Despite the benefits, the integration of big data and AI in toxicology comes with challenges. Data quality and consistency remain significant issues as toxicological data can be heterogeneous, incomplete, or biased. Additionally, there is a need for transparent and explainable AI models to build trust among stakeholders. Ethical considerations, including data privacy and the potential for algorithmic bias, must also be addressed.
