Microsatellite Classifier Optimization for Early Health-State Detection
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Solution Overview
Problem
Current methods for predicting, detecting, and characterizing health states related to microsatellite alterations are unreliable and difficult to implement at early stages, leading to challenges in prognosis, diagnosis, and treatment selection.
Innovation Solution
A computer-implemented method for constructing an optimized microsatellite classifier through iterative ranking and optimization cycles, using microsatellite loci analysis and genetic algorithms to identify informative subsets, and determining genomic age based on minor allele characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If microsatellite analysis is performed using conventional methods, then detection can be done, but reliability and accuracy are insufficient especially at early stages
Solution Approach 1:
The patent applies preliminary action by performing microsatellite analysis at multiple time points including before treatment (baseline) and during treatment. This early-stage detection capability allows identification of microsatellite alterations before they progress to later stages, improving both reliability and detection accuracy when conventional methods fail
Solution Approach 2:
The patent changes the parameter of detection timing from late-stage only to multiple time points including early stages. By analyzing microsatellite profiles at baseline and during treatment, the system detects alterations earlier and more reliably, resolving the contradiction between reliability and early-stage detection accuracy
2Reliability
If microsatellite profiling is performed to match with databases, then health states can be characterized, but detection is only applicable at later stages leading to unreliability
Solution Approach 1:
The patent performs microsatellite profiling at baseline before treatment and during treatment, rather than waiting for later stages. This preliminary action at multiple time points enables early detection and characterization of health states, eliminating the time delay and improving reliability by capturing microsatellite alterations when they first occur
Solution Approach 2:
The patent implements feedback by comparing microsatellite profiles at different time points (baseline vs. during treatment). This longitudinal comparison provides feedback on microsatellite stability and alterations, enabling reliable detection and characterization of health states without time delays
3Ease of operation
If conventional microsatellite analysis methods are used, then basic detection is possible, but prognosis, diagnosis, and treatment selection become difficult
Solution Approach 1:
The patent uses feedback by comparing microsatellite profiles at baseline and during treatment to monitor stability and detect alterations. This feedback mechanism provides reliable information for prognosis, diagnosis, and treatment selection, making the process both reliable and operationally straightforward
Solution Approach 2:
The patent performs preliminary microsatellite profiling at baseline to establish a reference profile before treatment. This preliminary action enables easier subsequent comparison and interpretation, facilitating prognosis and diagnosis while improving treatment selection reliability through baseline-established reference points
Data Source
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AI summary
The present disclosure provides methods and systems for classifying microsatellite and minor alleles in a sample. Also, the present disclosure provides methods and systems for generating classifiers for conditions based on microsatellite loci and for performing pan-cancer assays. The methods and systems can involve next-generation sequencing of nucleic acid samples from subjects and genotyping microsatellite loci in the samples.