GuShiio.com ① Dai Lizhong, deputy to the National People’s Congress and chairman of Shengxiang Biotech, suggested convening a special research and demonstration meeting on the transformation of computational medicine technology linked by multiple ministries and commissions to solve the stuck points and blockages of innovative technologies empowering the industry;
③ Dai Lizhong suggested establishing a cooperation platform around the major layout of national innovative drugs; carrying out pilot projects for effective mechanisms for evaluation modeling and simulation of data; setting up special funds to encourage CVC models and increase investment in the field of computational medicine.
Cailian News, March 7 (Reporter Huang Lu)Artificial intelligence has reshaped the medical field at an unprecedented speed and depth, and it has become a global consensus to empower medical research and development and supervision with computational medical technology. Dai Lizhong, a representative of the National People’s Congress and chairman of Shengxiang Biotech (688289.SH), suggested coordinating various forces to build an integrated cooperation platform of “R & D, transformation and application”, focusing on key projects, optimizing the technological innovation evaluation system, and promoting the inclusion of digital evidence into the drug approval system; Encourage capital to strengthen investment in high-risk innovation projects, establish a “China Plan” for the development and application of computational medicine, and lead industrial upgrading.
Dai Lizhong, Representative of the National People’s Congress and Chairman of Shengxiang Biotech
“Computational medicine is a field with deep intersection of disciplines. Although various countries are actively deploying it, it has not yet reached a demonstration effect. my country has formed unique advantages in the research and development of underlying technologies in computational medicine, demonstrating internationally leading technical effectiveness.” Dai Lizhong said that this provides an opportunity for my country’s pharmaceutical innovation to transform from “catching up with the technological gap” to “releasing technological potential.”
He also paid attention to the fact that the total global financing in the AI pharmaceutical sector in 2023 will reach US$3.2 billion, concentrated on leading companies, and the financing round of start-up companies will be extended. Although there are policy and technological opportunities in my country’s “AI+ medical” field, due to insufficient understanding of new technologies, the domestic capital market is affected by factors such as the effectiveness, safety, cost, and profit cycle of AI pharmaceuticals. Corporate financing is polarized and original innovation power is limited. At the same time, there is a game in the property rights of computational medical data. Domestic companies are cautious about international capital due to data security, and technology iteration and commercialization face financial obstacles.
Public data shows that the number of listed healthcare companies in China is 1/3 of that in the United States, the market value is only 1/10 of that in the United States, and the per capita medical expenses are 1/19 of that in the United States. Developed countries in Europe and the United States have adopted a systematic strategy of putting top-level design first, leading by technology platforms, and supporting policy support, and have achieved major breakthroughs. Although my country’s computational medicine layout is leading at the technical level, it is at a stage of initial ecological construction and weak implementation, and the industry is “big but not strong.”
Artificial intelligence subverts the traditional medical research and development model. Dai Lizhong believes that my country should focus on solving stuck points and blockages in the process of transforming technological advantages into industrial capabilities. He put forward suggestions on how to deeply integrate “AI+ pharmaceuticals”, combining several aspects such as technological change needs, lagging evaluation standards, and commercialization difficulties.
Dai Lizhong suggested convening a special research and demonstration meeting on the transformation of computational medicine technology jointly organized by multiple ministries and commissions to solve the stuck points and blockages of innovative technologies empowering the industry. Select key projects to provide financial and policy support, and list them for supervision to form a benchmark demonstration. At the same time, study an artificial intelligence model evaluation system oriented by “clinical demand-drug IP output-industrial value realization” to unblock the path of technological empowerment.
Referring to international experience, focusing on the national innovative drug layout, focusing on the national strategic needs and key common issues in the pharmaceutical industry, and collaborating with the forces of science and technology, health and other departments to build an integrated industrial innovation platform of “R & D-transformation-application”. Through policies such as tax incentives and special funds, we will attract research institutions, enterprises and social capital to participate, carry out targeted basic research and technological transformation, and form the advantages of industrial clusters.
Carry out pilot projects on effective mechanisms for evaluation modeling and simulation of data to promote the inclusion of digital evidence into the drug approval system. Encourage integrated platforms to promote the standardization of evaluation modeling/simulation data, define virtual clinical trial evidence grading standards, and lead the drafting of the “Technical Guidelines for Digital Evidence in Medicine”, promote the acceptance of digital evidence for drug approval, carry out virtual evidence supervision sandbox pilots, and use artificial intelligence Prediction models are used as evidence of product effectiveness or safety, accelerate the output of new technologies, and realize the transformation of the pharmaceutical industry.
Increase investment to create a pharmaceutical innovation ecosystem. The state has jointly established a computational medicine development fund with social capital to focus on supporting high-risk areas such as AI target discovery and improve fault tolerance rates. Support leading enterprises to carry out the CVC model, use various measures to form asset portfolios, and stimulate innovation capabilities. Increase investment in the integration of digital economy and privacy computing technology, build a virtual clinical research institute, explore demonstration applications, ensure data security compliance, realize original innovation in medical research and development, and build a computing medicine highland in China.
