Development of hybrid models by the integration of the read-across hypothesis with the QSAR framework for the assessment of developmental and reproductive toxicity (DART) tested according to OECD TG 414

• Published in: Toxicology reports 2024-12, Vol.13, p.101822, Article 101822
• Main Authors: Pandey, Sapna Kumari, Roy, Kunal
• Format: Article
• Language: English
• Subjects: adults; animals; computer simulation; DART; hazard identification; hybrids; NAMs; NGRA; QSAR; quantitative structure-activity relationships; Read-across; reproductive toxicology; Testing guidelines; toxicity
• ISSN: 2214-7500; 2214-7500
• DOI: 10.1016/j.toxrep.2024.101822

The governing laws mandate animal testing guidelines (TG) to assess the developmental and reproductive toxicity (DART) potential of new and current chemical compounds for the categorization, hazard identification, and labeling. In silico modeling has evolved as a promising, economical, and animal-friendly technique for assessing a chemical's potential for DART testing. The complexity of the endpoint has presented a problem for Quantitative Structure-Activity Relationship (QSAR) model developers as various facets of the chemical have to be appropriately analyzed to predict the DART. For the next-generation risk assessment (NGRA) studies, researchers and governing bodies are exploring various new approach methodologies (NAMs) integrated to address complex endpoints like repeated dose toxicity and DART. We have developed four hybrid computational models for DART studies of rodents and rabbits for their adult and fetal life stages separately. The hybrid models were created by integrating QSAR features with similarities-derived features (obtained from read-across hypotheses). This analysis has identified that this integrated method gives a better statistical quality compared to the traditional QSAR models, and the predictivity and transferability of the model are also enhanced in this new approach. [Display omitted] •Four Hybrid models are developed for developmental and reproductive toxicity (DART) data.•The DART data of rodents and rabbits' adult and fetal life stages are used.•The hybrid models combine physicochemical and similarity-based features.•The hybrid modeling strategy enhances model quality and prediction.•The developed hybrid models can utilize a potential substitute approach for evaluating DART toxicity.