Under the boom of pharmaceutical companies in AI pharmaceuticals, these problems need to be solved urgently!

【Pharmaceutical Network Market Analysis】In recent years, capital is continuing to increase the AI+ pharmaceutical field to inject impetus
into the industry.
According to data, in 2021, China's AI pharmaceutical financing scale has reached 1.
236 billion US dollars, a year-on-year increase of 163.
54%.

At present, the pharmaceutical field is still paying more and more attention to AI
.
Not only multinational pharmaceutical companies such as Pfizer and Novo Nordisk; Local technology companies and pharmaceutical companies have successively introduced a number of policies in China to support the innovation and development of artificial intelligence and pharmaceutical industries, and encourage the next generation of information technology to empower pharmaceutical research and development, and are also pouring into the AI+ pharmaceutical track
.
Under the boom of pharmaceutical companies in AI pharmaceuticals, these problems need to be solved urgently! (Image source: Pharmaceutical Network) A large number of pharmaceutical companies are deploying AI pharmaceuticals For example, recently, AI pharmaceutical company Insilico announced that it has reached a drug research and development cooperation
with the multinational pharmaceutical company Sanofi.
Under the agreement, the latter will be required to pay Insilico an aggregate upfront payment of up to US$21.
5 million in advance and target discovery costs, additional R&D and commercial milestone payments, with a total potential value of up to US$1.
2 billion
.
On July 25, Yunnan Baiyao announced that the company will cooperate with Huawei to carry out extensive exchanges and cooperation in the field of artificial intelligence drug research and development, explore mechanisms for joint scientific research and innovation, and expand the breadth and depth of cooperation between the two sides, including but not limited to large and small molecule design, related diseases, database development, etc
.
In June, Hisun Pharmaceutical and XtalPi also joined hands again, further expanding the cooperation
between the two parties in the field of chemical synthesis.
It is reported that XtalPi has an automated experimental technology platform and compound management platform, which can provide flexible intelligent chemical synthesis services, which will continue to help Hisun Pharmaceutical explore drug synthesis pathways and methods with higher efficiency and accelerate the process of
drug research and development.
At the beginning of this year, the two sides launched their first chemical synthesis project
.
.
.
.
.
.
.
According to "Global AI Pharmaceuticals Enter a New Stage", from the initial computer-aided drug design (CADD) to today's artificial intelligence drug discovery (AIDD), AI has now been involved in almost the entire process
from drug target discovery to clinical trials.
Domestic AI pharmaceuticals are hot, but these problems still need to be solved On the whole, although China's AI pharmaceutical field started late, in recent years, thanks to the encouragement of macro policies for AI technology and innovative drug research and development, as well as the rapid development of the AI field and the continuous attention of the capital market, China's AI pharmaceutical field space is gradually opening
.
Analysts predict that the proportion of the innovative drug market in the overall pharmaceutical market may reach 15% in the future, and the compound growth rate from 2021 to 2026 will reach 16.
1%, and affected by this, the potential market space of AI pharmaceuticals in 2026 is expected to reach 364.
3 billion yuan.

However, it should be noted that although the development prospects of AI pharmaceuticals are widely optimistic, there has been no successful listing of AI drugs in the world, and most AI pharmaceutical companies are still in the exploration and research stage
.
Among them, in the clinical trial stage, less than 1/4
of AI applications are used in scenarios such as drug compliance, prediction of treatment outcomes, data analysis, pathological research, and disease diagnosis.
In terms of talents, although many universities have opened AI-related majors and courses, the compound talent gap who are proficient in AI and pharmaceuticals at the same time is still not small
.
The industry pointed out that many team members of AI pharmaceutical companies either understand AI but do not understand medicine, or understand drugs but do not understand AI, and the integration of multidisciplinary knowledge faces many obstacles, which will become a key factor
affecting the development of the AI pharmaceutical industry.
In addition, the industry still lacks unified standards for supervision, and there are a series of problems
such as unclear business models, data constraints, algorithms to be improved, and technologies that need to be improved.
In this regard, industry analysts believe that although the overall development of AI pharmaceuticals is optimistic, in the long run, the development of the industry will return to rationality, and in the future, the entire AI pharmaceutical industry will continuously improve the overall innovation ability
of the pharmaceutical industry under the survival of the fittest while crossing obstacles.
Disclaimer: Under no circumstances does the information or opinions expressed herein constitute investment advice
to anyone.