China AI R&D Conference - Future Drug R&D Trends

Recently, the 2-day China AI Drug Research and Development Conference (CAPR 2023) was held in Shanghai. The conference set up a main forum and 6 sub-forums. From the aspects of how AI affects small molecule drug design, macromolecule drug design, protein design and structure prediction, how it cooperates with molecular dynamics simulation, how it affects disease biology research, etc., the "AI+drug R&D" is fully explained and discussed. Introduced and fully demonstrated the latest application of AI technology, key issues and future prospects.

The conference also demonstrated the complete industrial form of "IT+BT". A number of AI pharmaceutical companies, IT and AI giants participated deeply, and attracted a number of data storage, high-performance GPU, computing power, and database suppliers to participate in the conference or exhibition.

The development of AI is of great help to breaking through the bottleneck of pharmaceutical R&D, speeding up the R&D cycle, and reducing R&D costs. At present, AI has been widely used in the entire pharmaceutical industry chain, especially in the drug discovery stage. Although AI is still immature, it is growing iteratively at an "exponential" rate. Experts predict that in 3 to 5 years, AI will bring the development of the entire pharmaceutical industry from quantitative to qualitative changes.

AI training requires a large amount of real and reliable data, and the quality of the data directly affects the results of later AI training. A large amount of data requires long-term and continuous accumulation in reality. The lack of data has become one of the problems restricting the development of AI.

Shengshi Junlian has successfully built a real antibody library with a level of "300 billion diversity" after two technological breakthroughs since its establishment, and has accumulated high-quality, high-quantity, and verified real antibody libraries for a long time through self-developed projects. data. The company is committed to creating a new data-driven and biology-driven AI application workflow, and establishing a dry-wet combination macromolecular AI drug research and development platform. At present, the company's data-driven and biology-driven AI-assisted "one-key generation" biopharmaceutical optimization technology platform has greatly shortened the development cycle of macromolecular drugs and provided a basis for borderless drug development.

In the future, our ideal is to use AI to build a virtual drug library with unlimited diversity and borders, for which we have been working hard. If you need to know more about our services or are interested in our technology, please feel free to contact our team, welcome to cooperate with us~