Galixir, a Source Code Capital portfolio company, raises tens of millions of dollars in funding, with existing investor Source Code Capital continuing to increase its stake

源码资本·December 29, 2020·1·4

Galixir's technical capabilities are built on sophisticated AI models, enabling end-to-end coverage of drug discovery from hit compounds to preclinical candidates.

On December 29, 2020, Galixir announced the completion of its latest two funding rounds, raising tens of millions of US dollars. The rounds were led by Redpoint China Ventures and 5Y Capital, with participation from Source Code Capital, BAI Capital, Gaorong Ventures, and DCM. Maxceed Capital served as the exclusive financial advisor for the transaction. Source Code Capital was a co-lead investor in Galixir's Pre-A round.

Galixir stated that the proceeds will be used to expand its R&D team and build professional biochemical testing laboratories, creating a closed-loop workflow spanning drug generation, screening, evaluation, and testing — enabling rapid optimization and advancement of its R&D pipeline.

In just four months, Galixir completed three consecutive funding rounds. During this period, the company achieved multiple major technical breakthroughs, further extending its lead over domestic and international competitors. On one front, Galixir successfully developed drug generation and screening-evaluation models targeting innovative genetic targets for difficult-to-treat diseases. On another, 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 showed that Galixir's proprietary drug activity evaluation module significantly improved screening efficiency, with hit rates more than ten times higher than traditional methods. Additionally, the Galixir team used its proprietary molecular design and compound optimization modules to rapidly generate multiple de novo design or optimization proposals for entirely novel molecular structures, all of which have passed wet-lab validation.

"Wet-lab results have proven 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. Chengtao Li, founder and CEO of Galixir.

Founded in 2019, Galixir is dedicated to applying cutting-edge artificial intelligence to preclinical drug discovery. Its self-developed AI drug discovery platform aims to help drug discovery scientists dramatically reduce the time and cost of drug development while providing comprehensive patent protection for the drugs under development.

Dr. Chengtao Li, the company's founder and CEO, graduated from Tsinghua University's Yao Class with a bachelor's degree and holds a PhD in computer science from MIT. He is among the leading scholars in the interdisciplinary field of AI and chemistry. Galixir's rapidly growing team comprises professionals with multidisciplinary backgrounds, with key members hailing from leading internet companies, multinational pharmaceutical firms, and drug research institutions. Team members have experience leading new drug projects approved by the FDA, and have pioneered and optimized multiple AI models for drug discovery. The Galixir research team continues to explore frontier technologies at the intersection of AI and drug discovery: this year alone, in collaboration with top domestic and international universities and research institutes, the team has published several papers at leading conferences and in top-tier journals.

The "AI drug discovery" track that Galixir occupies is a subsector of the broader "AI+" landscape that has drawn considerable industry optimism in recent years. Drug R&D generally comprises four stages: drug discovery, preclinical research, clinical research, and regulatory approval and commercialization.

The core competitive battleground in AI drug discovery is pipeline depth — the further a drug pipeline advances, the greater its value. Galixir holds a leading position in this race. Its technical capabilities rest on sophisticated AI models that tightly integrate computational chemistry and medicinal chemistry, building a comprehensive automated system through various tools that covers the full journey from hit compounds to preclinical candidates.

Galixir has developed multiple proprietary algorithms and established a suite of deep learning models spanning 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. Comparative analyses show that Galixir's self-developed models and algorithms have achieved state-of-the-art results in multiple stages, substantially shortening R&D timelines and costs — directly addressing the "high investment, long cycle" dilemma that drug discovery companies face both in China and globally.

On the commercialization front, Galixir has established multiple highly efficient project teams capable of simultaneously conducting multiple early-stage drug discovery programs. The company has already signed strategic cooperation agreements with several renowned domestic and international universities and pharmaceutical companies, ensuring smooth upstream innovation and downstream testing for its drug discovery and development efforts.