There is a "double ten law" in the pharmaceutical industry, that is, the average cost of a new drug from research and development to the market is more than 1 billion US dollars, and the research and development cycle is greater than 10 years
.
But even so, only about 10% of new drugs can be approved into the clinical stage
.
However, it is worth noting that there have been recent reports that a team of the First Affiliated Hospital of Xi'an Jiaotong University has adopted an AI-assisted drug design service based on the large model of Huawei Cloud Pangu drug molecules in the work of antibiotic research and development, and has made a breakthrough in the development of super antibacterial drugs, breaking through the "double ten law" of the pharmaceutical industry - shortening the research and development cycle of pilot drugs from several years to one month, and reducing research and development costs by 70%.
Recently, the drug has been patented internationally and is undergoing a preclinical research phase supporting IND (Clinical Research Approval for New Drugs) filing
.
In this regard, the industry believes that this is the performance of artificial intelligence in the industrial upgrading of the pharmaceutical field, which is playing a key role, and the application of artificial intelligence technology is gradually shortening the research and development cycle
of scientific research teams.
It is understood that one of the key problems that has been facing the new drug R&D personnel is the screening of massive drug molecules
.
Under the unsupervised learning mode and the "graph-sequence asymmetrical condition autoencoder" deep learning network architecture, the HUAWEI CLOUD Pangu Drug Molecule Big Model has pre-learned the chemical structure of 1.
7 billion small molecules and received massive training to better predict and recommend
the molecular structure and properties.
In fact, in recent years, with the help of artificial intelligence and AI to accelerate innovation and research and development, it is not surprising in the pharmaceutical track
.
Since 2022, a number of listed pharmaceutical companies have reported that they have cooperated with technology companies to accelerate their entry into the field of AI drug research and development
.
For example, on July 25, Yunnan Baiyao announced that the company signed a comprehensive cooperation agreement on artificial intelligence drug research and development with Huawei on the 23rd
.
According to the agreement, the two sides will carry out exchanges and cooperation in the field of artificial intelligence drug research and development, including but not limited to large and small molecule design, related diseases, database development, etc
.
In June, Haizheng Pharmaceutical and Jingtai Technology, a drug research and development technology company driven by intelligent and automated technology, joined hands again to further expand their cooperation
in the field of chemical synthesis.
It is reported that Xtal has an automated experimental technology platform and compound management platform, which can provide flexible intelligent chemical synthesis services, which will continue to help Haizheng Pharmaceutical explore drug synthesis pathways and methods with higher efficiency and accelerate the drug research and development process
.
At the beginning of this year, the two sides launched their first chemical synthesis project
.
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.
.
.
.
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In addition to domestic pharmaceutical companies, multinational pharmaceutical companies are also accelerating their development with the help of
artificial intelligence.
Previously, PathAI and GlaxoSmithKline (GSK) jointly announced that they had reached a multi-year strategic research and development collaboration that would leverage PathAI's digital pathology technology platform, including its AIM-NASH tool, to accelerate scientific research and drug development projects
in oncology and non-alcoholic steatohepatitis (NASH).
On the whole, with the continuous development of science and technology, more and more companies and researchers have begun to apply "artificial intelligence" to pharmaceutical research and development and marketing
.
Trying to further improve the success rate of new drug research and development through artificial intelligence technology AI algorithms, reduce manufacturing costs and research and development time
.
From this time, artificial intelligence-assisted super antibacterial drug research and development, cost reduction of 70%, the industry is expected to see more AI company milestones delivered in 2022-2023, and more research projects will be promoted to clinical phase
I.
