Jingtai Technology, which has the halo of being the "first AI pharmaceutical stock" in China, has attracted considerable attention in the secondary market. In the past few months, it has always sparked discussions within the industry due to occasional breakthroughs.

According to Wind, on November 19th, Jingtai Technology's lowest intraday price was HKD 3.51 per share, hitting a new low since its listing. The closing price for the day was HKD 4.00 per share, a drop of 12.66%. Compared to its issue price of HKD 5.28 per share, it has dropped 24.24%. In fact, since September this year, the stock price of Jingtai Technology has shown an overall fluctuating downward trend.

According to the official website of Jingtai Technology, it is an innovative research and development platform company driven by artificial intelligence (AI) and robots. Based on technologies and capabilities such as quantum physics, artificial intelligence, cloud computing, and large-scale experimental robot clusters, it provides innovative research and development technologies, services, and products for global industries such as biomedicine, chemical engineering, new energy, and new materials. According to the 2024 interim report, revenue from drug discovery solutions accounted for 59.29% of total revenue during the reporting period.

In recent years, artificial intelligence has frequently emerged, and China has also introduced a series of policies to promote its development. This year's government work report also proposed the "Artificial Intelligence+" action for the first time, which aims to empower various industries with artificial intelligence at the national level. At the same time, in the pharmaceutical industry, large models represented by Alphafold and AlphaProteo are highly regarded in the industry; Large models represented by ADMETlab and inClinico have also been applied in drug development in China.

However, the story of capital cannot avoid the issue of commercialization. Some industry professionals once told 21st Century Business Herald reporters that in the field of AI pharmaceuticals, the road from drug development to clinical trials, to market launch, and finally to commercialization is actually very long. It is too early to talk about commercialization at present.

Repeatedly falling below the issue price

On June 13th of this year, Jingtai Technology was officially listed on the Hong Kong Stock Exchange. From the prospectus and later released interim report, it can be seen that Jingtai Technology's business consists of two parts: drug discovery solutions and intelligent automation solutions, and the two are equally matched.

In fact, not only is Jingtai Technology the "first stock of AI pharmaceuticals", but it also carries the halo of being the "first stock of AI+robots". In addition, it is also the first AI for Science to be listed under the 18C rule of the Hong Kong Stock Exchange.

The 18C rule is mainly aimed at specialized technology companies, involving new generation information technology, advanced hardware, advanced materials and other fields. Some market views believe that it is actually aimed at enterprises that need to invest huge amounts of capital and R&D investment to commercialize their products or expand their business scale, and these enterprises often have high growth potential.

This also to some extent summarizes the current situation of Jingtai Technology: high investment and long-term losses.

According to the prospectus, from 2021 to 2023, Jingtai Technology's revenue will be 62.799 million yuan, 133 million yuan, and 174 million yuan respectively; Meanwhile, from 2021 to 2023, Jingtai Technology incurred operating losses of 299 million yuan, 525 million yuan, and 722 million yuan respectively, totaling over 1.5 billion yuan.

In terms of research and development, from 2021 to 2023, the R&D expenses of Jingtai Technology were 213 million yuan, 359 million yuan, and 481 million yuan respectively, accounting for approximately 52.4%, 53.5%, and 49.8% of the total operating expenses of the same year.

According to the 2024 interim report, the company's revenue during the reporting period was RMB 103 million, a year-on-year increase of 28.3%. Among them, in terms of drug discovery solutions, the revenue in the first half of the year reached RMB 60.9 million, a year-on-year increase of 68.6%; The operating loss reached 393 million yuan; We will invest 210 million yuan in research and development.

It should be pointed out that on the day of its listing, Jingtai Technology opened at HKD 5.39 per share, with an intraday increase of over 20%. The closing price of the day was HKD 5.8 per share, up 9.85%, with a total market value of HKD 19.759 billion.

However, just a few days later, on June 17th, it fell below the issue price and was reported as low as HKD 5.18 per share. In July, there were multiple instances of falling below the issue price. In early September, the stock price rose by over 200% at one point, but then fluctuated and fell all the way, falling below the issue price again.

The 2024 interim report also pointed out that according to Frost&Sullivan's data, based on 2022 revenue, Jingtai Technology's customers cover 16 of the top 20 biotechnology and pharmaceutical companies in the world, including Pfizer, Eli Lilly, Johnson&Johnson, Merck, etc.

Despite multiple accolades and collaborations with several biopharmaceutical giants, the market valuation of Jingtai Technology is still considered "high" by some market analysts.

Huachuang Securities pointed out in its analysis of Jingtai Technology that from 2021 to 2023, the number of revenue generating projects for drug discovery solutions will be 18, 47, and 81 respectively. However, currently, AI pharmaceuticals have not yet launched commercial products, and customers are still in the exploration and trial stage, so the investment will not be very large. The amount of orders outsourced to AI+CRO is relatively limited, and the current revenue has not yet covered research and development, sales, and other expenses, showing a short-term loss state.

Behind this, it is actually influenced by the laws of innovative drug development, as the development of innovative drugs has always been high investment, high-risk, and long-term. There is currently no commercially viable model for AI pharmaceuticals.

AI pharmaceuticals have broad prospects

There is a "double ten law" in the field of drug development, which states that the complete process of innovative drug development from research and development to marketing requires 10 years and an investment of 1 billion US dollars.

Nowadays, the emergence of AI has almost participated in the entire process from drug target discovery to clinical trials. It is widely believed in the industry that the application of AI pharmaceutical technology has the potential to shorten the drug development cycle, reduce costs, and improve the success rate of research and development. It has broad prospects and enormous potential in the field of drug development.

