Multi-Omic Model for Personalized Chronic Disease Intervention
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Solution Overview
Problem
Current healthcare approaches for preventing and treating chronic diseases, such as cardiovascular and digestive health conditions, often lack personalization and are limited by insufficient use of genomic and microbiome data, leading to suboptimal patient outcomes and compliance issues.
Innovation Solution
The development of systems and methods that utilize multi-omic models to generate personalized diagnostic and therapeutic signatures from genomic, microbiome, lifestyle, and clinical data, enabling tailored interventions and improving health outcomes through digital therapeutics programs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If general healthcare approaches are used for prevention and treatment of chronic diseases, then implementation is simple and cost-effective, but patient outcomes are suboptimal and compliance is poor
Solution Approach 1:
The patent segments the healthcare system into multiple components: genomic analysis module, microbiome analysis module, lifestyle data collection module, intervention generation module, and compliance monitoring module. Each module processes specific data types and generates targeted outputs, allowing the complex system to be managed through modular, independent components that can be implemented and maintained separately.
Solution Approach 2:
The patent performs preliminary genomic and microbiome characterization of patients before disease onset or progression, establishing baseline data that informs personalized prevention and treatment strategies. This advance characterization allows the system to predict disease risk and tailor interventions before clinical symptoms manifest, improving outcomes while avoiding reactive complex treatments.
2Reliability
If personalized healthcare approaches using genomic and microbiome data are implemented, then patient outcomes improve and compliance increases, but data processing complexity and cost increase
Solution Approach 1:
The patent merges genomic data, microbiome data, lifestyle data, and clinical data into a unified multi-omic data platform. This integrated approach allows simultaneous processing of diverse data types through a single analytical framework, reducing the complexity that would arise from separate analysis systems and enabling comprehensive personalized healthcare recommendations.
Solution Approach 2:
The patent transforms raw genomic and microbiome data into standardized phenotypic parameters and risk scores that can be directly applied to clinical decision-making. By converting complex molecular data into actionable clinical parameters, the system reduces data processing complexity while maintaining the personalization benefits of multi-omic analysis.
3Measurement precision
If comprehensive multi-omic data collection is performed, then diagnostic precision and therapeutic personalization improve, but time and resource requirements increase
Solution Approach 1:
The patent performs preliminary genomic and microbiome sequencing using efficient next-generation sequencing technologies that can characterize an individual's multi-omic profile in a single upfront test. This preliminary data collection establishes a comprehensive baseline that remains valid over time, eliminating the need for repeated extensive sampling and reducing total time investment despite the comprehensiveness of the data collected.
Solution Approach 2:
The patent creates digital replicas of patient data including genomic sequences, microbiome compositions, and lifestyle patterns that can be stored and repeatedly analyzed without requiring additional physical samples. These digital copies enable unlimited re-analysis and updating of interpretations as new research emerges, maintaining diagnostic precision without additional time or resource investment for physical sampling.
Data Source
AI summary
A platform providing methods and systems for prevention and/or treatment of a health condition, where a method can include: simultaneously reducing severity symptoms of the health condition and comorbid conditions upon: receiving a set of samples from one or more subjects; receiving a biometric dataset from one or more subjects; receiving a lifestyle dataset from one or more subjects; returning a genomic single nucleotide polymorphism (SNP) profile and a baseline microbiome state upon processing the set of samples, the biometric dataset, and the lifestyle dataset with a set of transformation operations; generating personalized intervention plans for the one or more subjects upon processing the genomic SNP profile and the baseline microbiome state with a multi-omic model; and executing the personalized intervention plans for the one or more subjects.