Artificial Intelligence (AI) is transforming drug discovery by enabling faster identification and optimization of potential drug candidates. Machine learning, predictive analytics, and computational models help researchers analyze complex biological and chemical data, reducing both development time and costs. Computational pharmacology supports virtual screening, drug-target interaction studies, toxicity prediction, and pharmacokinetic analysis before clinical testing. AI also enhances personalized medicine by identifying therapies best suited to individual patients. The integration of big data, cloud computing, and automation is improving research efficiency and accelerating pharmaceutical innovation. These advancements are shaping the future of safer, more effective, and data-driven drug development.
