Economic Observer reporter Zhang Ying

We are the 'veterans' of the AI pharmaceutical industry, already classified as the first generation of AI pharmaceutical companies, because now there is a second generation. ”On October 24, 2026, at the 11th Pharmaceutical Innovation and Investment Conference, Ren Feng, Co CEO and Chief Scientist of British Silicon Intelligence (03696. HK), joked.

Yingsi Intelligent was founded in 2014 and is a leading AI pharmaceutical company in the world. This year, it has reached BD deals with multiple multinational pharmaceutical companies. As of October 23, 2026, the company's market value is HKD 21.3 billion.

The second generation AI pharmaceutical companies mentioned by Ren Feng mainly refer to AI pharmaceutical companies incubated by technology giants such as Anthropic and ByteDance, or created by their technical backbones cross-border. The founders of these startups are often young people in their twenties or thirties, whom Ren Feng refers to as the new generation of AI pharmaceuticals.

Ren Feng admitted that in the era of AI explosion, AI pharmaceutical companies also have anxiety, and it is currently unclear what kind of competition will emerge in the future.

Ren Feng believes that there are significant differences in investors' evaluation criteria for these two types of companies at present. For mature companies like Yingsi Intelligence, the evaluation criteria are often based on how many innovative targets there are, how many projects have entered clinical trials, and whether the business model can be implemented. For start-up AI pharmaceutical companies, they still focus on team, technology, data, algorithms, and so on.

They are still in the sunrise period of only discussing technology, and no one is asking them to land, "Ren Feng said, but ultimately they will also enter the second half and be evaluated for their commercial landing capabilities.

|Dialogue|

Economic Observer: Everyone is very concerned about what impact these new generation AI pharmaceutical companies will bring to you, and whether they will weaken your company's competitiveness?

Ren Feng:Everyone has different technological paths. Most of the new generation enterprises are based on large models, while we used to be based on vertical domain models, which were all small models. Each small model solves a small problem, for example, this model solves solubility, and that model solves permeability and metabolic stability problems. Each problem is solved by building a model based on a specific type of data, without relying on any base model.

The big model is completely different after it comes out. For example, Anthropic attempts to solve problems by scheduling vertical models with its own large model. Of course, these models cannot schedule us because we are closed source and can only schedule open source. But open source small models are not good or bad, they require a lot of experiments to verify open source models. This is the strategy of large companies.

Our approach is different. After years of optimization, iteration, and feedback, we believe that our vertical classification model is better than most open-source models.

The new generation is based on large models to create multimodal models, with intelligent agents as the main focus. However, in the future, they may also create vertical models, just like we may create intelligent agents. Gradually, everyone's technological routes will become more and more similar.

What is our specific relationship? There will definitely be competition, but there will also be mutual promotion.

Economic Observer: Who made the open-source models they call?

Ren Feng:Many, such as research teams from some universities. But the quality is unknown. These open-source models need to be validated.

Economic Observer: Will they poach people from your company?

Ren Feng:There are indeed some AI pharmaceutical companies targeting our company to recruit talent, and we are also improving incentive measures to retain core talents. Meanwhile, we can cultivate more talents. We have been recruiting newly graduated PhDs or returning postdoctoral fellows from both domestic and international sources. We found that many of them are mentally active, passionate, and willing to embrace new things. These people are rarely limited by rules and often provide us with a wealth of innovative ideas.

Economic Observer: If you had to use three words to summarize the progress in the AI pharmaceutical field this year, which three words would you use and why?

Ren Feng:The first characteristic is anxiety. Both companies within and outside the field of AI pharmaceuticals are very anxious. We are also very anxious. In the era of AI explosion, we need to think about our future competitive advantages and what kind of company we will become. Not only in the industry, this anxiety phenomenon is quite common. In the morning report, the president of the Pharmaceutical University said that their school is also anxious.

The second one is change, there have been many changes in the AI field this year. The entire technical roadmap is different from what we did before. Everyone is transitioning from a single modal vertical model to a multi-modal large model, and this change cannot be resisted by anyone. Another thing is that technology giants are entering the pharmaceutical industry one after another, a change that was rarely seen before. Previously, these giants did not make drugs but only provided bases, and this change was also something we did not expect.

Another change is that more and more multinational companies are coming to China for cooperation. They not only come to buy pipelines, but also bring their pipelines to China for a phase one test because China's phase one test has low cost and high efficiency. After the first phase of testing and technical results, the multinational company brought it back to the United States for the second phase, a change that had not been seen before. So, change is a particularly important theme this year, and if you can't adapt to these changes, you will be anxious and uncomfortable all the time.

The third word is game. As a company, it's quite difficult for us to compete with market trends, especially as a listed company. Any negative news in the market can lead to a decline in the company's stock price. We have also been conducting roadshows to tell investors in the secondary market that the company's fundamentals are not a problem.

(Author Zhang Ying)