Drug discovery and development are intricate processes that traditionally involve numerous costly and time-consuming experimental steps. AI has emerged as a game-changer in this domain, offering a suite of tools and techniques that can significantly expedite the drug design process while reducing costs and enhancing success rates. AI-aided drug design leverages machine learning algorithms, deep learning models, molecular simulations, and big data analytics to streamline various stages of drug discovery, from target identification to lead optimization and pharmacokinetics evaluation.
