ArticleRegulatory toxicology and pharmacology : RTP2020
Management of pharmaceutical ICH M7 (Q)SAR predictions - The impact of model updates.
Article in Regulatory toxicology and pharmacology : RTP, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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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
12 citing papers in PubMed, 32 citations in OpenAlex.
- Potential for Computational Genotoxicity: A Report on Symposium 3 of the 53rd Annual Meeting of the Japanese Environmental Mutagen and Genome Society (JEMS), 2024.Genes and environment : the official journal of the Japanese Environmental Mutagen Society · 2026Article
- Guidelines for the assessment and control of mutagenic impurities in pharmaceuticals.Genes and environment : the official journal of the Japanese Environmental Mutagen Society · 2025Review
- Charged Thienobenzo-1,2,3-Triazoles as Especially Potent Non-Selective Cholinesterase Inhibitors: Design, Anti-Inflammatory Activity, and Computational Study.Pharmaceuticals (Basel, Switzerland) · 2025Article
- Heterostilbene Carbamates with Selective and Remarkable Butyrylcholinesterase Inhibition: Computational Study and Physico-Chemical Properties.Biomolecules · 2025Article
- Revisiting the approaches to DNA damage detection in genetic toxicology: insights and regulatory implications.BioData mining · 2025Article
- Resveratrol-Based Carbamates as Selective Butyrylcholinesterase Inhibitors: Design, Synthesis, Computational Study and Biometal Complexation Capability.Molecules (Basel, Switzerland) · 2025Article
- Bridging science and curriculum: preparing future leaders in computational toxicology.Frontiers in toxicology · 2025Review
- Efficient Access to New Thienobenzo-1,2,3-Triazolium Salts as Preferred Dual Cholinesterase Inhibitors.Biomolecules · 2024Article
- Cholinesterase Inhibition and Antioxidative Capacity of New Heteroaromatic Resveratrol Analogs: Synthesis and Physico-Chemical Properties.International journal of molecular sciences · 2024Article
- New Charged Cholinesterase Inhibitors: Design, Synthesis, and Characterization.Molecules (Basel, Switzerland) · 2024Article
- A local QSAR model based on the stability of nitrenium ions to support the ICH M7 expert review on the mutagenicity of primary aromatic amines.Genes and environment : the official journal of the Japanese Environmental Mutagen Society · 2022Article
- MultiCASE Platform for In Silico Toxicology.Methods in molecular biology (Clifton, N.J.) · 2022Article
Corrections and comments
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Authors and funding
11 authors at 9 institutions in 2 countries.
Funding
Abstract
Pharmaceutical applicants conduct (Q)SAR assessments on identified and theoretical impurities to predict their mutagenic potential. Two complementary models-one rule-based and one statistical-based-are used, followed by expert review. (Q)SAR models are continuously updated to improve predictions, with new versions typically released on a yearly basis. Numerous releases of (Q)SAR models will occur during the typical 6-7 years of drug development until new drug registration. Therefore, it is important to understand the impact of model updates on impurity mutagenicity predictions over time. Compounds representative of pharmaceutical impurities were analyzed with three rule- and three statistical-based models covering a 4-8 year period, with the individual time frame being dependent on when the individual models were initially made available. The largest changes in the combined outcome of two complementary models were from positive or equivocal to negative and from negative to equivocal. Importantly, the cumulative change of negative to positive predictions was small in all models (<5%) and was further reduced when complementary models were combined in a consensus fashion. We conclude that model updates of the type evaluated in this manuscript would not necessarily require re-running a (Q)SAR prediction unless there is a specific need. However, original (Q)SAR predictions should be evaluated when finalizing the commercial route of synthesis for marketing authorization.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.