At the 2026 Yabuli Forum Summer Annual Meeting held in Chengdu from September 4-6, a key conversation unfolded regarding the future of pharmaceutical innovation. Dr. Zhu Jun, Executive Director and Chief Executive Officer of HENLIUS, shared his perspective that artificial intelligence's role in new drug development extends far beyond simple efficiency gains. He argued that AI has the potential to become a decisive, transformative force that reshapes the very foundation of how therapies are created.
Dr. Zhu broke down AI's contribution to the medical industry into two distinct facets. The first, which he termed "AI for efficiency," focuses on streamlining communication and operational processes to drastically shorten timelines. The second, "AI for science," represents a more profound shift—utilizing AI to identify and design targets and proteins that were previously considered impossible or too challenging to pursue. This scientific application moves beyond mere speed, unlocking entirely new avenues of research.
From a competitive standpoint, Dr. Zhu believes AI will fundamentally alter the prevailing profit model for Chinese pharmaceutical companies, which has historically relied on scale and resource volume. With AI's ability to pinpoint disease mechanisms and their corresponding targets, a small, agile company could produce a blockbuster product. In this new paradigm, a team of 50 people leveraging AI effectively could outperform a traditional 2,000-person organization, creating value in a disruptive and unprecedented manner.
Regarding the industry's maturity, Dr. Zhu proposed a "three-stage theory" for AI-driven drug development. The first stage, where the industry predominantly operates today, involves AI as a support tool in wet labs, where it assists in screening and then reverts to dry lab computational optimization, yielding hybrid results. The second stage, which many companies are beginning to explore, sees AI autonomously discovering targets and designing molecules for experimental validation, though no product has successfully emerged from this phase yet. The third stage, arriving with the era of strong artificial intelligence, envisions a future where everything is data-driven and computational, fundamentally redefining the research landscape.
Dr. Zhu also provided concrete examples of AI application in HENLIUS's actual pipeline. He discussed an asset for a weight-loss injection, where the benchmark product, while capable of building muscle and reducing fat, suffered from low affinity and required high doses, leading to side effects like acne and muscle spasms. By applying AI to identify the correct epitope, the company was able to enhance affinity by more than 20-fold, dramatically reducing these adverse effects.
Addressing the company's strategic choice to develop proprietary algorithms rather than rely on external tools, Dr. Zhu underscored the critical importance of data quality. He explained that the core of AI lies in high-quality data—information about which structures have been proven invalid and which show promise is not truly open-source; it is a company's proprietary accumulation. This accumulated knowledge grows exponentially, as each use generates more data that, in turn, feeds back into the model, making the development of proprietary large models essential. He also noted that the daily salary for AI interns can exceed that of seasoned employees with 5-10 years of experience, adding that the key isn't the sheer volume of investment in AI, but rather the strategic approach and a deep understanding of the fundamentals.
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