Deep learning drug interaction prediction method and device, medium and equipment

Abstract

The invention provides a deep learning drug interaction prediction method and device, a medium and equipment. The method comprises the following steps: acquiring drug molecule information of two to-be-predicted drugs; the atomic-scale network encodes each piece of drug molecule information, captures interaction information between atoms and chemical bonds, and outputs an encoded drug molecule map to represent zatomj; the molecular level network uses a multi-head attention mechanism to extract the relationship between different drug molecules from each drug molecular map expression zatomj, and outputs a molecular map expression zmolj; and converting the output molecular maps zmol1 and zmol2 of the two drugs into a vector so as to obtain a drug interaction prediction result. According to the method, the problem that side information cannot be fully considered in a traditional framework can be solved, and relation information among different drug molecules can be captured, so that the accuracy of a prediction result is improved.

Description

Technical field [0001] The present invention relates to the field of pharmaceutical technology, more particularly, to a deep learning drug interaction prediction method, apparatus, medium and apparatus. Background [0002] Today, multipharmacy has become a common phenomenon, which also leads to increased odds of drug interactions. Drug-Drug Interaction (DDI) is when a patient takes two or more drugs at the same time, and the efficacy of one drug is affected by the effect of another drug, resulting in a weakening of the drug effect or toxic side effects. Therefore, in the case of combination drugs, how to predict and detect possible adverse drug interactions in advance, thereby reducing potential risks and promoting safe drug combination prescription, has become a major problem that needs to be solved urgently in the field of bioinformatics. [0003] With the establishment and development of more and more public data sets, there is great potential for DDI prediction using predicti...

AI Technical Summary

Problems solved by technology

[0008] In order to overcome the shortcomings and deficiencies in the prior art, the purpose of the present invention is to provide a deep learning drug interaction prediction method, device, medium and equipment; this method can solve the problem that the side information cannot be fully considered in the traditional framework, and can capture The relationship information between different drug molecules can be obtained to improve the accuracy of prediction results

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