharmaceutics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- Computational Identification of Active Drug Metabolites for Human Protein Targets.Molecular pharmaceutics · 2026Article
- Stereoselective Biotransformation: Transfer of Learning to Advance Drug Metabolism and Biocatalysis.Angewandte Chemie (International ed. in English) · 2026Review
- Metabolite Identification Data in Drug Discovery, Part 1: Data Generation and Trend Analysis.Molecular pharmaceutics · 2025Article
- Metabolite Identification Data in Drug Discovery, Part 2: Site-of-Metabolism Annotation, Analysis, and Exploration for Machine Learning.Molecular pharmaceutics · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In drug discovery, metabolite identification data are used to identify metabolic soft spots in research molecules to facilitate reduced metabolism in subsequently designed compounds. In addition, knowledge about exact metabolite structures enables the assessment of risks associated with active, reactive, or toxic metabolites. In the present work, we exemplify how metabolite identification data are generated and utilized at AstraZeneca. We share metabolite transformation scheme data derived from incubations in human hepatocytes for a set of 120 compounds. Comparison with other in-house generated metabolite identification data, both in terms of chemical space analysis and
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Registered trials
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