Microbiome Characterization Models for Cutaneous Diagnosis and Therapy
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Solution Overview
Problem
Current methods for characterizing the human microbiome and developing personalized therapeutic measures for cutaneous conditions are limited by inadequate sample processing techniques and data analysis, leading to insufficiently effective diagnostics and therapies.
Innovation Solution
A method and system for characterizing the microbiome composition and functional features of a population, generating datasets, and transforming these into models to diagnose and treat cutaneous conditions through microbiome-derived diagnostics and therapeutics, including probiotic, phage-based, and small-molecule-based therapies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current sample processing and data analysis techniques are used, then the process is simpler and more resource-efficient, but the characterization precision and diagnostic effectiveness are insufficient
Solution Approach 1:
The patent segments the microbiome analysis process into distinct functional modules: sample collection, DNA extraction, 16S rRNA gene amplification, next-generation sequencing, and bioinformatics analysis. Each module is optimized independently to achieve high precision while managing complexity through standardized protocols and automated processing pipelines.
Solution Approach 2:
The patent introduces standardized reference microbiomes and computational algorithms as intermediaries between raw sequencing data and diagnostic conclusions. These intermediaries enable objective, reproducible characterization by comparing subject microbiomes against established references, thereby improving measurement precision without proportionally increasing complexity.
2Reliability
If comprehensive microbiome characterization is performed, then diagnostic accuracy and personalized therapy effectiveness improve, but data processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary actions by establishing reference microbiomes from healthy populations and pre-developing diagnostic algorithms before actual subject analysis. This allows rapid comparison and diagnosis for individual subjects, achieving high diagnostic accuracy without requiring time-consuming de novo analysis for each patient.
Solution Approach 2:
The patent creates computational copies of reference microbiomes and uses these replicated models for rapid comparison against subject samples. This copying approach enables simultaneous analysis of multiple subjects against the same reference framework, reducing overall processing time while maintaining diagnostic reliability.
3Reliability
If personalized probiotic therapies are developed based on individual microbiome profiles, then treatment effectiveness increases, but the complexity of therapy formulation and delivery increases
Solution Approach 1:
The patent applies local quality by formulating probiotic therapies tailored to specific deficiencies identified in each subject's microbiome profile. Rather than using standardized formulations, the therapy composition is customized to address local imbalances in specific bacterial taxa or functional pathways, thereby improving effectiveness while using modular probiotic components to manage formulation complexity.
Solution Approach 2:
The patent changes key parameters of probiotic formulations based on microbiome characterization results, including strain selection, dosage levels, and delivery timing. These parameter adjustments are made systematically according to predefined thresholds and algorithms, enabling personalized therapy optimization without requiring complex manual formulation processes for each patient.
Data Source
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AI summary
A method for at least one of characterizing, diagnosing, and treating a cutaneous condition 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 cutaneous 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 cutaneous condition; and at an output device associated with the subject, promoting a therapy to the subject based upon the characterization and the therapy model.