MindRank has announced the completion of a cumulative $52 million Series B financing round to support the continued development of its AI-discovered oral GLP-1 receptor agonist, MDR-001, as it progresses through Phase III clinical testing for obesity. The Hangzhou, China-based biotechnology company said the financing was backed by several investment institutions and industrial funds.
The new capital will also be used to further develop the company's proprietary Molecule Arts Platform (MAP), an AI-driven drug discovery engine that integrates molecular design, laboratory experimentation and clinical data analysis throughout the development process.
Explaining the platform's approach, MindRank said, "By constructing multi-agents that connect computational models, wet-lab experiments, and clinical feedback, the platform drives the continuous validation and iteration of prediction results through experimental and clinical data," creating what the company described as a "compound growth flywheel" in which data and algorithms reinforce one another over successive drug development cycles.
According to MindRank, the company has secured three investigational new drug (IND) approvals across China and the United States, while its pipeline includes five preclinical candidates and a total of 15 first- or best-in-class programmes.
MDR-001 is currently the company's most advanced programme. The oral GLP-1 candidate entered Phase III testing in China earlier this year, approximately four and a half years after the company used artificial intelligence to identify and optimise the molecule. The placebo-controlled MOBILE study is enrolling approximately 750 adults with overweight or obesity.
In earlier Phase IIb testing, patients receiving MDR-001 achieved up to 7.8% placebo-adjusted weight loss after 24 weeks. The results position the candidate within a growing competitive market for oral GLP-1 therapies.
Looking ahead, founder and CEO Zhangming Niu said the company's ambition extends beyond developing individual medicines. "Our long-term goal is not just [to build] an innovative drug company, but an AI-native pharma system capable of continuously exploring, continuously learning, and continuously creating innovative drugs," he said. Niu added that the MAP platform "provides high-precision map navigation for exploring the vast drug space," while "distilling every molecular design computation, experimental validation, and clinical feedback into new knowledge, making every exploration the starting point for the next innovation."
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