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  Artificial Intelligence

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

by Andrii Buvailo, PhD  (contributor )   •   Nov. 17, 2023  

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Companies are increasingly turning to generative artificial intelligence (AI) to develop new therapeutics, giving biotech companies with patents on these technologies a distinct advantage in the tech-enabled pharmaceutical future. One of the pioneers in using generative AI to process biological and chemical data in order to design new molecules is biotech company Insilico Medicine. The Company filed a patent application on its mutual information adversarial autoencoder in 2018 – and that patent was approved in 2022. 

The patent covers Insilico’s proprietary system for using generative AI to produce novel small molecules that can be further synthesized, tested and advanced into clinical assets – the algorithmic backbone to its Chemistry42 engine that has produced new possible treatments for diseases like fibrosis, cancer, and COVID-19.

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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

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