Galixir Secures Nearly $10M in Pre-A Funding to Advance AI-Driven Drug Discovery Platform

36Kr learned that the AI drug R&D platformGalixirCompleted a Pre-A financing round of nearly $10 million, co-led by Source Code Capital and DCM, with Morningside Ventures participating as a follow-on investor. Gaorong Ventures, the lead investor in the angel round, continued to increase its investment. The funds from this round will be primarily used for the development of an AI technology platform and the expansion of technical talent.

Galixir, founded in 2019, is a solutions provider leveraging AI to support new drug R&D. It aims to integrate artificial intelligence with pharmaceutical, chemical, and biological technologies to build an AI-driven drug discovery platform, thereby reducing the development cycle and costs for scientists in the drug R&D process and advancing every stage of new drug development.

Currently, Galixir has established multiple drug R&D modules, including retrosynthesis prediction, drug screening, and molecular design. The company has successfully delivered design solutions to several clients and become a strategic partner of renowned pharmaceutical enterprises in China, collaborating with industry experts to deeply explore the applications of artificial intelligence in drug discovery and development.

Galixir's Service Process

"From an industry-wide perspective, new drug development currently still faces significant pain points—extremely long development timelines and exorbitantly high costs."

According to research data published in *Nature*, the development of a new drug, from project initiation to market approval, takes an average of 10–15 years and costs approximately $3 billion. However, new drug developmentReturn on Investment Is Not Necessarily Equivalent:On the R&D investment front, from 2012 to 2017, the average total R&D expenditure was $148.5 billion, with a growth rate of 3.8%; from 2018 to 2021, the average total R&D expenditure was $180 billion, and the total R&D expenditure in 2021 is projected to reach $188 billion, representing a 38% increase compared to 2012.

However, on the return side, the complexity of the new drug development process, long R&D cycles, and low success rates have left pharmaceutical companies somewhat “willing but unable” in their new drug development efforts. Since 2010, the return on investment for R&D has shown a declining trend year by year. AI can bring new ideas and approaches to multiple stages of drug discovery.

In response, Founder & CEO Li Chengtao stated,Leveraging artificial intelligence, clients can perform deep learning on datasets to train models that automatically handle target identification, molecular design, synthesis, formulation, and drug property prediction and optimization. This significantly reduces client burdens and enhances return on investment. Galixir has strategically prioritized retrosynthesis prediction and chemical reaction prediction, a decision driven by both the team’s technical expertise and critical industry pain points.

Finally, let me introduce the team. Dr. Li Chengtao, Founder and CEO of Galixir, received his bachelor's degree from the Yao Class at Tsinghua University and subsequently earned his Ph.D. in Computer Science from the Massachusetts Institute of Technology (MIT). He has published multiple papers at top-tier artificial intelligence conferences; the teamWe have assembled top-tier talent from the fields of artificial intelligence, chemistry, and biology.The expert advisory team consists entirely of senior professors from top-tier research institutions such as the Massachusetts Institute of Technology, Tsinghua University, Shanghai Jiao Tong University, and Fudan University.

Image source: Ruijing Creative

Investor Perspectives

Huang Yungang, Partner at Source Code Capital, stated:

China’s innovative drug R&D is in a golden period, with new technologies serving as the key to achieving leapfrog breakthroughs. In recent years, the importance of data science in drug development has rapidly increased. Particularly with the integration of machine learning, the combination of data and algorithms has yielded encouraging results in modeling and analyzing complex problems. This, in turn, further promotes the generation of massive datasets and the iteration of algorithms, significantly transforming the methodological framework of drug R&D.

Zeng Zhenyu, Managing Partner at DCM China, stated:

Drug R&D is a field where AI can create significant value. Traditionally, drug development has heavily relied on manual expertise, resulting in lengthy timelines and vast amounts of data whose potential remains largely untapped.

Morningside Ventures stated:

New drug discovery is one of the vertical industries most suited for leveraging the advantages of artificial intelligence (AI) and generating commercial impact. This is not only because target proteins and drug molecules, being highly structured chemical entities, naturally align with AI’s computational logic, but also because the large-scale generation of novel druggable molecules brings more than just efficiency gains to the industry—it systematically creates new supply, thereby driving the digital transformation of the entire sector.

A project lead at Gaorong Ventures stated:

Artificial intelligence is playing a significant role in addressing some of humanity’s most critical challenges, with pharmaceutical development being a key application area. This field also presents substantial challenges, requiring teams to master state-of-the-art AI technologies while possessing a deep understanding of the pharmaceutical industry. Galixir possesses these capabilities.