In silico techniques in toxicology are continually evolving with advancements in technology and data science. The integration of machine learning and artificial intelligence is enhancing the predictive power of these models. Moreover, the development of comprehensive databases and more sophisticated algorithms is improving the accuracy and reliability of in silico predictions. Collaborative efforts among regulatory bodies, academia, and industry are also driving the standardization and validation of these methods.
