Galixir Announces Tens of Millions of Dollars in Funding, Using "AI+" to Break Through Bottlenecks in Drug Discovery
Gaorong Ventures led Galixir's angel round and continued to increase its stake in subsequent funding rounds.
On December 29, 2020, Galixir announced the completion of its latest two funding rounds, raising tens of millions of dollars. In 2019, Gaorong Ventures had led Galixir's angel round and continued to increase its stake in subsequent rounds.
Galixir stated that the proceeds would be used to expand its R&D team and build professional biochemical testing laboratories, creating a closed-loop process for innovative drug generation, screening, evaluation, and testing to enable rapid optimization and advancement of R&D projects.
Multiple Technical Breakthroughs, Rapid Pipeline Advancement
In just the past four months, Galixir has completed three consecutive funding rounds. During this period, the company achieved several major technical breakthroughs, further extending its lead over domestic and international competitors. On one hand, Galixir successfully developed drug generation and screening-evaluation models targeting innovative genetic targets for difficult-to-treat disease types. On the other hand, its existing drug R&D pipelines have all made solid progress and have successively entered in vivo and in vitro laboratory validation stages: experimental feedback from authoritative institutions shows that Galixir's proprietary drug activity evaluation module has significantly improved screening efficiency, with hit rates more than ten times higher than traditional methods. Additionally, the Galixir team used its proprietary molecular design module and compound optimization module to generate multiple de novo design or optimization schemes for entirely novel molecular structures in a short period, all of which have passed wet-lab validation. "The wet-lab results demonstrate that the Galixir platform can efficiently and accurately identify novel molecules with better activity than benchmark drugs and greater patent space. This makes it possible for us to rapidly advance multiple R&D pipelines," said Dr. Chengtai Li, founder and CEO of Galixir.
Interdisciplinary Team, Deep Focus on AI-Powered Drug Discovery Platform
Founded in 2019, Galixir is dedicated to using cutting-edge artificial intelligence to focus on preclinical drug R&D. Its self-developed AI drug discovery platform aims to help drug R&D scientists substantially save time and costs in the drug development process while providing comprehensive patent protection for developed drugs.
The company's founder and CEO, Dr. Chengtai Li, graduated from Tsinghua University's Yao Class for his undergraduate studies and holds a PhD in computer science from MIT. He is one of the leading scholars in the AI + chemistry interdisciplinary field. Galixir's rapidly growing team comprises professionals with interdisciplinary backgrounds: key members come from well-known internet companies, multinational pharmaceutical firms, and drug research institutions. Team members have experience leading new drug projects through FDA approval and have pioneered and optimized multiple AI models in drug R&D. Currently, Galixir's research team continues to explore frontier technologies at the intersection of AI and drug discovery: this year alone, the team has published several papers in top-tier conferences and journals in collaboration with leading domestic and international universities and research institutes.
Integrating Hundreds of Models to Build an AI + New Drug R&D Moat
The "AI drug discovery" track that Galixir occupies is one of the most promising sub-sectors in the broader "AI+" space in recent years. Generally, drug R&D comprises four stages: drug discovery, preclinical research, clinical research, and regulatory approval and commercialization.
The core of competition in the AI drug discovery space is pipeline depth — the further a drug pipeline advances, the greater its value. Galixir holds a leading position in this track. Its technical capabilities are built on sophisticated AI models that fully integrate computational chemistry and medicinal chemistry dimensions, constructing a comprehensive automated system through various tools that covers the entire journey from hit compounds to preclinical candidates.
Galixir has developed multiple proprietary algorithms and established a series of deep learning models for drug target discovery, candidate compound generation, compound structure optimization, druggability and toxicity prediction, and patent analysis. In just over a year since its founding, Galixir has integrated hundreds of models and developed optimized workflows for drug discovery in cancer, metabolic diseases, and immune-related diseases, gradually building competitive moats in the AI + new drug R&D space. Based on preliminary comparative analysis, Galixir's self-developed models and algorithms have achieved best-in-class results in multiple stages, dramatically shortening R&D timelines and costs — directly addressing the "high investment, long cycle" challenge that drug R&D companies commonly face both domestically and internationally.
On the commercialization front, Galixir has established multiple efficient project teams capable of simultaneously conducting multiple early-stage drug discovery projects. The company has already signed strategic cooperation agreements with several well-known domestic and international universities and pharmaceutical companies, ensuring smooth upstream innovation and downstream testing in innovative drug discovery and development.
