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Applications for estimation of in vivo toxicity point of departure for discovery stage molecule predictive safety assessment

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NIAID Data Ecosystem2026-05-02 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE269501
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Utilization of in vitro (cellular) techniques, like Cell Painting and transcriptomics-based methods could provide powerful tools for risk assessment and regulatory decision-making. However, using these models generates challenges translating in vitro concentrations to corresponding in vivo internal exposures. We tested whether in vivo (rat liver) transcriptional and apical points of departure (PODs) could be accurately predicted from in vitro (rat hepatocyte or human HepaRG) transcriptional PODs or HepaRG Cell Painting PODs using PBPK modeling. We compared two PBPK models, ADMET predictor and the httk R package, and found httk to predict the rat hepatocyte no observed transcriptional effect level (NOTEL)-derived PODs more accurately. Our findings suggest that a rat liver apical and transcriptome POD can be estimated utilizing a combination of in vitro transcriptome-based PODs coupled with PBPK modeling for IVIVE. RNAseq transcriptomics profiling on Rat primary hepatocytes and Human HepaRG after treatments with a set of agrochemicals, with known developmental toxicity endpoints, at multiple doses
创建时间:
2025-06-28
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