System and method for the latent space optimization of generative machine learning models
US11610139B2 · kind B2 · utility
2Cited by
4References
12Claims
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Key dates
| Filing date | Jul 15, 2022 |
| Grant date | Mar 21, 2023 |
| Priority date | — |
| Expiry date | Jul 15, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16C20/90
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system and method for optimizing the latent space in generative machine learning models, and applications of the optimizations for use in the de novo generation of molecules for both ligand-based and pocket-based generation. The ligand-based optimizations comprise a tunable reward system based on a multi-property model and further define new measurable metrics: molecular novelty and uniqueness. The pocket-based optimizations comprise an initial multi-property optimization followed up by either a seed-based optimization or a relaxed-based optimization.
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