About PyLabs
Bridging the gap between molecular generative AI and physical reality.
Why PyLabs exists
Generative AI has solved the problem of inventing novel molecular architectures, yielding virtual libraries of unprecedented size. However, knowing a molecule can be made is rarely enough; we must investigate what it will do.
Synthesis is expensive. Experimental characterisation is slow. Even computational quantum-chemistry methods like TD-DFT bottleneck the screening process, forcing scientists to abandon millions of candidates untested.
PyLabs was built at the intersection of molecular science and modern AI to break this bottleneck. We predict the physical reality of a molecule before a chemist commits to making it.
Built for molecular discovery
Our architecture and platform are designed with the rigor expected by R&D scientists across pharma, biotech, and specialty chemicals. (Team and founder biographies to be updated).
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