AI-assisted drug discovery company Galixir announced the completion of a Pre-A funding round of several million US dollars, co-led by Source Code Capital.

Galixir has announced the completion of a nearly $10 million Pre-A funding round. The round was co-led by Source Code Capital and DCM, with 5Y Capital participating as a follow-on investor. Gaorong Ventures, the lead investor in the company's angel round, continued to increase its stake. The proceeds will be primarily directed toward R&D investments, including the development of its technology platform and the expansion of its technical team.

Founded in 2019, Galixir is an AI-powered solutions provider for drug discovery. The company is dedicated to combining cutting-edge artificial intelligence with pharmaceutical, chemical, and biological technologies to build an AI-driven drug discovery platform — helping scientists explore broader druggable space, reduce R&D costs, and shorten the timeline for bringing new drugs to market. In November 2019, Galixir was selected for the Merck Group China Accelerator program.

According to research published in Nature, developing a new drug from project initiation to regulatory approval takes an average of 10 to 15 years and nearly $3 billion in R&D costs — a figure that continues to rise year over year. Deloitte research shows that return on investment for new drug development at large biopharmaceutical companies has fallen to a nine-year low of just 1.9%.

For major pharmaceutical companies spending over $10 billion annually on R&D, such massive investment no longer guarantees commensurate returns. This decline in R&D returns has, in turn, accelerated the division of labor between large pharmaceutical firms and technology-focused R&D companies.

As traditional drug development methods continue to face dual bottlenecks of cost and success rate, an increasing number of scientists are turning to artificial intelligence — a field that has gained significant traction in recent years — hoping that AI will spark new kinds of insight.

In response, Galixir, which is committed to AI-enabled drug discovery, has developed corresponding solutions and completed two consecutive funding rounds — angel and Pre-A — within just six months, raising over $10 million in total.

"With our AI-based technology, clients can use deep learning models to learn from datasets. Once trained, these models can automatically handle molecular design, synthesis planning, and drug property prediction and optimization — truly reducing client burden and improving returns," said Dr. Chengtao Li, founder and CEO.

To date, Galixir has built multiple drug discovery modules including retrosynthetic reaction prediction, drug screening, and molecular design. It has delivered design solutions for several clients and established strategic partnerships with leading domestic pharmaceutical companies, working alongside industry experts to explore applications of AI in drug R&D.

The company has also published multiple influential academic papers at top international AI conferences including ICML and NeurIPS.

Galixir has now assembled world-class talent across AI, chemistry, biology, and related fields. Core team members hail from top institutions including MIT, Yale University, Tsinghua University, and Peking University, as well as major internet companies and multinational pharmaceutical firms.

Dr. Chengtao Li, founder and CEO, graduated from Tsinghua University's Yao Class before earning his PhD in computer science from MIT. He has published numerous papers at top AI conferences and is recognized as one of the leading scholars in the AI + chemistry interdisciplinary space.

The company's expert advisory team comprises senior professors and researchers from top institutions including MIT, Tsinghua University, Shanghai Jiao Tong University, and Fudan University.

Yungang Huang, Partner at Source Code Capital, commented: "With the convergence of technological transformation, talent accumulation, and national strategy, China's innovative drug R&D is in a golden cycle. New technologies are the key to leapfrog breakthroughs for Chinese innovative drugs. In recent years, the importance of data science in drug discovery has been rising rapidly — particularly since the introduction of machine learning, where the combination of data and algorithms has achieved encouraging results in modeling and analyzing complex problems. This, in turn, further promotes the production of massive datasets and the iteration of algorithms, significantly transforming the methodological system of drug R&D. Galixir's team has exceptionally strong interdisciplinary backgrounds in machine learning, chemistry, and biology, coupled with rich engineering experience. We believe the team can achieve major accomplishments in the AI + new drug R&D field."

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