SNP Panel for COVID-19 Severity Prediction
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Solution Overview
Problem
Current methods lack the ability to accurately predict the severity of COVID-19 disease progression, making it difficult for healthcare providers to timely intervene with appropriate measures such as ICU transfer or vaccination strategies, especially during pandemics with limited resources.
Innovation Solution
A method utilizing 381 specific single nucleotide polymorphisms (SNPs) as markers to predict the severity of COVID-19 disease, allowing for personalized risk assessment and targeted vaccination recommendations by analyzing genetic data from patients using DNA arrays and bioinformatic analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If genetic analysis methods are used to predict disease severity, then prediction accuracy is improved, but device complexity and cost increase
Solution Approach 1:
The patent segments the complex genetic analysis into a focused panel of 381 specific SNPs, analyzing only the most relevant genetic markers associated with COVID-19 severity. This segmentation maintains high prediction accuracy while reducing the complexity compared to whole-genome sequencing or broader genetic panels.
2Reliability
If comprehensive genetic screening is performed, then prediction reliability is improved, but loss of time increases
Solution Approach 1:
The patent performs preliminary action by pre-selecting and validating the 381 SNPs that are most strongly associated with COVID-19 severity before the actual testing. This pre-prepared panel allows for rapid analysis during clinical practice, maintaining high reliability while minimizing the time required for genetic screening.
Solution Approach 2:
The patent changes the parameter of analysis from comprehensive genomic sequencing to a targeted SNP panel of 381 specific markers. This parameter change reduces the analytical time significantly while maintaining prediction reliability by focusing on the most clinically relevant genetic variations.
3Measurement precision
If more SNPs are analyzed, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent applies partial action by analyzing exactly 381 SNPs - enough to achieve high prediction accuracy for COVID-19 severity, but not so many as to create unnecessary complexity. This optimized number balances precision requirements with practical implementation feasibility.
Data Source
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AI summary
The invention relates to a method for predicting the severity of the course of a Covid-19 disease using single nucleotide polymorphism (SNP) markers.