The China Academy of Commerce Industry Research pointed out that compared to traditional drug development, AI technology can shorten the time for drug discovery and preclinical research by nearly 40%, and increase the success rate of clinical new drug development from 12% to about 14%.

Moreover, AI can significantly reduce costs at various stages of research and development. Haitong Securities pointed out that the cost reduction in the target discovery and confirmation process is the largest, reaching 67% and 66%, respectively. Administrative tasks can be significantly optimized through automation, although the cost savings may not be as significant as in other stages, reaching up to 56%.

At the same time, the target hit generation stage benefits from AI's predictive ability of up to 56%, and there is still room for further optimization as accuracy improves. The cost of regulatory submission can also be reduced by up to 54% through automation. Due to the experimental complexity required for preclinical testing, although AI can improve efficiency, the cost reduction in this stage is 44%, which may be slightly lower than other stages.

The "2024-2029 China AI Pharmaceutical Market Status Research Analysis and Development Prospect Forecast Report" shows that the global AI pharmaceutical market size will be 1.04 billion US dollars in 2022, an increase of 31.31% compared to the previous year. It is expected that the global AI pharmaceutical market will reach $2.994 billion by 2026.

However, if AI wants to truly disrupt the entire pharmaceutical industry, I think it will be difficult in the short term, but it can achieve the effect of changing from quantity to quality in some aspects. These changes one by one may ultimately bring new developments to the industry, but it still takes time A securities analyst pointed out to 21st Century Business Herald reporters that from the perspective of technology itself, there are still some difficulties in the development of AI pharmaceuticals, and the most important one is the issue of trust in AI.

Specifically, trust issues can be divided into several dimensions. Firstly, in terms of compliance, AI needs to input a lot of data, whether it is self built AI or external AI. How to legally use this data is a problem that needs to be solved, while also avoiding the leakage of sensitive data; Secondly, how to determine the ownership of intellectual property rights for AI generated content is also a problem that needs to be addressed; Once again, in terms of ethics, due to the unpredictability of AI, many things will emerge from quantitative to qualitative changes, and it is difficult to judge whether AI will do some bad things.

According to the 2023 White Paper on Chinese AI Pharmaceutical Companies, currently, AI pharmaceuticals are mainly focused on drug discovery worldwide. The possible reason is that this stage is mainly based on chemical processes, and researchers have a good grasp of the completeness and repeatability of candidate compound data, chemical stability, theoretical understanding, etc., which is conducive to AI modeling.

At present, multiple AI developed drugs have entered clinical trials worldwide, with the highest progress reaching phase three. At the same time, many drugs developed using AI technology have failed to enter clinical trials. No AI developed drugs have been successfully launched yet.

Commercialization still needs to be explored

According to the statistics of "Zhiyao Bureau", among domestic AI pharmaceutical companies, except for Jingtai Technology, which has already been listed on the Hong Kong Stock Exchange, and Yingsi Intelligent, which is rushing to be listed within this year, only a few companies such as Drug Ranch and Zhitai Pharmaceutical have reached Series C financing. The vast majority of other companies are still in the stage of angel to A+round, and mid to late stage financing cases are very rare.

The above industry insiders pointed out that we need to take a rational view of the investment and financing market. Returning to the essence of current AI, it is nothing more than using more efficient methods for text recognition, image recognition, and speech recognition, and using this information to calculate at a scale that was previously impossible to process, ultimately obtaining results. But to truly achieve a transition from quantitative change to qualitative change, breakthroughs need to be sought in terms of contextualization.

Recently, the National Health Commission, the State Administration of Traditional Chinese Medicine, and the National Center for Disease Control and Prevention jointly released the "Reference Guidelines for Artificial Intelligence Application Scenarios in the Health Industry", which includes 4 major categories and 13 subcategories, totaling 84 specific scenarios, to promote the innovative development of "artificial intelligence+" applications in the health industry.

During an interview with 21st Century Business Herald, Wang Yue, Director of Data Analysis and Artificial Intelligence Strategy Consulting at Aikenwei Greater China, pointed out that these more than 80 scenarios are highly summarized and can comprehensively guide the implementation of AI in different scenarios of the medical industry, thereby improving the accuracy and efficiency of diagnosis and treatment, and also promoting the digital transformation of the entire medical industry.

After scenarization, there is still a commercialization path, and it is still early to talk about commercialization. The road from drug development to clinical trials to market and finally to commercialization is actually very long. In this process, strict requirements for safety, compliance, and other aspects in the pharmaceutical industry are also accompanied, "said the industry insider.

At present, there are three business models for AI pharmaceuticals: Al+SaaS, AI+CRO, and Al+Biotech.

Huachuang Securities pointed out that Al+SaaS mainly provides AI assisted drug development software service platforms. There are few domestic enterprises that choose this business model, and more choose AI+CRO, Al+Biotech business models or compatible with two or three of the above business models. The business model of AI pharmaceuticals is not yet clear, and various companies are exploring which model can bring real opportunities to AI pharmaceuticals. However, no business model has been proven to be better than others.

The above-mentioned securities analyst said that the combination of artificial intelligence and the healthcare industry is a major direction for future development. The stage of Spark is when artificial intelligence is embedded into different scenarios of the medical industry to solve specific problems. In the future, artificial intelligence will achieve deeper applications in the medical field, bringing about significant changes to the entire industry.

Source: 21st Century Business Herald