Chronic constipation intestinal flora transplantation donor-acceptor matching method based on multidimensional flora characteristics and machine learning and application of chronic constipation intestinal flora transplantation donor-acceptor matching method

By analyzing the intestinal microbiota sequencing data and constructing a multi-dimensional characteristic difference matrix, and evaluating donor scores using a random forest model, the problem of poor efficacy of intestinal microbiota transplantation treatment in the existing technology is solved, and higher treatment success is achieved rate and clinical effect.

CN119314563AActive Publication Date: 2025-01-14SHANGHAI BIOTECAN PHARMA +2
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Patent Information

Application Number
CN202411380777.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-09-30
Publication Date
2025-01-14
Estimated Expiration
2044-09-30

AI Technical Summary

Technical Problem

The response rate of existing intestinal microbial transplant treatment is only about 70%, some patients have failed to benefit, and there is a lack of effective donor microbial characteristics screening methods to improve the therapeutic effect.

Method used

By analyzing the 16s rRNA intestinal microbiota sequencing data of donor and acceptor, a multi-dimensional characteristic difference matrix was constructed, high-contribution characteristics were screened out, feature weights were evaluated using a random forest machine learning model, donor scores were calculated, and the optimal donor was selected. to improve treatment success rate.

Benefits of technology

It significantly improves the success rate and clinical effect of intestinal microbial transplant treatment, ensures accurate matching between donor and recipient, and improves the treatment response rate and the quality of life of patients.

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Abstract

The invention relates to a chronic constipation intestinal flora transplantation donor-receptor matching method based on multidimensional flora characteristics and machine learning and application of the chronic constipation intestinal flora transplantation donor-receptor matching method. 16s rRNA intestinal flora data of a donor and a receptor before FMT treatment and retrospective data of FMT clinical treatment effect are collected; the characteristics of flora abundance difference, metabolic pathway activity difference, enzyme activity difference, species diversity difference and the like between a donor and a receptor are calculated, the characteristics are selected through principal component analysis, and high-contribution characteristics capable of explaining 90% variance are screened out. According to the method, a random forest machine learning model is used for screening out characteristic markers related to the treatment effect, the weights of the markers in the model are calculated, and finally the optimal donor is screened out by performing weighted scoring and sorting on the flora characteristics of each donor.
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Citation Information

Patent Citations

  • Intestinal flora preparation capable of directionally proliferating and used for transplanting intestinal flora as well as preparation method and application of intestinal flora preparation

    CN114181855A

  • Donor and recipient matching algorithm for treating diabetes by flora transplantation

    CN111768810A

  • Donor and receptor typing method for treating ulcerative colitis by intestinal flora transplantation

    CN112614596A

  • Establishment method of artificial intelligence model for predicting prognosis of ARDS patient

    CN115249543A

  • Donor and receptor matching method for flora transplantation

    CN117577172A

Cited By

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    CN122087477A