It takes at least 10 years and costs $1 billion to successfully develop a new drug, which is recognized as "double ten laws" in the field of new drug research and development. As new technologies continue to emerge, biomedical companies are trying to break this "law" with the power of artificial intelligence(AI).
Today, Daxing biomedical industry Base in Beijing Zhongguancun Science and Technology Park, known as "China's pharmaceutical Valley", is building an "artificial intelligence +" pharmaceutical innovation ecology, accelerating the process of new drug research and development by improving the success rate and accuracy. It enables the biomedical industry to make progress.
As the main land for the development of Beijing's medical and health industry, Daxing Biomedical Industry Base has actively introduced the cross-integration projects of medical and health, artificial intelligence, and big data, promoting the cutting-edge technologies of life and health in the industry base.
Not long ago, a new addition was introduced to the biomedical base - "X-Gen AI New Drug Discovery and Design Research Center". The platform was established by the park's enterprise Beijing Hotgen Biotech Co., Ltd., to promote the application of AI technology in drug target discovery, drug efficacy screening, drug molecular design and optimization, clinical trial design and management, drug relocation and so on. Sungen Biomedical and Youngen Gene, two high-tech enterprises under Hotgen Biotech, accelerate the R&D process with the help of AI by improving the success rate of experiments and clinical trials.
Xu Lida, director of the research center, said that the research of innovative drugs and new targets is the key, and the use of AI to search for massive multi-omics data can help to find new mechanisms of action to treat diseases. For the new target, "according to the shape of the 'keyhole', the 'key' can be designed using AI or biological computing methods." With the "key", "semi-finished product", and optimization, the "key" can match the "keyhole" more accurately, which is "affinity mature". "These two paths complement each other and can help us find the most suitable 'key' faster," Xu said.
In antibody molecular optimization, they have used calculations to assist antibody affinity maturation, effectively predict key amino acids, and use these predictions to guide antibody directed mutations that can improve affinity 10-fold within 2 months. With the support of AI, the development efficiency of nucleic acid drugs is higher, and the design and screening of nucleic acid sequences can be completed in 8 hours. At present, Sungen's first innovative drug developed by AI for cardiovascular and cerebrovascular diseases is about to enter the clinic.
The research center that discovered and designed the new drug has both wet and dry laboratories. Wet laboratory refers to the traditional biological laboratory, with a variety of reagents and experimental operations. Dry laboratory refers to the use of computers. After the computer results are repeatedly verified in the wet experiment, the product is further optimized and developed on the computer with the help of AI.
The research of new drugs with AI is interdisciplinary and requires R&D personnel with professional backgrounds such as information science, pharmaceutical engineering, and biotechnology. "Four years ago, we recognized that AI technology is a very important accelerator and began to build a team to do research while polishing algorithms, models, and processes.
Now we have got a taste of how AI can improve success rates." Said by Lin Changqing, chairman of Hotgen, AI technology has become the best "assist" for many industries to achieve accelerated development.
(Excerpt from Economic Daily)
Updated: Jul 24, 2024
