AI pharmaceuticals have greatly shortened the R&D time, and more than 60 local AI pharmaceutical companies have entered the market

【Pharmaceutical Network Market Analysis】Data show that the birth of a new drug usually requires an investment of at least $1 billion + more than 10 years of research and development cycle, but the success rate is less than 10%.

With the rapid development of AI technology and the continuous expansion and maturity of application scenarios, AI technology is gradually penetrating into the field of biopharmaceuticals, which is expected to change the problems of long R&D time, high cost, low efficiency and high risk of traditional pharmaceuticals, and bring major changes
to the new drug industry.
In recent years, the global AI pharmaceutical industry has continued to grow and develop, in China, although China's AI pharmaceutical started late, but in recent years it is also developing very fast, some listed pharmaceutical companies, medical institutions, universities and institutes, Internet giants and start-ups have begun to lay out the AI pharmaceutical track
.
According to statistics, there are currently more than 60 AI pharmaceutical companies in China, including Insilicon, XtalPi and so on
.
Before 2020, there were fewer than 10 AI pharmaceutical companies
in the country.
With more and more companies entering the market and the gradual enhancement of pharmaceutical companies' R&D efforts, the attention of the AI pharmaceutical field continues to rise, and capital continues to bet on this track to accelerate the iteration speed of AI pharmaceutical-related technologies
.
Data show that in 2020, the "first year of China's AI Pharmaceutical", the investment and financing amount of domestic AI Pharma exceeded 3.
1 billion yuan, a year-on-year increase of nearly 7 times
.
Subsequently, China's AI pharmaceutical showed explosive growth, with the investment and financing scale exceeding more than 10 billion, and the financing scale of China's AI pharmaceutical increased to 1.
236 billion US dollars in 2021, a year-on-year increase of 163.
54%.

According to the monitoring of Smart Pharmaceutical, a total of 42 financing events occurred in global AI+ drug research and development in Q3 2022, with a total investment of 1.
247 billion US dollars, of which 12 were in China and 5 were more than 100 million yuan financing
.
It can be seen that the market is full of confidence in the prospects of
this field.
It is worth mentioning that although the prospects of AI pharmaceuticals are widely promising, there are currently no AI R&D drugs successfully listed worldwide, and most AI pharmaceutical companies are still in the stage of exploration and research, and they need to constantly "throw money" in order to achieve the transformation from science to results and promote drugs into the clinical process
.
Some industry insiders pointed out that there are still many challenges in the research and development and application of AI pharmaceuticals, such as insufficient data volume, uneven data quality, low algorithm accuracy, algorithm can not meet needs, etc.
, and breakthroughs in data, algorithms, and computing power are needed in the future
.
At the same time, the lack of compound talents is also a major bottleneck in the development of domestic AI pharmaceuticals, "those who understand computing do not understand pharmaceuticals, those who understand pharmaceuticals do not understand calculations", how to better transform biological problems into computational problems, and then solve them by digital means, can not be separated from the participation of a large number of compound talents, so it is very important
to focus on training such talents.
In the long run, AI pharmaceuticals will be the trend of the times, which is expected to bring greater development space
to new drug research and development.
However, in the short term, AI pharmaceutical companies are facing many of the difficulties mentioned above, and how to promote the development of domestic AI drugs and narrow the gap with foreign countries is a problem
faced by local entry companies.
In addition, the industry also calls for domestic AI pharmaceuticals to be supported by more targeted support policies and regulations at the policy level, and promote the establishment of a supervision, governance and sharing mechanism for pharmaceutical big data; In addition, at the industry-university-research level, AI technology companies, pharmaceutical companies, universities, etc.
need to strengthen cooperation to accelerate the transformation of achievements and cultivate innovative talents
.
Disclaimer: Under no circumstances does the information or opinions expressed in this article constitute investment advice
to anyone.