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• W2885164266 abstract "Broad toxicology profiling takes traditionally place at the interface between discovery and development when a potential drug candidate is selected. However, it would be both time- and cost-wise better if mechanism (target)-related toxicity and compound-chemistry-related toxicity are addressed earlier, when discussions on novel drug targets take place and compound series are identified and optimized. As the traditional in vivo and in vitro toxicity testing is rather low throughput, they cannot be used in these early stages of the drug discovery process. Therefore a paradigm shift in toxicity testing needs to take place to move to high-throughput cell-based assays to reveal key pathways and proteins linked with toxicity endpoints. In this proof-of-concept work, we explore both transcriptional profiling and imaging techniques to flag early potential toxicity issues. We provide findings of an in-depth exploration of a single chemical core structure. A subset of close analogs was identified via transcriptional profiling, which commonly downregulate multiple tubulin genes across cellular contexts, suggesting possible spindle poison effects. The biological relevance of the finding was confirmed by two different approaches: firstly, high content imaging using cells endogenously tagged with fluorescent tubulin protein genes flagged potential issues via the identification of a characteristic aggregate-formation phenotype. Secondly, a qualified toxicity assay (in vitro micronucleus test) showed increased micronucleus induction for selected compounds showing tubulin downregulation. SAR analysis triggered the synthesis of a new set of compounds and allowed us to extend the series showing the genotoxic effect. This indicates how medicinal chemistry can be guided to dial out undesired effects, thereby optimizing candidate selection. We conclude the chapter by discussing how this approach may be incorporated into state-of-the-art drug development strategies where data integration plays an important role." @default.
• W2885164266 created "2018-08-22" @default.
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• W2885164266 date "2018-08-03" @default.
• W2885164266 modified "2023-10-06" @default.
• W2885164266 title "Addressing Genotoxicity Risk in Lead Optimization: A PDE10A Inhibitor Case Study" @default.
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• W2885164266 doi "https://doi.org/10.1002/9783527801756.ch21" @default.
• W2885164266 hasPublicationYear "2018" @default.
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