Biological Sample Analysis with Adaptive Microorganism Identification
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Solution Overview
Problem
Existing methods for identifying microorganisms in biological samples, such as those described in WO2021112673, are limited by speed and resource efficiency, and there is a need to determine microorganism characteristics with higher throughput and confidence.
Innovation Solution
A method utilizing a supervisory system to analyze biological samples, determining the necessity of subsequent identification analysis and microorganism characteristics based on initial analysis data, allowing for efficient resource allocation and faster identification through multiple analysis arrangements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all samples are analyzed through multiple identification analysis arrangements to ensure accurate microorganism identification, then the reliability of identification results is improved, but the time required and resources consumed increase significantly
Solution Approach 1:
The system performs preliminary analysis using a first analysis arrangement to obtain initial analysis data before committing to full identification analysis. This preliminary step allows the system to identify samples that clearly do or do not contain microorganisms, avoiding unnecessary subsequent analysis steps for samples that will yield negative or inconclusive results, thereby reducing overall analysis time while maintaining reliability for positive identifications
Solution Approach 2:
The supervisory system uses feedback from the first analysis arrangement to dynamically determine which samples require subsequent identification analysis. Based on the initial analysis results, the system intelligently routes only those samples with positive or inconclusive results to the second analysis arrangement, creating a feedback-driven workflow that optimizes both time and reliability
2Loss of information
If all samples undergo complete identification analysis to determine microorganism characteristics, then the completeness of data is improved, but the resource efficiency deteriorates
Solution Approach 1:
The system extracts and processes only the essential information from the first analysis arrangement to determine whether subsequent analysis is needed. By taking out only the critical decision-making data points (positive, negative, or inconclusive results) and using them to filter the sample population, the system avoids performing complete identification analysis on samples that don't require it, thus improving resource efficiency while maintaining data completeness for relevant samples
Solution Approach 2:
The system applies partial analysis (first analysis arrangement) to all samples and then applies complete analysis (second analysis arrangement) only to the subset of samples that require it. This partial action approach ensures data completeness for the necessary subset while avoiding excessive resource consumption that would result from applying complete analysis to all samples
3Productivity
If a supervisory system is introduced to manage multiple analysis arrangements and determine subsequent analysis requirements, then the productivity of sample analysis is improved, but the device complexity increases
Solution Approach 1:
The supervisory system serves multiple functions: it manages the first analysis arrangement, processes analysis data, determines which samples require subsequent analysis, manages the second analysis arrangement, and generates final results. By consolidating these multiple functions into a single supervisory system rather than having separate control systems for each function, the system improves productivity while limiting the increase in overall complexity through functional integration
4Measurement precision
If subsequent identification analysis is performed on all samples from the first analysis arrangement, then the accuracy of microorganism identification is improved, but the loss of time and resources increases
Solution Approach 1:
The system segments the sample population into different groups based on the results of the first analysis arrangement: samples with negative results, samples with positive results, and samples with inconclusive results. By segmenting the workflow in this way, the system applies subsequent identification analysis only to the relevant segments (positive and inconclusive samples), thereby maintaining identification precision for samples that need it while improving overall analysis throughput by excluding samples that don't require further analysis
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
The method provides faster and more resource-efficient identification of microorganisms, enabling higher throughput and confident determination of microorganism characteristics using a supervisory system to optimize sample analysis.
Implementation Method 1
by an electronic processor of the supervisory system, using the first set of analysis data, for each sample in the set of biological samples: a) identifying no, one, or multiple microorganisms in the sample and generating microorganism data based on the identifying; and at least one of: b1) based on the microorganism data, determining whether a subsequent identification analysis is required
Data Source
Figure 1A~1C
Figure 2
Figure 3A~3C
AI summary
Method of analysing a set of biological samples for identification of microorganisms potentially present in the samples, the method comprising steps of obtaining a first set of analysis data, by an electronic processor of the supervisory system, using the first set of analysis data, for each sample in the set of biological samples, determining if a subsequent analysis is required, and generating a first subset of samples with samples for which it is determined that subsequent analysis is required. The method further comprises analysing the samples in the first subset of biological samples in a second analysis arrangement. The disclosure also contemplates determining, for each sample, whether a microorganism characteristic is to be determined.