Pharmaceutical companies flocked to layout, focus on what direction?



In 2023, the artificial intelligence wave triggered by the explosion of ChatGPT swept the world, and let people see the new possibilities of generative AI in the pharmaceutical field.

It is reported that traditional drug research and development faces the problem of long cycle, large capital investment and high risk. Industry analysts believe that the use of AI technology can shorten the new drug research and development cycle, save costs, and significantly improve the efficiency of drug research and development and enterprise competitiveness.

In recent years, cooperation cases between pharmaceutical companies and technology companies have been frequent, and the advantages of AI pharmaceuticals have gradually emerged.

01 AI+ medicine "ignites" the new direction of the industry

The so-called AI pharmaceutical, that is, the use of big data, cloud computing and other artificial intelligence technology means to assist drug discovery, drug management and other drug research and development links.

Traditional drug development is a long, costly and laborious process with a high failure rate. There is a famous "double ten law" in the field of drug research and development, that is, the average time to develop a new drug is ten years, and the cost is one billion dollars.

With the explosive growth of artificial intelligence, the "double ten laws" of drug research and development may be broken. According to Nvidia's public information, the use of AI technology can reduce the time required for early drug discovery to 1/3 times, and save costs to 1/200 times.

In the long term, AI pharmaceuticals have great prospects. According to the Markets and Market report, the global AI revenue value in the drug discovery market is $600 million in 2022 and is expected to reach $4 billion by 2027.

The huge imagination space and market potential have attracted the global head pharmaceutical companies to compete in the AI+ pharmaceutical field. For example, Astrazeneca, Johnson & Johnson and AI+ pharmaceutical listed company Benevolent AI reached a strategic cooperation.

In China, as early as 2015, a large number of AI pharmaceutical startups such as Jingtai Technology, Yiyao Technology, and Star Medicine Technology have sprung up.

Traditional pharmaceutical companies are not willing to lag behind, such as Yunnan Baiyao (000538.SZ) and Huawei reached cooperation on AI drug research and development; Fosun Pharmaceutical (02196.HK) and AI pharmaceutical company Insi Intelligence entered into a cooperation agreement; Wuxi AppTec (02359.HK) has invested in a number of AI-enabled drug research and development companies; Many CRO companies, such as Haoyuan Pharmaceutical (688131.SH), Chengdu Lead (688222.SH), Hongbo Pharmaceutical (301230.SZ), and Medisi (688202.SH), are also promoting the integration of "CRO+AI"......

In addition, Baidu, Tencent, Alibaba, Bytedance and other Internet giants have also built drug research and development platforms based on their own AI algorithms and other advantages, and strive to get a share of the blue ocean market of AI pharmaceutical research and development.

At the same time, the financing heat of AI pharmaceuticals is heating up rapidly. According to statistics, in 2022, the total number of AI pharmaceutical race-related financing events reached 144, an increase of 87%, and the total amount was 6.202 billion US dollars, an increase of 36%. Among them, the United States and China are more active in AI drug research and development financing, with 71 and 43 cases respectively in 2022.

It is not difficult to see that the use of AI technology for drug research and development has now become one of the hot tracks in the medical field.

02 "Small molecule" is still the main track of AI pharmaceutical

By the end of 2022, there are 700 AI drug research and development companies in the world, more than half of which are in the United States; China accounts for about 3.5%, and there are 80 AI pharmaceutical companies.

At present, there are three main entrants in the AI pharmaceutical market, which are divided into large pharmaceutical companies, CRO, and Internet companies. There are three main business models, namely, AI SaaS that sells software, AI CRO that sells drug research and development services, and AI Biotech that directly develops and sells drugs.

From the perspective of subdivision, the current research focus of AI pharmaceuticals is still concentrated in small molecule drugs. Among the nearly 80 AI pharmaceutical companies in China, 41 focus on small molecule research and development, accounting for more than half of AI pharmaceutical companies.

This is mainly due to the accumulation of data in the field of small molecules, the market is relatively mature, and it has been widely used in virtual screening, molecular generation, ADMET prediction, drug redirection and other links.

Some industry analysts said that in the future, AI pharmaceuticals will gradually expand to synthetic macromolecular biological drugs, and antibodies and peptides will be the next key areas of drug discovery.

03 Challenges facing AI pharmaceuticals

It should be pointed out that while the rapid development of AI has brought new opportunities to pharmaceuticals, it still faces great challenges.

The first is the acquisition of the dataset. As we all know, AI technology has very high requirements for the "quantity" and "quality" of data. Only when the data is rich and accurate enough can AI better play its role in data analysis, integration, screening and so on.

Accurate and effective clinical trials are the cornerstone of successful drug development, and in AI pharmaceuticals, large amounts of clinical trial data are also critical. But such data is a core asset of pharmaceutical companies and is scattered across hospitals, making it extremely difficult to obtain. Therefore, "getting the right data set" is seen by the industry as one of the top five challenges facing AI medicines.

The second is the scarcity of professionals. In the field of AI pharmaceuticals, technicians need to have a deep understanding of pharmaceutical medicine related knowledge and AI artificial intelligence in order to better play the advantages of the model. However, in real life, such high-end composite talents are very scarce, which has become an important factor hindering the development of the industry.

In addition, medical care is closely related to human life, so the supervision of AI+ medical application scenarios is also extremely strict. As the corresponding regulatory rules continue to be released, the development of AI pharmaceuticals in the future will be full of more uncertainty.

As of now, the world has not yet successfully approved a drug developed by AI. It can be said that AI pharmaceutical research and development is still in the stage of exploration and early development.

Conclusion:

There is no doubt that with the rapid development of AI technology, the value of AI in the pharmaceutical industry will be greater and greater. Under the trend of The Times, how to break through various challenges for AI pharmaceutical companies is the primary problem to be solved.

From the perspective of investment analysis, Southwest Securities believes that companies with the industry Know-How and customer base, have an early layout in the field of AI, and actively embrace large model technology changes have first-mover advantages. 1) AI+ diagnosis and treatment field, focusing on Runda Medical, Chuanghuikang, Jiahe Meikang, Ambiping, Jianhui information, digital people, etc.; 2) AI+ pharmaceutical field, focusing on Hongbo Pharmaceutical, Yiqiao Shenzhou, Haoyuan Pharmaceutical, etc.