CITIC Construction Investment pointed out that the AI pharmaceutical field is undergoing rapid iteration and transformation. The updated iterations of algorithms and support for computing power have laid a good technical foundation for the application of AI in the pharmaceutical field. The traditional drug development process takes a long time, is expensive, and the success rate is low. As new drugs with existing targets are approved one after another, the difficulty of developing new drugs gradually increases. At present, AI has shown efficiency value in early stages such as structure prediction, target screening, virtual screening, molecular generation, and multi-parameter optimization. It is expected to reduce the range of candidate molecules, reduce low-value experiments, and reduce the discovery cost of a single qualified hit. Increased investment in related dry experiments and continued growth in demand for wet experiments are expected to continue to increase the downstream industrial chain.

CITIC Construction Investment pointed out that the AI pharmaceutical field is undergoing rapid iteration and transformation. The updated iterations of algorithms and support for computing power have laid a good technical foundation for the application of AI in the pharmaceutical field. The traditional drug development process takes a long time, is expensive, and the success rate is low. As new drugs with existing targets are approved one after another, the difficulty of developing new drugs gradually increases. At present, AI has shown efficiency value in early stages such as structure prediction, target screening, virtual screening, molecular generation, and multi-parameter optimization. It is expected to reduce the range of candidate molecules, reduce low-value experiments, and reduce the discovery cost of a single qualified hit. Increased investment in related dry experiments and continued growth in demand for wet experiments are expected to continue to increase the downstream industrial chain.