Insilico Medicine’s Generative AI Patent Provides Advantage in AI Drug Discovery Race

The process covered by the patent describes the use of deep neural networks(DNNs) – machine learning modules which process data and predict new outputs in order to “generate novel objects that are indistinguishable from data objects.” 

Importantly, the patent covers a computer method for generating an object that satisfies a condition using one or more deep neural networks. Not only does the patent cover using DNNs to design a new molecule, but also the processing of data to arrive at that point, the comparison between the new molecule and the desired molecule, the selection of an object best meeting the desired conditions, obtaining a physical form of the new structure, and validating that physical form. 

Fig 1. Combining various state-of-the-art machine learning methods, Chemistry42 delivers diverse, high-quality molecular structures within hours. As the structures are generated, they are dynamically assessed using the reward and scoring modules in the platform.

Putting the Generative AI for Chemistry Patent into Action