Galixir Leverages AI to Discover Novel Preclinical Candidate for Autoimmune Diseases

Galixir Identifies Novel Preclinical Candidate Compound for Autoimmune Diseases Using Its Proprietary AI-Driven Drug Discovery Platform, Pyxir®Galixir has identified a novel preclinical candidate compound (PCC) for the treatment of autoimmune diseases using its proprietary artificial intelligence drug discovery platform, Pyxir®. The preclinical compound, generated, screened, and iteratively refined by AI, features a completely new scaffold structure and independent intellectual property space. It demonstrates excellent performance in efficacy, pharmacokinetics, and safety, with promising results shown in both in vitro and in vivo preclinical studies. The successful discovery of this preclinical candidate validates Galixir’s closed-loop, AI-centric, technology-driven drug discovery capabilities.

Precise Localization of PCC, AI Offers New Perspectives

Autoimmune disease (AID) refers to a group of diseases in which the human immune system mistakenly attacks the body's own organs, tissues, or cells, causing damage. To date, nearly a hundred types of autoimmune diseases have been identified globally, including rheumatoid arthritis, systemic lupus erythematosus, ulcerative colitis, and multiple sclerosis. A large number of patients with autoimmune diseases worldwide require long-term treatment. Despite the approval and marketing of various drugs, there remains a significant unmet clinical need.

After Galixir confirmed the target and completed the collection and analysis of relevant data, it initiated an AI-based de novo design of small molecules. Following data processing and model training, the AI-powered drug discovery platform Pyxir® rapidly generated tens of millions of novel virtual molecules. After a series of screenings for drug-likeness, synthetic feasibility, and patent-related rules, combined with domain knowledge from computational chemistry, medicinal chemistry, and biology, Galixir identified three compounds with novel scaffolds within one month. Wet-lab experiments validated that all three compounds exhibited high activity (EC50 < 100 nM), with one compound showing an EC50 below 10 nM, making it a highly promising hit compound.

Throughout the Hit→Lead→PCC optimization phase, approximately 80 compounds were iterated. Three scaffold series of compounds progressed concurrently, with experimental evaluation data on activity, selectivity, metabolic stability, safety, and more being continuously fed back into the Pyxir® platform to further optimize and re-validate the candidate molecules. After iterative cycles via the AI drug discovery platform, the most active Hit scaffold series advanced into the Lead optimization stage. Ultimately, Galixir identified a preclinical candidate compound within this scaffold series. Pharmacokinetic and efficacy experiments showed that, compared to the current best-in-class clinical positive control, this compound exhibited lower toxicity, reduced infection risk after discontinuation, and several other potential advantages. Following rigorous evaluation by experts in the relevant field, the compound was officially designated as the project’s preclinical candidate compound (PCC) and is now set to enter the preclinical development stage.

Empowering New Drug Discovery, AI Has a Long Way to Go

The development of new drugs is often compared to finding a perfectly designed "key" that precisely unlocks the "lock" of disease-causing genes, thereby treating diseases by modulating certain mechanisms. How to overcome numerous obstacles and find this "key" in the shortest possible time? Galixir's AI drug discovery platform, Pyxir®, offers a new approach to solving this problem. Particularly, advancements in data processing technology and computing power provide foundational technical support and innovative insights for AI-driven drug discovery.

Dr. Chengtao Li, founder and CEO of Galixir, stated: Drug development is a complex systematic project that requires balancing multiple parameters to achieve optimal results. AI technology has unique advantages in taking various indicators into account. This PCC milestone has validated the excellent performance of the artificial intelligence drug discovery platform Pyxir® as well as Galixir's closed-loop capabilities in drug discovery. However, this is only the first step in our long journey. We look forward to collaborating with more pharmaceutical companies in the near future to jointly accelerate drug discovery pipelines using AI and search for more brilliant stars in the compound universe that can cure human diseases. This is also the original intention behind naming the company Galixir (Galaxy + Elixir).

Facing numerous unmet clinical needs, Galixir will next focus on differentiated pipelines that can bring more benefits to the pharmaceutical industry, especially projects targeting undruggable or difficult-to-drug targets, continuously tackling new challenges in the pharmaceutical field and shouldering its social responsibility. After years of deep cultivation in mechanism research, drug design, and wet-lab testing, with the rapid acceleration of data accumulation, Galixir is gradually moving towards the global optimization of AI technology.