Machine learning techniques are increasingly being used to enhance the predictive capability of toxicological risk assessment. Algorithms can process vast amounts of data to identify potential hazards and synthesize information from diverse sources. This leads to more robust risk assessments and the ability to rapidly evaluate new chemicals without extensive in vivo testing.
