What Does the Future Hold for Machine Learning in Toxicology?
The future of ML in toxicology is promising, with potential advancements in several areas:
Personalized Toxicology: ML could enable personalized risk assessments based on individual genetic profiles and exposure histories. High-throughput Screening: Integrating ML with high-throughput screening technologies could accelerate the identification of toxic compounds. Regulatory Science: As ML models become more robust and interpretable, they could play a more significant role in regulatory science, guiding policy and decision-making.
