Statement

Novogaia develops new medicines from nature. The future of drug discovery lies in learning from natural evolution, shaped by billions of years of optimization, not in forcing synthetic chemistry on complex biology.

Drug discovery is struggling. Despite huge technological advances, drug discovery is failing patients. The industry still relies on the same molecular starting points that worked decades ago, but the low-hanging fruit is gone. As a result, drug development is slower and more costly than ever, and most drugs never reach patients. Human biology demands new starting points.

It is time to learn from nature again. Machine learning, combined with the latest chemical analytics, open up this rich resource for the first time at scale. Novogaia applies these technologies to screen fungi, the most prolific drug producers, unlocking molecular starting points with higher chances of success in the clinic. We build AI systems to rapidly characterize new fungal chemical space and map it to biologically and commercially de-risked targets in areas of unmet need. Our ML systems decode drug-like molecular structures from natural samples better than anyone else.

We are a team of computational biologists and machine learning engineers from leading academic labs at UCL, Imperial College London, ETH Zurich and TU Delft, backed by a former GSK and Merck executive and the pioneer in ML for metabolomics. By applying machine learning to biological datasets, we aim to fundamentally change drug discovery, translating natural diversity into therapeutic breakthroughs.