This Year's Nobel Prizes Inject a Strong Boost into the AI Sector

AI Becomes the Biggest Winner of the 2024 Nobel Prize.

First, an artificial intelligence scholar won the Nobel Prize in Physics. The committee awarded them for "utilizing physics tools to develop foundational methods for today's powerful machine learning technologies."

Immediately following, the 2024 Nobel Prize in Chemistry was awarded to David Baker, Demis Hassabis, and John M. Jumper for their contributions to the field of protein design and protein structure prediction using AI.

It must be said that the influence of AI is indeed enormous.The Nobel Prize heralds that the end of the universe might be AI, and the future trend of the pharmaceutical industry is becoming increasingly clear: AI is the future.

This is a signal that deserves particular attention.In the AI field, Chinese companies have long anticipated and kept pushing forward.

The day after AlphaFold won the award, on October 10, XtalPi, the first AI pharmaceutical stock in China, reached a licensing agreement with Janssen Biotech, a subsidiary of global leading pharmaceutical company Johnson & Johnson, for its similar technology-based XtalFold™ AI platform.

In recent years, the commercialization of Nobel Prize-winning achievements has been visibly accelerating, and with the boost from AI, this trend is expected to become even more pronounced.

/ 01 / The Inevitable Trend of the Pharmaceutical Industry

In the pharmaceutical industry, AI empowerment is no longer a novelty. However, the recognition by the Nobel Prize still endows AI-driven drug discovery with a distinct significance.

Heiner Linke, chairman of the Nobel Chemistry Committee, spoke highly of the AI protein structure prediction technology that won the prize this year, with the core point being,When proteins become predictable, the medical community gains greater confidence in tackling more undruggable targets and improving drugs' efficacy while reducing toxicity. The disruptive progress of AI has opened up entirely new possibilities for scientific research and the biopharmaceutical industry.

The Nobel Prize, as the highest award in academia, represents the forward-looking fields recognized by the scientific community with significant influence. It often drives related disciplines and fields to develop towards deeper and broader levels, leading to more new discoveries and breakthroughs.

After being recognized by the Nobel Prize, it is not uncommon for related fields to enter a golden age.For example, quantum mechanics has achieved leapfrog development under the impetus of the Nobel Prize.

The medical field is no exception. The 2018 Nobel Prize in Physiology or Medicine—"for their discovery of cancer therapy by inhibition of negative immune regulation"—has, to a certain extent, accelerated the development of cancer immunotherapy. Currently, immunotherapy is at the core of cancer treatment research, with Keytruda (K药) alone generating annual sales exceeding $20 billion.

CRISPR/Cas9, which won the Nobel Prize in Medicine in 2020, has also entered a fast track of development, giving rise to a number of star products or companies.Following the announcement of the award, the leading companies in the field, Intellia and CRISPR Therapeutics, experienced rapid stock price surges. Intellia's market value once exceeded $20 billion, while CRISPR Therapeutics' market value quickly climbed to nearly $19 billion after the Nobel Prize.

Whether it's the successive entrepreneurial endeavors of industry giants like David Baker, or the flurry of AI collaboration announcements from major pharmaceutical companies, the strategic importance of AI in the industry has long been a consensus. Now, with the added impetus of the Nobel Prize, AI-driven drug discovery undoubtedly carries even higher expectations.

The research and development of innovative drugs is a slow process, and AI molecules also need to undergo long-term clinical validation. Many factors have led to the label of "yet to be verified" for AI drug development remaining an objective fact; however,The recognition by the Nobel Prize fully proves that this path is correct, and AI is the inevitable direction for the pharmaceutical industry.

With the boost from the Nobel Prize, AI pharmaceuticals may be on the verge of an accelerated growth phase, marked by a surge in leading companies.

/ 02 / Big Pharma Can't Do Without AI

The establishment of a successful business model requires both technology that addresses pain points and a group willing to pay for that technology. To some extent, the technology determines the product's potential, while the strength of the willingness to pay decides its actual performance.

