Chronic and acute eco-toxicity modeling of carcinogenic and hazardous air pollutants toward humans for critical risk assessment and regulatory decision-making

Abstract

Rapid and regular exposure to carcinogenic, toxic, and hazardous chemicals in humans and other living organisms can cause serious chronic (long-term) and acute (short-term) health issues. Since in-vitro and in-vivo toxicity testing requires a long time, a large number of animal experiments, and a high cost, in-silico toxicity testing is the best alternative supported by various regulatory organizations. In our current work, multiple regression-based Quantitative structure–activity relationship models (two chronic toxicity models, a QAAR (quantiative activity-activity relationship) model (chronic studies), and seven acute toxicity models) have been developed to assess the chronic and acute toxicities of carcinogenic chemicals toward humans rigorously following the OECD principles. Statistical validation metrics (R² = 0.604–0.990, Q²_LOO = 0.558––0.988, Q²_F1 = 0.580–0.990, Q²_F2 = 0.503–0.988, MAE_test = 0.103–0.766) demonstrated the robustness, reliability, reproducibility, and predictivity of the developed models. The developed models were utilized to screen the PPDB database, and their predictions were validated against real-world data to confirm their predictive accuracy and reliability. Thus, the present work will significantly aid in bridging the chronic and acute toxicity data gap, identifying carcinogenic chemicals, screening various chemical databases, and developing safer (from observed bio-marker), non-carcinogenic, and greener chemicals strictly obeying the reduction, refinement, and replacement (3Rs) guidelines.