The Future of Drug Discovery: AI and Machine Learning in Life Sciences Research

After enrichment with chemical and biochemical techniques, the protein targets are identified through proteomics approaches. The final step is to validate the target information via SPR, MST, ITC, etc., and the corresponding pharmacological effects with the appropriate biological function assays. Identifying and validating biological targets is one of the primary steps in drug discovery. AI-driven algorithms can process massive datasets, including genetic information, proteomics, and clinical trial data, to identify potential targets that may respond to specific drug interventions. ML models help determine the viability of a target by analyzing its interactions within biological pathways.