What Are the Future Directions for QSAR Models in Toxicology?
The future of QSAR models in toxicology looks promising, with ongoing research focusing on:
Integration with omics data: Combining QSAR models with genomics, proteomics, and metabolomics data to enhance predictive accuracy. Artificial intelligence: Leveraging AI and machine learning techniques to develop more sophisticated and accurate models. Big data: Utilizing large-scale datasets to improve model training and validation. Regulatory acceptance: Gaining broader acceptance and use of QSAR models in regulatory decision-making processes.
