Discovery Phase Agrochemical Predictive Safety Assessment Using High Content In Vitro Data to Estimate an In Vivo Toxicity Point of Departure.

Utilization of in vitro (cellular) techniques, like Cell Painting and transcriptomics, could provide powerful tools for agrochemical candidate sorting and selection in the discovery process. However, using these models generates challenges translating in vitro concentrations to the corresponding in vivo exposures. Physiologically based pharmacokinetic (PBPK) modeling provides a framework for quantitative in vitro to in vivo extrapolation (IVIVE). We tested whether in vivo (rat liver) transcriptomic and apical points of departure (PODs) could be accurately predicted from in vitro (rat hepatocyte or human HepaRG) transcriptomic PODs or HepaRG Cell Painting PODs using PBPK modeling. We compared two PBPK models, the ADMET predictor and the httk R package, and found httk to predict the in vivo PODs more accurately. Our findings suggest that a rat liver apical and transcriptomic POD can be estimated utilizing a combination of in vitro transcriptome-based PODs coupled with PBPK modeling for IVIVE. Thus, high content in vitro data can be translated with modest accuracy to in vivo models of ultimate regulatory importance to help select agrochemical analogs in early stage discovery program.

Applications of Zebrafish Embryo Models to Predict Developmental Toxicity for Agrochemical Product Development.

The development of safe crop protection products is a complex process that traditionally relies on intensive animal use for hazard identification. Methods that capture toxicity in early stages of agrochemical discovery programs enable a more efficient and sustainable product development pipeline. Here, we explored whether the zebrafish model can be leveraged to identify mammalian-relevant toxicity. We used transgenic zebrafish to assess developmental toxicity following exposures to known mammalian teratogens and captured larval morphological malformations, including bone and vascular perturbations. We further applied toxicogenomics to identify common biomarker signatures of teratogen exposure. The results show that the larval malformation assay predicted teratogenicity with 82.35% accuracy, 87.50% specificity, and 77.78% sensitivity. Similar and slightly lower accuracies were obtained with the vascular and bone assays, respectively. A set of 20 biomarkers were identified that efficiently segregated teratogenic chemicals from nonteratogens. In conclusion, zebrafish are valuable, robust, and cost-effective models for toxicity testing in the early stages of product development.