Castres, France, and Shenzhen, China, November 9, 2026
Pierre Fabre Laboratories and XtalPi Holdings Limited have announced a strategic collaboration focused on discovering innovative small-molecule drug candidates using artificial intelligence (AI), robotics and advanced pharmaceutical research technologies. Under the agreement, the companies will work together across multiple research programs, primarily in oncology, with potential applications in dermatology and rare diseases. The collaboration aims to accelerate the discovery of new clinical candidates against biological targets that have historically been difficult to address through conventional drug development approaches. XtalPi will contribute its integrated AI capabilities and robotics platform to design and deliver novel small-molecule therapeutics against undisclosed targets. Pierre Fabre Laboratories will provide expertise in disease biology, drug discovery, translational research and clinical development to evaluate and select the most promising compounds. The French pharmaceutical company will also take responsibility for the subsequent clinical and commercial development of selected candidates. This partnership reflects the growing pharmaceutical industry focus on combining computational technologies with experimental research to improve early-stage drug discovery and address significant unmet medical needs.
AI and Robotics Drive Novel Drug Discovery
A central component of the collaboration is XtalPi’s integrated AI-powered drug design and robotics platform, which will be used to develop new small-molecule therapeutic candidates. The approach involves de novo drug design, a process in which researchers create novel chemical structures rather than relying exclusively on modifications of existing compounds. By applying computational methods and robotic technologies, XtalPi aims to explore chemical possibilities and generate compounds against selected biological targets. The targets involved in the collaboration have not been publicly disclosed. The companies intend to investigate challenging and historically difficult-to-drug targets, an area that can present considerable scientific and technical barriers during conventional drug discovery. Such targets may require innovative approaches to identify compounds with suitable biological activity and development potential. Integrating AI-based molecular design with laboratory experimentation can help researchers prioritize potential candidates and support the evaluation of their properties. The collaboration will initially concentrate on oncology research, where new therapeutic approaches remain important for addressing complex cancers and treatment resistance. Dermatology and rare diseases may also become areas of research under the agreement. However, the announcement does not identify specific disease targets, drug candidates or clinical trial programs, and the collaboration should be understood as an early-stage discovery initiative rather than a clinical development milestone.
Pierre Fabre to Lead Research and Clinical Development
Pierre Fabre Laboratories will contribute its established capabilities in disease biology, discovery research, translational science and clinical development. Its role will include evaluating compounds generated through XtalPi’s platform and selecting the most promising candidates for further development. The company will be responsible for subsequent clinical and commercial development of the selected molecules. This division of responsibilities brings together XtalPi’s computational drug-design and robotics expertise with Pierre Fabre’s pharmaceutical research and therapeutic development experience. Francesco Hofmann, Head of Pharma Research and Development at Pierre Fabre Laboratories, described the agreement as an important addition to the company’s research and development roadmap. He highlighted the potential of using AI expertise to accelerate the delivery of high-quality clinical candidates across multiple targets. Raymond Zheng, Head of Integrated Drug Discovery at XtalPi, also emphasized the opportunity to combine the company’s AI and robotics capabilities with Pierre Fabre’s established therapeutic development expertise. The partnership is intended to support the identification of promising preclinical candidates that could eventually progress toward clinical investigation. Experimental validation, preclinical safety assessment and clinical trials will remain essential before any compounds emerging from the collaboration can be considered potential medicines.
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Strategic Partnership Strengthens Pharmaceutical R&D
The agreement represents a strategic step in Pierre Fabre Laboratories’ efforts to strengthen its research and development capabilities through data science and artificial intelligence. For XtalPi, the collaboration provides an opportunity to apply its AI and robotics technologies within pharmaceutical research programs supported by an established international drug-development organization. The financial structure includes an upfront payment, multiple milestone payments and downstream economic participation, although the companies have not disclosed the specific financial terms. This arrangement links the discovery collaboration with potential future development and commercial milestones. More broadly, the partnership reflects the pharmaceutical industry’s increasing interest in using AI to improve the efficiency of drug discovery, particularly when exploring complex biological targets. AI technologies can help generate and prioritize molecular designs, but their success ultimately depends on experimental evidence, biological validation and clinical evaluation. Through this collaboration, Pierre Fabre and XtalPi aim to identify innovative small-molecule candidates for oncology and potentially other therapeutic areas. The progress of these research programs will determine whether the partnership can translate its computational discoveries into viable clinical candidates and, eventually, new treatment options for patients.
Source: Pierre Fabre Laboratories, XtalPi press release
