According to the latest research report by CITIC Construction Investment, the realm of AI-driven pharmaceuticals is experiencing swift advancement and transformation. Supported by algorithm enhancements and robust computational capabilities, a solid technical framework has been established for its practical applications. Traditional drug development processes are notorious for their lengthy timelines, high costs, and low success rates. With the continuous approval of new drugs targeting existing molecules, the challenge of discovering novel drugs intensifies. Presently, AI has showcased significant efficiency gains in the preliminary phases of drug development, including structural prediction and target identification. It is anticipated to refine the selection of candidate molecules, minimize unnecessary experiments, and reduce the costs associated with identifying individual viable compounds. Heightened investments in dry experiments (computer-based simulations and data analysis), coupled with a steady increase in demand for wet experiments (laboratory-based testing), are poised to drive new growth across the downstream industry chain.