Predicting Prenatal Developmental Toxicity Based On the Combination of Chemical Structures and Biological Data.

ABSTRACT: For hazard identification, classification, and labeling purposes, animal testing guidelines are required by law to evaluate the developmental toxicity potential of new and existing chemical products. However, guideline developmental toxicity studies are costly, time-consuming, and require many laboratory animals. Computational modeling has emerged as a promising, animal-sparing, and cost-effective method for evaluating the developmental toxicity potential of chemicals, such as endocrine disruptors, without the use of animals. We aimed to develop a predictive and explainable computational model for developmental toxicants. To this end, a comprehensive dataset of 1244 chemicals with developmental toxicity classifications was curated from public repositories and literature sources. Data from

SUBMITTER: Ciallella HL 

PROVIDER: S-EPMC9191745 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature