What future developments are expected in AI-driven toxicology?
As AI technology continues to advance, future developments in toxicology are likely to focus on enhancing the precision and scope of predictive models. Innovations such as transfer learning and reinforcement learning could further improve model accuracy and adaptability to new data. Additionally, the integration of AI with other emerging technologies like omics and high-throughput screening will likely provide deeper insights into toxicological processes and facilitate the development of personalized medicine approaches.
In conclusion, ML and AI hold transformative potential for toxicology, providing innovative solutions to longstanding challenges in the field. While there are hurdles to overcome, the continued development and application of these technologies promise to enhance our ability to predict and mitigate toxicological risks effectively.
