PD Effluent Metabolomic Profiling for Peritoneal Transport Status
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Solution Overview
Problem
Conventional methods for determining peritoneal transport status in dialysis patients are labor-intensive, time-consuming, and require extra clinic visits, lacking comprehensive analysis of patient characteristics that affect peritoneal dialysis treatment effectiveness.
Innovation Solution
A method involving mass analysis of low volumes of PD effluent to generate patient information using biomarkers such as L-tryptophan, 2-methoxy-2-methylpopanoic acid, and others, allowing for efficient determination of peritoneal transport status through a computational model, enabling personalized dialysis treatment recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods are used to determine peritoneal transport status, then measurement precision can be achieved, but labor intensity and time consumption increase significantly
Solution Approach 1:
The patent replaces conventional manual laboratory analysis methods with automated mass spectrometry technology. The mass spectrometer automatically analyzes metabolite profiles in peritoneal dialysis effluent, eliminating the need for manual sample processing and reducing labor intensity while maintaining measurement precision through automated quantitative analysis of multiple biomarkers simultaneously.
Solution Approach 2:
The patent employs a multi-marker panel approach where a single mass spectrometry analysis simultaneously measures multiple biomarkers (including but not limited to L-tryptophan, 2-methoxy-2-methylpopanoic acid, 2-hydroxy-3-methyl-butyric acid, L-glutamine, L-phenylalanine, L-leucine, L-serine, L-α-glycerophosphorylcholine, cis-cinnamic acid, L-tyrosine, uric acid, L-histidine, N1-acetylspermidine, L-isoleucine, 5′-methylthioadenosine, and 4-hydroxybenzoic acid). This multi-functional analysis determines peritoneal transport status, dialysis adequacy, and membrane characteristics in a single test, dramatically improving productivity.
2Measurement precision
If conventional monitoring methods are used, then accurate patient characterization is achieved, but the number of extra clinic visits increases
Solution Approach 1:
The patent enables self-service monitoring by analyzing peritoneal dialysis effluent that is already collected during routine dialysis treatments. The automated mass spectrometry system processes these routine samples without requiring additional patient visits, allowing patients to be monitored continuously as part of their standard care routine, thereby eliminating extra clinic visit time.
3Adaptability or versatility
If comprehensive biomarker analysis is performed, then adaptability for personalized treatment is improved, but device complexity increases
Solution Approach 1:
The patent utilizes programmable parameter adjustments in the mass spectrometry system to adapt to different biomarker analyses. The instrument can be programmed to detect and quantify specific metabolites based on their mass-to-charge ratios and retention times, allowing comprehensive biomarker profiling without requiring physical modification of the device. This software-based parameter adjustment maintains adaptability while managing device complexity.
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
Facilitates frequent, accurate, and less intrusive monitoring of peritoneal transport status, reducing the need for extra clinic visits and improving patient health outcomes by optimizing dialysis treatments.
Implementation Method 1
generating patient information via mass analysis of the volume of PD effluent
Data Source
AI summary
Methods, apparatuses, and systems for determining a peritoneal transport status classification of a patient based on mass analyzing low volumes of peritoneal dialysis (PD) effluent evaluated using PD effluent fingerprints of known transport statuses to determine a peritoneal transport status classification of the patient are described. In one example, a method includes obtaining a volume of PD effluent of the dialysis patient, generating patient information via mass analysis of the volume of PD effluent, and determining patient profile information based on evaluating the patient information with a profile library, the patient profile information comprising a peritoneal transport status classification. The PD effluent fingerprints may include information of at least one biomarker including at least one of L-tryptophan, 2-methoxy-2-methylpopanoic acid, 2-hydroxy-3-methyl-butyric acid, L-glutamine, L-phenylalanine, L-leucine, L-serine, L-α-glycerophosphorylcholine, cis-cinnamic acid, L-tyrosine, uric acid, L-histidine, N1-acetylspermidine, L-isoleucine, 5′-methylthioadenosine, and 4-hydroxybenzoic acid.