AI is expensive. It is reported that OpenAI is expected to spend more than 200 billion US dollars by 2030, of which 60% to 80% will be used for training and running models.The scale of AI and large models in vertical fields is significantly smaller, but the high cost is bound to limit the feasibility of pharmaceutical companies independently developing AI algorithms.

Currently, the innovation return rate of large pharmaceutical enterprises continues to decrease. Facing the patent cliff, the "pipeline" anxiety keeps amplifying, and there is an increasing emphasis on AI-driven drug discovery.As AI pharmaceutical technology develops and gets validated, pharmaceutical companies' willingness to pay also rises.

Today's large pharmaceutical companies cannot do without AI. The collaboration between Johnson & Johnson and XtalPi mentioned above is just another strong example of how large pharmaceutical companies are accelerating their AI deployment.

Data shows that in 2023 alone, MNCs announced over 30 public collaborations in the "AI + drug" R&D field, with a total disclosed value of approximately $10 billion, and the highest single deal reaching $2.7 billion. This highlights the fervent enthusiasm MNCs have for AI.

In fact, nowadaysThe enthusiasm of large pharmaceutical companies for AI-driven drug discovery is not only reflected in pipeline layout and the choice of R&D tools but has also risen to become a fundamental logic supporting corporate operations, with strategic significance that goes without saying.

On October 10, global pharmaceutical leader Eli Lilly appointed its first Chief Artificial Intelligence Officer—Thomas J. Fuchs. Thomas J. Fuchs will provide comprehensive vision, strategic guidance, and leadership for Eli Lilly's artificial intelligence initiatives, covering drug discovery, clinical trials, manufacturing, commercial activities, and internal functions.

Big pharmaceutical companies are paying more attention to AI, which also means they are increasingly willing to spend money.On October 7, AstraZeneca introduced the AI molecular lipoprotein(a) inhibitor YS2302018 from CSPC Group. YS2302018 is still in the preclinical stage, but the total transaction value exceeds $2 billion, with the upfront payment alone reaching $100 million.

In terms of the AI pharmaceuticals industry, the business model has been validated. In 2023, Schrodinger achieved a profit of nearly 300 million RMB, primarily through software service revenue. This makes it the world's first publicly listed AI pharmaceutical company to achieve profitability.

The Nobel Prize has confirmed the correct direction, with clear pain points and payment willingness from big pharmaceutical companies. AI-driven drug discovery is bound to accelerate into a harvest period.Next, it depends on who has sufficient resources, patience, and mature business capabilities to grow rapidly and break through in this emerging blue ocean market.

/ 03 / Who Will Be the Big Winner?

Although China's AI pharmaceuticals industry is still "in its infancy" and the future is full of uncertainties, there is no doubt that as AI technology takes the stage at the Nobel Prize, Chinese AI pharmaceutical companies will also seize development opportunities in the major trend of "AI, the future."

Chinese AI companies have unique advantages for development: industrial data and supply chain strengths.The core of AI is algorithms, which require the continuous accumulation of high-precision data for model training, development, and optimization. It can be said that the quality and scale of data are fundamental competitive factors. Due to its industrial scale, China has access to larger data volumes with relatively lower data acquisition costs, providing inherent advantages for the development of the AI industry. However, there remains a gap between theoretical data volume and the actual conversion into usable AI data assets. How to accumulate high-precision data suitable for AI model training during R&D and production while maintaining high quality and low cost is key to the industrial implementation of AI pharmaceutical technologies.

Of course,Whether AI pharmaceuticals in China can establish themselves in the global market depends more importantly on their ability to continuously keep up with the times and gain a firm foothold in the global arena.Compared with the rapidly developing pharmaceutical market in China, the pharmaceutical R&D markets in Europe and the United States are more mature, with a clearer consensus on AI. AI-driven pharmaceutical companies are flourishing yet face fierce competition. Both AI and pharmaceuticals are in an era of great technological exploration. This requires companies to have a clear judgment and deep understanding of the global pharmaceutical market. Their technological products should not be too far ahead of the market's purchasing willingness, nor should they fall behind the trend, in order to continuously secure commercial contracts and offset the high costs of R&D.

