Microbiome Diagnostic System for Autoimmune Disease Characterization
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Solution Overview
Problem
Current methods for characterizing autoimmune diseases and providing tailored therapies based on microbiome analysis are limited due to technological constraints, failing to effectively diagnose and treat conditions such as autoimmune diseases, gastrointestinal disorders, and other health-related states.
Innovation Solution
A method and system for characterizing autoimmune conditions through microbiome-derived diagnostics and therapeutics, involving the receipt of biological samples, characterization of microbiome composition and functional features, and transformation of this data into predictive models for therapeutic interventions, including probiotic, phage-based, and small-molecule therapies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current microbiome analysis methods are used, then some health conditions can be characterized, but the methods lack the precision and comprehensiveness needed for effective autoimmune disease diagnosis and treatment
Solution Approach 1:
The microbiome analysis is segmented into distinct functional categories (metabolic functions, immune system interactions, structural components) that can be independently characterized and analyzed. This segmentation allows for precise measurement of specific autoimmune-relevant functions without requiring complete analysis of all microbiome aspects, thereby improving measurement precision while managing processing complexity.
Solution Approach 2:
The patent introduces a new dimension of analysis by characterizing not just the presence of microorganisms but their functional capabilities and interactions with the host immune system. This functional dimension adds depth to microbiome characterization, enabling more precise autoimmune disease diagnosis beyond traditional taxonomic classification.
2Loss of information
If comprehensive microbiome characterization is performed, then better diagnostic insights are obtained, but the resources and time required for processing increase significantly
Solution Approach 1:
The patent extracts and focuses specifically on microbiome functions and characteristics most relevant to autoimmune diseases, rather than attempting to characterize the entire microbiome comprehensively. This selective extraction of critical diagnostic information maintains diagnostic completeness for autoimmune conditions while significantly reducing processing time and resource requirements.
Solution Approach 2:
The method performs partial characterization of the microbiome by focusing only on the functional aspects and microbial components most strongly associated with autoimmune pathology. This partial action approach provides sufficient diagnostic information for autoimmune disease identification without the excessive time and resources required for complete microbiome analysis.
3Adaptability or versatility
If current therapeutic approaches are used, then general treatment can be provided, but individualized therapy tailored to specific microbiome profiles is not achievable
Solution Approach 1:
The patent applies local quality by tailoring therapeutic interventions to the specific functional deficiencies or imbalances identified in each patient's microbiome profile. Rather than applying uniform treatment, the system customizes probiotic selections, prebiotic recommendations, and dietary interventions based on the local functional characteristics of each individual's microbiome, thereby achieving high adaptability without requiring overly complex system infrastructure.
Data Source
AI summary
A method for at least one of characterizing, diagnosing, and treating an autoimmune disorder in at least a subject, the method comprising: receiving an aggregate set of biological samples from a population of subjects; generating at least one of a microbiome composition dataset and a microbiome functional diversity dataset for the population of subjects; generating a characterization of the autoimmune condition based upon features extracted from at least one of the microbiome composition dataset and the microbiome functional diversity dataset; based upon the characterization, generating a therapy model configured to correct the autoimmune condition; and at an output device associated with the subject, promoting a therapy to the subject based upon the characterization and the therapy model.