Optimal Primer Set Selection via Amplification Data Similarity
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Solution Overview
Problem
The selection of optimal primer sets for high-level multiplex assays is intractable due to exponential growth in possible combinations, leading to inefficient primer design and resource-intensive methods that require multiple rounds of redesign and consideration of primer-primer competition and target abundance.
Innovation Solution
A computer-implemented method that uses amplification data from preparatory assays to determine optimal primer sets by calculating similarity metrics and viability scores, allowing for the selection of primer sets based on data-driven analysis rather than bioinformatic predictions, thereby reducing the need for multiple redesigns and optimizing primer concentration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If in-silico methods relying on bioinformatic data are used for primer selection, then the design process is simplified, but the classification performance is not optimized and multiple rounds of redesign are required
Solution Approach 1:
The patent performs preliminary experimental testing of primer sets in single-plex assays before final multiplex assembly. By pre-evaluating primer performance, compatibility, and amplification efficiency in controlled single-plex conditions, the method identifies optimal primer combinations before committing to full multiplex assays, reducing iterative redesign cycles
Solution Approach 2:
The patent implements feedback loops where experimental results from preparatory single-plex assays inform subsequent multiplex design decisions. Amplification data, specificity metrics, and efficiency measurements feed back into the selection process, allowing continuous optimization of primer sets based on actual experimental performance rather than theoretical predictions
2Reliability
If comprehensive consideration of target abundance and primer-primer competition is made, then assay accuracy improves, but time and resource consumption increase
Solution Approach 1:
The patent segments the complex multiplex primer design problem into manageable single-plex preparatory assays. By evaluating primer sets individually in single-plex conditions first, then progressively combining them, the method breaks down the intractable exponential search space into linear sequential steps, reducing design time while maintaining accuracy through systematic evaluation
Solution Approach 2:
The patent performs preliminary evaluation of target abundance ratios and primer compatibility in single-plex assays before final multiplex combination. This pre-assessment of competitive interactions and relative abundances allows optimization of primer concentrations and selection without requiring exhaustive testing of all possible multiplex combinations
3Manufacturing precision
If the number of possible multiplex assay combinations is evaluated exhaustively, then the optimal primer sets are identified, but the computational and experimental burden becomes intractable
Solution Approach 1:
The patent divides the exponential search space of multiplex combinations into linear sequences of single-plex evaluations. By assessing primer sets individually and in small progressive combinations rather than evaluating all possible multiplexes simultaneously, the method reduces computational and experimental complexity from exponential to linear scale
Solution Approach 2:
The patent evaluates a selective subset of primer combinations based on preliminary single-plex performance data rather than exhaustively testing all possible combinations. By using preliminary data to filter and prioritize candidate primer sets, the method achieves sufficient optimization without the intractable burden of complete enumeration
Data Source
AI summary
Disclosed herein are methods and systems for determining optimal primer sets for a multiplex assay, each of the optimal primer sets intended to amplify one or more targets. The method comprises obtaining amplification data from a plurality of preparatory assays. The amplification data describes at least the amplification of a first target of the one or more targets by a first primer set in a first preparatory assay, the amplification of the first target amplified by a second primer set in a second preparatory assay, the amplification of a second target of the one or more targets by the first primer set in a third preparatory assay, and the amplification of the second target by the second primer set in a fourth preparatory assay. The method further comprises determining a plurality of similarity metrics, each similarity metric being indicative of a degree of similarity between the amplification data produced by one of the plurality of preparatory assays compared to another one of the preparatory assays. The method further comprises determining, based on the plurality of similarity metrics, the optimal primer sets for the multiplex assay.