The data presented here support the application of the Stemina devTOXqP platform for predictive toxicology and further demonstrate its value in ToxCast as a novel resource that can generate testable hypotheses aimed at characterizing potential pathways for teratogenicity and HTS prioritization of environmental chemicals for an exposure-based assessment of developmental hazard.

The dataset from the Stemina (STM) assay is annotated in the ToxCast portfolio as STM. Major findings from the analysis of ToxCast_STM dataset include (1) 19% of 1065 chemicals yielded a prediction of developmental toxicity, (2) assay performance reached 79%-82% accuracy with high specificity (> 84%) but modest sensitivity (< 67%) when compared with in vivo animal models of human prenatal developmental toxicity, (3) sensitivity improved as more stringent weights of evidence requirements were applied to the animal studies, and (4) statistical analysis of the most potent chemical hits on specific biochemical targets in ToxCast revealed positive and negative associations with the STM response, providing insights into the mechanistic underpinnings of the targeted endpoint and its biological domain. The results of this study will be useful to improving our ability to predict in vivo developmental toxicants based on in vitro data and in silico models.

This dataset is associated with the following publication: Zurlinden, T., K. Saili, N. Rush, P. Kothiya, R. Judson, K. Houck, E. Hunter, N. Baker, J. Palmer, R. Thomas, and T. Knudsen. Profiling the ToxCast Library With a Pluripotent Human (H9) Stem Cell Line-Based Biomarker Assay for Developmental Toxicity. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 174(2): 189-209, (2020).