Traditional drug discovery processes can take 10-15 years from target identification to market approval, with high failure rates at each stage.
The average cost of bringing a new drug to market exceeds $2.6 billion, with significant financial risks due to high failure rates.
The vast chemical space and complex biological interactions make it difficult to identify optimal drug candidates.
Only about 10% of drug candidates that enter clinical trials receive FDA approval, highlighting the need for better prediction methods.
To revolutionize drug discovery by combining artificial intelligence with quantum computing, accelerating the development of life-saving treatments while reducing costs and improving success rates.
Pushing the boundaries of what's possible in drug discovery through cutting-edge AI and quantum computing technologies.
Making a meaningful difference in patients' lives by accelerating the development of new treatments.
Genion's platform deeply integrates AI large language models, cheminformatics, quantum simulations, and multimodal data fusion technologies, constructing a unique algorithmic system that is difficult to replicate. At the same time, Genion has independently built an efficient workflow and fully registered intellectual property rights for the platform, ensuring technological exclusivity and leadership.
Genion has accumulated a high-quality proprietary molecule-target database, significantly improving the accuracy and reliability of drug predictions. This database has been intellectually property-registered, further reinforcing its exclusive data advantage.
By establishing long-term strategic partnerships with pharmaceutical companies and research institutions, Genion has developed a broad industry influence and resource network. These deep collaborations provide strong support for platform application and expansion.
Genion boasts an interdisciplinary professional team covering AI, chemistry, biology, and quantum computing, with strong research and innovation capabilities.
The platform continuously optimizes AI models through experimental data feedback, enhancing the accuracy and reliability of drug screening. This closed-loop optimization capability ensures that Genion remains an industry leader in drug development efficiency and success rates.
CEO, PhD
CEO of Alan Scientific Inc., PhD in Molecular Biology, Ohio State University. Former NIH lab director. 35+ publications, 5 patents. Expert in peptide design, molecular genetics, and biopharma industry leadership.
AI Scientist
BSc in Physics, National Tsing Hua University (Taiwan); PhD in Computational Science, University of Maryland; FDA Postdoc (drug discovery)
Administrator, Master
Master in Business Administration, University of Washington. Former founder & operations director, marketing head, and technical recruiter. Rich experience in business operations, marketing, and technical talent acquisition for global tech companies.