BIOS 2026 | MindRank Showcases AI-Powered Drug Discovery Innovations and Explores Global Collaboration Opportunities

During the conference,MindRank's Chief Commercial Officer, Mr. Lin Jian, shared the latest progress in AI-assisted GLP-1 oral new drug development.Facing the "Eroom's Law" challenge in traditional drug development, AI empowerment has become an inevitable choice for updating the R&D paradigm. MindRank, relying on its one-stop AI platforms such as PharmKG™, Molecule Pro™, and Molecule Dance™, has significantly improved R&D efficiency. The self-developed pipeline MDR-001 (GLP-1RA small molecule) obtained IND approval in just 19 months and launched Phase III clinical trials in December 2025. Clinical results show that the candidate drug has significant weight loss effects (up to 10.3% in 24 weeks) and excellent safety. In the future, MindRank will focus on building a data and engineering-driven drug discovery + continuous learning closed loop, establishing a dual-driven R&D and business model of "AI platform + self-developed pipelines."

At the roundtable forum of the Acro Innovation Forum (closed-door meeting), guests from MindRank, Angxin Bio, Yudao Bio, and Kuoyue Smart Drug participated.Jointly discussed the current status and prospects of AI applications in drug research and development.

The guests unanimously agreedAI Is Accelerating Its Penetration into the Entire Drug R&D Chain，Its advantages in small molecule drug design, computational methods based on allosteric mechanisms, and generative methods have gradually been validated, with particularly significant results in early R&D, ADMET optimization, and hit compound discovery. Moreover, the role of AI has extended across the entire chain of process manufacturing, preclinical evaluation, and clinical trials, showing potential in increasing yield, optimizing drug-likeness, and improving patient enrollment and trial simulation. In response to the contradiction between the rapid iteration of AI and the long development cycle of drugs, the industry adopts a phased deployment strategy and model version locking, while the transparency principle established by regulatory agencies is gradually replacing pure technological competition. Regarding cross-border collaboration, core algorithms, training data, and talent loss represent major risks; enterprises should build locally independent algorithms and datasets, choose cooperation models with clear compliance frameworks, and continuously monitor regulatory updates.

This Year's BIOSeedin Spring Innovation Cooperation SummitIgniting the forefront of wisdom for the biopharmaceutical industry,MindRank will collaborate with global ecosystem partners to explore new paradigms of AI-empowered pharmaceutical R&D, promoting more innovative achievements to reach the international stage.