Microbiome Diagnostics via Deep Sequencing and Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for characterizing the human microbiome and providing therapeutic measures based on microbiome analysis are limited, failing to effectively address health conditions and tailor therapies to specific individuals due to technological constraints.
Innovation Solution
A method involving deep sequencing of microorganism DNA to identify and classify microbiome compositions associated with antibiotic usage, using reference sequences and probability values to determine treatment courses for individuals, including administering specific bacteria or prebiotics to address microbiome imbalances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current methods are used for microbiome characterization, then the process is simpler and less resource-intensive, but the precision and depth of analysis are insufficient to identify specific health conditions and tailor therapies
Solution Approach 1:
The patent segments the microbiome analysis into distinct functional categories (e.g., butyrate production, bile acid metabolism, vitamin synthesis) and identifies specific bacterial taxa within each category. This segmentation allows for precise characterization of microbiome composition and function without requiring analysis of every possible microbial parameter, thereby improving measurement precision while managing system complexity through focused, targeted analysis.
2Reliability
If deep sequencing and comprehensive analysis are implemented, then the ability to identify antibiotic-induced microbiome alterations improves, but the cost and computational resources required increase significantly
Solution Approach 1:
The patent extracts and focuses on specific, clinically relevant bacterial taxa and functional pathways that are most indicative of antibiotic-induced microbiome alterations. Rather than analyzing all microbial data generated by deep sequencing, the system identifies and isolates key diagnostic markers (such as specific genera or functional categories) that reliably indicate health status. This extraction approach maintains high diagnosis reliability while reducing the volume of data that requires computational processing and interpretation.
3Adaptability or versatility
If current probiotic therapies are used, then treatment is broadly applicable, but the therapy cannot be tailored to specific individual microbiome compositions or health conditions
Solution Approach 1:
The patent applies local quality by matching specific probiotic formulations to specific deficiencies identified in an individual's microbiome composition. Rather than administering a standardized probiotic mixture to all patients, the system identifies which specific bacterial taxa or functional pathways are depleted in each patient and prescribes probiotics targeted to restore those specific deficits. This personalized approach increases therapy adaptability while managing complexity through a systematic method of identification and matching.
4Loss of information
If comprehensive microbiome analysis is performed to identify specific health conditions, then the ability to provide targeted therapeutics improves, but the time and resources for processing and interpreting data increase
Solution Approach 1:
The patent employs preliminary action by pre-establishing reference databases of healthy microbiome compositions and known pathological patterns across multiple populations. These reference data sets are curated and organized in advance, allowing the diagnostic system to compare individual patient results against established benchmarks without requiring de novo analysis of every possible parameter. This preliminary preparation of reference information enables rapid, accurate interpretation of patient data while retaining comprehensive microbiome information for diagnostic decision-making.
Data Source
AI summary
Methods, compositions, and systems are provided for detecting one or more effects of antibiotic usage for an infectious disease or other health condition on the microbiome of an individual, monitoring such effects, and/or determining, displaying, or promoting a therapy for such an effect. Methods, compositions, and systems are also provided for generating and comparing microbiome composition and/or functional diversity datasets. Methods, compositions, and systems are also provided for generating a characterization model for antibiotic usage.