Gut Microbiome Classifier for Personalized Statin Therapy

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Solution Overview

Problem

Current statin therapies for atherosclerotic cardiovascular disease (ACVD) exhibit significant heterogeneity in efficacy and are associated with adverse side effects, lacking personalized approaches to optimize treatment intensity and minimize side effects such as myopathy and type II diabetes risk.

Innovation Solution

A computer-implemented method using a classifier to process gut compositional data, including taxonomic abundance, diversity, and enterotype, to generate a gut microbiome signature for predicting statin therapy safety and efficacy, determining a recommended therapy intensity, probiotic, prebiotic, or combination therapy based on insulin resistance and blood hydroxymethylglutarate levels.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If statin therapy is prescribed to treat or prevent atherosclerotic cardiovascular disease, then efficacy in decreasing ACVD-associated mortality is improved, but heterogeneity in lowering LDL cholesterol and adverse side effects (myopathy, disrupted glucose control, type II diabetes risk) worsen

Engineering Contradiction:

Improveefficacy in decreasing ACVD-associated mortalityVSAvoidadverse side effects including myopathy, disrupted glucose control, and type II diabetes risk

Core Design Contradiction:

ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The patent applies local quality by using gut microbiome composition data to identify specific subpopulations with distinct responses to statin therapy. Different microbiome profiles (e.g., presence of specific taxa, diversity indices, enterotypes) are associated with differential efficacy and safety outcomes, allowing personalized therapy recommendations tailored to each individual's microbiome characteristics rather than applying a uniform treatment approach to all patients

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The patent employs parameter changes by measuring and analyzing multiple gut microbiome parameters (taxonomic abundance, diversity indices, enterotype classification) to predict statin response. These microbiome parameters serve as biomarkers that can identify patients at risk for adverse effects or poor efficacy, enabling clinicians to adjust therapy intensity or select alternative treatments based on individual microbiome parameter profiles

Inventive Principle:

Principle #35Parameter changes

2Adaptability or versatility

If personalized approaches to statin therapy are implemented, then treatment optimization and side effect minimization are improved, but current methods remain limited and lack comprehensive personalization

Engineering Contradiction:

Improvepersonalized treatment optimizationVSAvoidcomplexity of personalized therapy determination

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent uses gut microbiome composition data as an intermediary biomarker to bridge the gap between patient characteristics and statin therapy response. The microbiome profile serves as a measurable intermediary that can predict efficacy and safety outcomes, simplifying the personalization process by providing objective, quantifiable markers that guide therapy selection and intensity determination without requiring complex multi-parameter assessments

Inventive Principle:

Principle #24Intermediary (Mediator)

3Measurement precision

If gut microbiome data is analyzed to predict statin therapy outcomes, then personalized therapy recommendation accuracy is improved, but data processing and classification complexity increases

Engineering Contradiction:

Improveprediction accuracy of therapy recommendationVSAvoidcomplexity of classifier processing and data analysis

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent applies segmentation by dividing gut microbiome data into distinct analytical categories: taxonomic abundance of specific taxa, diversity indices (alpha and beta diversity), and enterotype classifications. This segmented approach allows systematic analysis of different microbiome aspects that independently or collectively predict statin response, making the complex data more manageable and interpretable while maintaining prediction accuracy

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS20230178243A1Predicting a recommended therapy from gut compositional data

Publication Date: 2023.06.08 INSTITUTE FOR SYSTEMS BIOLOGY

AI summary

Predicting therapy from gut compositional data is described herein. In an example, a system accesses gut compositional data including a taxonomic abundance, a taxonomic diversity, and/or an enterotype for a subject. The system generates a gut microbiome signature for a safety and an efficacy of a statin therapy for the subject by applying a classifier to the gut compositional data. The safety of the statin therapy is characterized by an insulin resistance of the subject and the efficacy of the statin therapy is characterized by a blood hydroxymethylglutarate level of the subject. The system determines a recommended therapy for the subject based on the gut microbiome signature and one or more taxa of the gut compositional data of the subject. The recommended therapy is selected from a statin therapy intensity, a probiotic therapy, a prebiotic therapy, or a combination thereof. The system outputs the recommended therapy.