Fertility Prediction via Multi-Assay Sperm Integration
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Solution Overview
Problem
Current methods for predicting fertility in agricultural animals are unreliable, as they often rely on single assays of sperm cells before or after freezing, which do not accurately correlate with fertility or success in assisted reproductive technologies, leading to economic losses due to inefficient breeding decisions.
Innovation Solution
A system and method that utilize a combination of data from semen quality attributes, physical characteristics, and other parameters to predict fertility-related attributes, enabling informed decisions on breeding and reproductive technologies through computational models and predictive analytics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If single assay of sperm cells is used before or after freezing, then the testing process is simple and quick, but the accuracy of fertility prediction is low
Solution Approach 1:
The patent combines multiple sperm cell assays (motility, morphology, DNA fragmentation, oxidative stress markers) into a single integrated fertility prediction system. This merging of multiple measurement techniques resolves the contradiction by achieving high prediction accuracy through comprehensive data collection while maintaining a unified testing workflow that manages complexity.
Solution Approach 2:
The patent uses a composite approach by integrating multiple types of sperm cell characteristics (functional, structural, genetic, and biochemical markers) to create a comprehensive fertility assessment. This composite methodology achieves high prediction accuracy by considering multiple factors simultaneously while organizing them into a structured evaluation framework.
2Measurement precision
If multiple assays of sperm cells are performed, then the fertility prediction accuracy is improved, but the complexity and cost of testing increases
Solution Approach 1:
The patent segments the fertility assessment into distinct measurement categories (motility, morphology, DNA integrity, oxidative stress) that can be performed as separate assays but integrated into a unified prediction model. This segmentation allows for systematic evaluation of multiple parameters while organizing complexity into manageable, standardized components.
Solution Approach 2:
The patent implements feedback mechanisms by using the results from multiple assays to continuously refine and improve the fertility prediction model. The system analyzes data from various sperm cell characteristics and provides feedback that enhances prediction accuracy over time, managing complexity through iterative optimization rather than simply adding more tests.
3Productivity
If genomic testing is used to predict fertility, then the testing is rapid and can evaluate many animals, but the accuracy of fertility prediction remains low
Solution Approach 1:
The patent introduces sperm cell functional and structural characteristics as intermediary measurements that bridge the gap between rapid genomic testing and accurate fertility prediction. These intermediary assays (motility, morphology, DNA fragmentation) provide direct functional information about sperm quality that complements genomic data, thereby improving prediction accuracy while maintaining efficient throughput through standardized protocols.
Data Source
AI summary
Embodiments of the present invention provide predictions from semen qualities (7) embryo characteristics (9), qualities (11), intracellular qualities (13), extracellular qualities (14), or the like of which a computational device prediction models automated computational transformation algorithm (3) may be applied to create a prediction model transformed data (4) perhaps to generate a prediction models completed prediction output which may be used to predict parameters (6) such as fertility-related parameters, fertility of an animal, embryo success rate, or the like.