Quick and precise high-throughput drug screening system based on deep learning

Abstract

The invention discloses a quick and precise high-throughput drug screening system based on deep learning. The drug screening system comprises a picture preprocessing module and a neural network module, wherein the picture preprocessing module comprises a channel merging module and a picture standardization module; the channel merging module merges different cell single-color channel pictures intothe multi-channel picture representation, wherein the merged picture tensors are represented as [H,W,C]; the picture standardization module standardizes the input multi-channel picture data into the tensor representation of [70,70,C]; the neural network module is connected with the picture standardization module, the input data of the neural network module is standardized picture tensors, and finally the trained neural network is subjected to final prediction classification prediction. The drug screening system DeepScreen based on deep learning has the advantages of being high in throughput, precise, efficient, fast, convenient, low in cost and resistant to interference, and has a worth-concerning practical and application prospect.

Description

technical field [0001] The invention relates to the technical field of biomedicine, specifically, a fast, accurate and high-throughput drug screening system based on deep learning. Background technique [0002] According to statistics, it takes 10-14 years and more than 200 million U.S. dollars for each new drug to go on the market, from testing to marketing. How to speed up the discovery and testing of new drugs has always been the key and difficulty in accelerating the drug R&D stage. In recent years, the development of biochemistry, physiopathology and other disciplines has provided new means of drug screening, and some drug screening models at the molecular and cellular level have emerged, and with the development of more advanced detection technology, automation technology and computer technology, In the late 1990s, a high throughput screening technology (High throughput screening, HTS) was developed. HTS mainly relies on automated operating systems, namely laboratory ...

AI Technical Summary

Problems solved by technology

Chinese patent 2017101273955 discloses an intelligent lead compound discovery method based on convolutional neural network, which solves the problems of low efficiency and low accuracy of virtual screening of lead compounds. This method first converts the compound structural formula into a plane picture, and performs black and white and Inverse color processing, all pictures are classified according to the activity properties of the compound and digitally labeled according to the category, and input into the system; select a part of the pictures as the training set for the convolutional neural network to perform deep learning on the classification problem, and the rest as the test set to evaluate the model; After the learning is completed, input the same processed pictures other than the training set and the test set for the system to calculate and predict the probability of its corresponding active attribute

However, in the prior art, there is no report about the fast and accurate high-throughput drug screening system based on deep learning of the present invention.

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