According to the Guojin Securities Research Report, traditional drug research and development has been in a state of “long cycle, high cost, and low success rate”: from target confirmation to final approval, a drug candidate needs to go through sequential processes such as hit discovery, pilot optimization, pre-clinical evaluation, and large-scale clinical trials. The chain relies on massive resources and repeated verification, resulting in an average development cycle of more than 10 years and a total investment of more than 2 billion US dollars for a single drug. The intervention of AI pharmaceuticals is expected to significantly reduce the R&D cycle and expenses: 1. Significantly reduce the R&D cycle. All stages of development can benefit. Among them, the drug discovery stage saves the most significant time, about 70-90%; pre-clinical research can save 50-80%; and clinical research can save 50-60%. 2. Dramatically reduce R&D costs. The participation of AI pharmaceuticals in drug discovery and clinical research is expected to save pharmaceutical companies about 50% of costs, corresponding to a volume of about 54 billion US dollars.

Disclaimer:Webull uses external vendor Google Translation Service for news translations where we endeavour to ensure these are correct, however, we recommend that you please double-check this information accordingly. Webull is not responsible for translation errors or issues.