A noteworthy phenomenon is that such companies in China are beginning to emerge.Among them, XtalPi, the "first AI pharmaceuticals" stock, has garnered significant attention during this Nobel Prize season. It is evident that, in addition to AI + Physics, which won this year's Nobel Prize in Physics, and the previously mentioned Nobel Prize in Chemistry for AI protein prediction, this year’s Nobel Prize in Physiology or Medicine research topic—miRNA—is also related to XtalPi. Moreover, in terms of timing, XtalPi's strategic layout was "just right": at the end of 2023, XtalPi collaborated with Yangtze River Life Sciences Technology based on AI technology to explore and develop a molecular diagnostic model for cancer prognosis risk prediction based on miRNA. This "triple hit" has made XtalPi a research model for AI pharmaceuticals amid the Nobel Prize spotlight.

As a research and development platform with its own robotics laboratory, XtalPi is actively converting China's industrial scale advantage into a research data advantage, while continuously expanding its overseas operations. To address data issues from the source, XtalPi has independently developed a modular, highly parallel automated chemistry laboratory, which has now reached a scale of hundreds of units. While serving pharmaceutical clients, it generates standardized R&D data, functioning like a data mine that provides ammunition for the validation of AI predictions and the training and development of AI models, transforming business operations into data assets and algorithmic assets. Additionally, backed by the intelligent hardware supply chain in the Guangdong-Hong Kong-Macao Greater Bay Area, XtalPi’s automated laboratories are scaling up faster and at a lower cost. According to publicly available information, XtalPi plans to continue the large-scale deployment of its automated robotic workstations, including establishing new laboratories in regions such as North America to support the needs and growth of its overseas business.

In terms of business strategy, XtalPi has fully leveraged the advantages and business expansion capabilities of its platform enterprise, with a total of over 300 clients globally. XtalPi boasts numerous benchmark clients, and its overseas business consistently accounts for a significant proportion. This includes 16 of the top 20 global pharmaceutical companies such as Eli Lilly, Pfizer, Johnson & Johnson, and Merck, as well as a series of cutting-edge biotech startups that it has incubated or collaborated with, such as METiS Pharmaceuticals, PhoreMost, and LaMont Biotech. Notably, METiS Pharmaceuticals is now nearing unicorn valuation.

At the same time, XtalPi has been actively seeking new business growth curves in the past few years, securing corresponding orders in the fields of large-molecule drug research and development, automated experimental solutions, and new materials research and development.

In July, XtalPi won the bid for the construction of the Intelligent Automation Integration and Innovation Platform for Traditional Chinese Medicine New Drug Development at a provincial-level laboratory in Guangdong Province. This project is expected to create the first fully automated platform in China for the separation and analysis of active components in traditional Chinese medicine.

The interim report this year shows that XtalPi has signed a five-year strategic cooperation agreement with GCL Group, with a total scale of approximately 135 million US dollars (about 1 billion yuan).

In the first half of this year, XtalPi launched the Ailux brand overseas to expand its macromolecule business. As of the end of August, it had reached macromolecule business collaborations with more than 20 clients, approximately half of whom are overseas clients.

In essence,As the underlying logic of AI combined with physical底层 algorithms is打通, AI pharmaceutical enterprises can easily achieve technology spillover and have the opportunity to become promoters of a series of AI industrializations.In XtalPi's ultimate vision, its business will extend to industries such as chemistry, materials, agriculture, and the environment. If the expansion proceeds smoothly, XtalPi's potential for explosive growth and sustainability may be worth anticipating.

Of course, these are all things to be discussed later. For now, AI technology is already recognized by the industry as a Nobel Prize-worthy future technology in the biopharmaceutical field. As overseas pharmaceutical companies frequently make advancements, it remains to be seen whether Chinese enterprises can seize the opportunity to grow rapidly. This vigorous wave of AI is accelerating, and the winners who manage to break through will eventually emerge.

       Original Title: This Year's Nobel Prize Gives a Shot in the Arm to the AI Track