Recursion Pharmaceuticals. has filed a patent for a computer system that identifies a subset of compounds through high throughput screening in various cell contexts. The system obtains vectors for each compound, combines them, and prunes the compounds based on similarity to create a smart compound library for drug discovery. GlobalData’s report on Recursion Pharmaceuticals gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Recursion Pharmaceuticals, Vehicle driver physiological monitoring was a key innovation area identified from patents. Recursion Pharmaceuticals's grant share as of January 2024 was 38%. Grant share is based on the ratio of number of grants to total number of patents.
Computer system for identifying compounds in smart compound library
A computer system has been developed for identifying a subset of compounds from a larger pool based on similarity between vectors representing different compounds. The system involves obtaining vectors for each compound through high throughput screening in various cell contexts, combining these vectors to form a combined vector for each compound, and then pruning the compounds to a subset based on the similarity between these combined vectors. The subset of compounds identified can then be used as a reduced size smart compound library for further high throughput screening in pharmaceutical drug discovery. The system utilizes measurements of different features in cell contexts, including color, texture, and size, to create vectors that represent each compound, allowing for efficient identification of compounds with similar characteristics.
Furthermore, the system includes instructions for reducing the dimension of each vector using principal component analysis and kernel functions, as well as computing angles between vectors to determine similarity. The pruning process involves computing geometric relationships between combined vector pairs and iteratively discarding compounds based on these relationships until a subset of compounds is identified. The system also includes normalization techniques and statistical analyses to ensure accurate identification of compounds for the subset. Overall, this computer system offers a sophisticated approach to compound identification and selection, streamlining the process of drug discovery through high throughput screening and vector analysis in various cell contexts.
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