Multiplex PCR and Pooled Susceptibility Testing for Polymicrobial Infections
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Solution Overview
Problem
Current methods for diagnosing and treating polymicrobial infections, such as urinary tract infections, are limited by their inability to accurately detect and identify multiple bacterial species and account for interactions between them, leading to inadequate antibiotic selection and potential treatment failures.
Innovation Solution
The use of multiplex PCR-based methods for detecting bacteria and pooled antibiotic susceptibility testing (P-AST) to identify polymicrobial infections and determine the effectiveness of antibiotics, considering interactions between cohabiting bacterial species, along with genetic resistance marker testing to guide therapeutic solutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional culture-based methods are used to diagnose polymicrobial infections, then the diagnostic process is simple and inexpensive, but the ability to accurately detect and identify multiple bacterial species is insufficient
Solution Approach 1:
The patent combines multiple detection methods (culture-based detection, PCR-based detection, and mass spectrometry) into a single integrated diagnostic system. This merging allows the system to maintain the simplicity and cost-effectiveness of traditional methods while incorporating advanced techniques to accurately detect and identify multiple bacterial species in polymicrobial infections.
Solution Approach 2:
The diagnostic system is designed to perform multiple functions: it can detect the presence of bacteria, identify specific bacterial species, determine antibiotic susceptibility, and analyze complex polymicrobial communities. This multi-functionality allows a single system to replace multiple separate diagnostic tools, improving detection accuracy without proportionally increasing complexity.
2Reliability
If traditional single-pathogen testing methods are used, then the testing process is straightforward, but the ability to account for interactions between cohabiting bacterial species is lost
Solution Approach 1:
The patent merges separate susceptibility testing for different bacterial species into a single pooled susceptibility test. By combining multiple bacterial species in one test environment, the system can observe how cohabiting species interact and affect antibiotic susceptibility, providing more reliable predictions of treatment outcomes while simplifying the overall testing process.
Solution Approach 2:
The patent uses pooled cultures as an intermediary medium to study interactions between bacterial species. Instead of testing each species separately, the pooled culture allows bacterial species to coexist and interact under controlled conditions, revealing how these interactions influence antibiotic susceptibility and enabling more accurate treatment predictions.
3Measurement precision
If comprehensive genetic resistance marker testing is performed, then therapeutic guidance is highly accurate, but the time and resources required for testing increase
Solution Approach 1:
The patent performs preliminary genetic resistance marker testing on pooled bacterial communities before final therapeutic selection. By conducting initial screening tests that identify common resistance patterns, the system can narrow down potential therapeutic options early in the process, reducing the time required for comprehensive testing while maintaining high accuracy in therapeutic guidance.
Solution Approach 2:
The patent uses genetic sequencing to create digital copies of bacterial resistance profiles. These digital copies can be analyzed computationally to predict antibiotic susceptibility without requiring extensive physical testing. This approach maintains high accuracy in therapeutic selection while significantly reducing the time and resources needed for comprehensive resistance testing.
Data Source
AI summary
Methods for identifying and providing information about inhibiting growth of polymicrobial infections, including but not limited to providing statistics or information about the likelihood of success in inhibiting growth of a polymicrobial infection with particular compositions or therapeutic solutions. The methods herein feature detection and identification of organisms of the polymicrobial sample (e.g., polymicrobial infection), phenotypic pooled sensitivity tests for determining the susceptibility or resistance of the polymicrobial sample (e.g., polymicrobial infection) in the sample to an antibiotic or other therapeutic agent, and identification of resistance genes, e.g., genetic markers that may indicate resistance to a particular treatment. Together, the data can be applied against databases of antibiotic/therapeutic susceptibility or resistance for particular known polymicrobial samples (e.g., polymicrobial infections) in order to provide information related to the likelihood of success of one or more therapeutic solutions for the polymicrobial sample (e.g., polymicrobial infection).