Probe Set Optimization for Rapid Pathogen Detection
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Solution Overview
Problem
Current diagnostic methods for infectious diseases in tropical developing countries are inefficient due to the need for extensive probe sets in hybrid selection, leading to resource-intensive and time-consuming processes, and often result in misdiagnoses, as they struggle to detect a broad spectrum of pathogens and emerging threats effectively.
Innovation Solution
A method involving the construction of candidate probes with hybridization patterns along a reference sequence, followed by a set cover solving process to reduce the number of probes, and subsequent synthesis of selected probes for hybridization and sequencing, enabling more rapid and cost-efficient pathogen detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a high number of candidate probes are used for hybrid selection to ensure comprehensive pathogen detection, then the detection coverage is improved, but the resource consumption and time required for analysis increase significantly
Solution Approach 1:
The patent extracts and removes redundant probes from the candidate probe set through iterative comparison. Probes that are shifted by less than a threshold distance and have mismatches within a threshold are identified as redundant and removed, keeping only the essential probes needed for comprehensive detection.
Solution Approach 2:
The patent designs candidate probes to collectively cover the entire target sequence space, where each probe serves multiple potential target regions. The probe set is constructed to be universally applicable across different pathogen variants while minimizing the total number of probes needed.
2Quantity of substance
If candidate probes are compared iteratively to reduce redundancy, then the number of probes is reduced, but the computational complexity and time for probe selection increase
Solution Approach 1:
The patent performs preliminary ordering of candidate probes before the iterative comparison process. By establishing an initial order, the algorithm can efficiently proceed through the probe list in a single pass, comparing each probe only against previously selected probes rather than all possible combinations.
Solution Approach 2:
The patent segments the probe selection process into discrete iterative steps, where in each iteration one probe is selected and redundant probes are removed. This breaks down the complex optimization problem into manageable sequential operations that can be executed efficiently.
3Ease of manufacture
If the probe selection depends on candidate probe ordering, then the selection process is simpler, but the output quality and optimality of the selected probe set deteriorates
Solution Approach 1:
The patent implements a dynamic probe selection process where the candidate probe list is reordered in each iteration based on the currently selected probes. This allows the algorithm to adapt to the evolving probe set and make optimally informed selections at each step, improving overall probe set quality while maintaining computational efficiency.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for comprehensive and rapid pathogen detection, reducing the number of probes needed, improving diagnostic accuracy, and enabling early detection of emerging diseases, thereby enhancing healthcare delivery and patient outcomes in resource-limited settings.
Implementation Method 1
contacting the selected probes to the target sequence or a fragment thereof; wherein the target sequence or fragment thereof that hybridizes to one or more of the selected probes is sequenced
Data Source
AI summary
The present invention provides a combination of genomic and computational technologies to provide rapid, portable sample analysis for sequencing or identifying a target sequence involving generating probes for use in analyzing a sample which may comprise a target sequence.