Acute Interstitial Nephritis Biomarker Panel for Non-Invasive Diagnosis
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Solution Overview
Problem
Current diagnostic methods for acute interstitial nephritis (AIN) are invasive, have low sensitivity and specificity, and rely heavily on clinical suspicion, lacking reliable non-invasive biomarkers for accurate diagnosis.
Innovation Solution
Development of a system using TNF-α, IL-9, and IL-5 as biomarkers in urine, saliva, or blood samples for diagnosing AIN, with a diagnostic index to differentiate AIN from other kidney diseases, and a point-of-care technology for rapid detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If kidney biopsy is performed to confirm AIN diagnosis, then diagnostic accuracy is improved, but patient risk of severe bleeding increases
Solution Approach 1:
The patent introduces urinary biomarkers (eosinophil cationic protein, neutrophil elastase, and kidney injury molecule-1) as intermediary substances that indirectly indicate AIN diagnosis without requiring direct tissue sampling. These biomarkers serve as mediators between the disease state and diagnostic detection, eliminating the need for invasive kidney biopsy while maintaining diagnostic accuracy.
2Ease of operation
If current diagnostic tests (urine eosinophils, urine sediment examination, imaging tests) are used, then non-invasive diagnosis is achieved, but sensitivity and specificity are poor
Solution Approach 1:
The patent combines multiple biomarkers (eosinophil cationic protein, neutrophil elastase, and kidney injury molecule-1) into a composite diagnostic panel. This composite approach leverages the complementary information from different biomarker sources to achieve high sensitivity and specificity while maintaining non-invasive urine-based testing.
3Device complexity
If clinical suspicion alone is used to diagnose AIN, then diagnostic process is simplified, but reliability of diagnosis is reduced
Solution Approach 1:
The diagnostic system enables self-service through automated detection of biomarker levels in urine samples. The system objectively measures biomarker concentrations and compares them against established thresholds, eliminating subjective clinical judgment while maintaining diagnostic simplicity. This automated approach enhances reliability without significantly increasing procedural complexity.
Data Source
AI summary
The invention provides methods and systems for detecting a biomarker related to AIN in a biological sample, and use thereof alone or as part of a diagnostic index for identifying and treating subjects at risk of AIN.


