A method for predicting drug activity and its application

A drug activity and prediction method technology, applied in the field of biomedicine, can solve problems such as insufficient guidance for new drug research and development, and achieve low cost, accurate results, and high efficiency

Active Publication Date: 2020-01-21
武汉百药联科科技有限公司 +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, almost all previous studies believed that the occurrence of disease was due to the change of a single gene locus. In recent years, people have gradually realized that most diseases are caused by multiple disease-causing genes (Hopkins, A.L. (2008) .Network pharmacology:the next paradigm in,drug discovery.Nat.Chem.Biol.4:682-690.), and the current proven link between disease and single gene variation is not enough to guide the development of new drugs

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  • A method for predicting drug activity and its application
  • A method for predicting drug activity and its application
  • A method for predicting drug activity and its application

Examples

Experimental program
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Effect test

Embodiment 1

[0061] Using the method of the present invention to predict drugs with activity in the treatment of bipolar disorder

[0062] figure 1 It is a flowchart of the method for predicting the drug activity of the present invention. Depend on figure 1 As can be seen, the predictive method of drug activity of the present invention comprises the following steps:

[0063] 1. Collect target and drug activity information of human marketed or drug candidates

[0064] Search drug target databases DGIdb, TTD and DrugBank to collect drug-target related information. Information about the activity of drugs on the market or under development is obtained from the three databases of DrugBank, TTD and ClinicalTrials. figure 2 It is a flow chart of data processing for obtaining drug activity and target information in the method for predicting drug activity of the present invention, wherein MetaMap, UMLS::Interface and UMLS::Similarity are standardized processes for disease description. Depend ...

Embodiment 2

[0107] Using the method of the present invention to predict drugs with activity in treating depression

[0108] Steps 1 to 5 of this embodiment are the same as in Embodiment 1, and the other steps are as follows:

[0109] 6. Predicting drugs with activity in treating depression

[0110] Input the four eigenvalues ​​of 5,451 drugs corresponding to different diseases into the activity prediction model (including three algorithms of SVM, NB, and LR) for activity prediction. For each drug, we considered the drug to be potentially active in treating depression if the results of any two of the three algorithms predicted antidepressant activity. RESULTS: Antidepressant activity was predicted for 182 of 5,451 drugs. By querying the DrugBank, TTD, and ClinicalTrials drug activity databases, 68 (37%) of the 182 potential drugs had clinical antidepressant activity, while the proportion of antidepressant drugs in the background database was 283 / 5451 (5.2 %), so the effective rate of th...

Embodiment 3

[0112] Using the method of the present invention to predict drugs with activity in treating schizophrenia

[0113] Steps 1 to 5 of this embodiment are the same as in Embodiment 1, and the other steps are as follows:

[0114] 6. Drugs that are predicted to be active in the treatment of schizophrenia

[0115] Input the four eigenvalues ​​of 5,451 drugs corresponding to different diseases into the activity prediction model (including three algorithms of SVM, NB, and LR) for activity prediction. For each drug, as long as the results of any two of the three algorithms predicted anti-schizophrenic activity, we considered the drug to have potential activity in the treatment of schizophrenia. The results showed that 161 of 5,451 drugs had predicted antischizophrenic activity. By querying the DrugBank, TTD and ClinicalTrials drug activity databases, 78 (48%) of the 161 potential drugs had clinical anti-schizophrenia activity, while the proportion of anti-schizophrenia drugs in the ba...

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Abstract

The invention discloses a drug activity prediction method and application thereof. The method comprises the following beneficial effects: step one, targets of human on-market or under-study drugs andtreatment activity information are collected by inquiring drug target interaction database information; step two, searching for a plurality of virulence gene databases, collecting disease associationgenes, and according to activity rates of drugs corresponding to the disease association genes, different assignment values of disease association genes of different database sources are given; step three, feature attributes of the drug targets and the disease association genes are built; step four, a machine learning prediction model is constructed; step five, a model prediction result is evaluated; and step six, a drug with activity to a specific disease is predicted. According to the invention, the drug activity prediction method can be used as a GPS in the drug discovery field; disease association genes can be identified efficiently; the effective guidance is provided for prediction, research and development of active drugs; and a novel method and idea is provided for the drug discovery field in future.

Description

technical field [0001] The invention belongs to the technical field of biomedicine, and in particular relates to a method for predicting drug activity and its application. Background technique [0002] Drug research and development is a systematic project with long cycle, high cost, high risk, fierce competition and high profit. According to statistics, it takes 10-15 years for a new drug to be produced from conception, laboratory lead compound identification, optimization, clinical trials to final marketing, and the research and development costs are as high as more than 800 million US dollars (DiMasi, J.A., Hansen, R.W., and Grabowski ,H.G.(2003).The price of innovation:new estimates of drug development costs.J.Health Econ.22:151-185.), and this cost is still increasing year by year, according to Tufts Center for the Study of Drug Development, CSDD) 2014 report, this figure has now grown to $2.558 billion (http: / / csdd.tufts.edu / news / complete_story / pr_tufts_csdd_2014_cost_...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G16H50/70G16C20/50G16C20/70G16C20/90
CPCG16C20/50G16C20/70G16C20/90
Inventor 张红雨全源朱丽达李姜柳叶茂杨庆勇黄清
Owner 武汉百药联科科技有限公司
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