AI helps drug research and development reduce costs and increase efficiency.”AI+ medical” industry has explosive growth opportunities

China Post Securities pointed out that the global market size of artificial intelligence solutions in the “AI+ medical” industry is expected to increase from US$13.7 billion in 2022 to US$155.3 billion in 2030, with a CAGR of 35.5%. There are explosive growth opportunities in the industry.

According to reports, the reporter interviewed a number of pharmaceutical companies and learned that AI technology has successfully achieved “cost reduction and efficiency improvement” in the early research and development stage of innovative drugs. The application value is reflected in shortening the research and development cycle, saving costs, and improving the probability of trial success.

China Post Securities pointed out that the global market size of artificial intelligence solutions in the “AI+ medical” industry is expected to increase from US$13.7 billion in 2022 to US$155.3 billion in 2030, with a CAGR of 35.5%. There are explosive growth opportunities in the industry. In terms of policy, domestic macro policies are favorable for AI pharmaceuticals, and the approval of three types of medical AI certificates is accelerating. “AI+ medical” has significant advantages over traditional medicine research and development. By building a moat in the closed-loop algorithm + data + clinical scenarios, the “AI+ medical” segment enjoys a valuation premium. “AI+ medical” is expected to be used in drug research and development, cancer diagnosis, medical imaging, surgical robots and other fields, and the industry may usher in tremendous changes.

According to the Cailian theme library, among the relevant listed companies:

Jiuzhou pharmaceuticalDuring the drug research and development process, AI is used to analyze basic data of compounds to predict compound solubility, stability, and crystallization behaviors, effectively shortening the research and development cycle and improving research and development efficiency.

near-shore proteinProactively deeply integrates AI tools such as AlphaFold with the company’s self-developed machine learning system, and is widely used in the innovative design, modification and expression of enzymes, antibodies and other proteins, as well as antibody affinity and stability modification of phage libraries and other technical fields.

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