AI-Assisted Microfluidic Paper-Based Analytical Device with Au-Pt Nanoparticles for Multiplex, Interference-Resistant
Teng Shen1, Zidong Chen1, Bin Ran2
1School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, P. R. China.
Analytical Chemistry
|December 3, 2025
Summary
An AI-powered paper device uses gold-platinum nanoparticles for sensitive, simultaneous detection of glucose, uric acid, and creatinine in urine, improving diabetes and kidney disease diagnostics.
Area of Science:
- Biomedical Engineering
- Analytical Chemistry
- Nanotechnology
Background:
- Multiplex point-of-care detection of urinary biomarkers like glucose, creatinine, and uric acid is crucial for managing diabetes and kidney disease.
- Current methods struggle with sensitivity and signal interference in complex urine samples.
Purpose of the Study:
- To develop an artificial intelligence (AI)-assisted microfluidic paper-based analytical device (μPAD) for simultaneous electrochemical quantification of urinary glucose, creatinine, and uric acid.
- To overcome sensitivity and interference challenges in complex urine matrices.
Main Methods:
- Fabrication of a μPAD with screen-printed electrodes modified by gold-platinum (Au-Pt) bimetallic nanoparticles.
- Electrochemical detection leveraging synergistic electrocatalysis of Au-Pt nanoparticles.
- Application of multilayer perceptron (MLP) neural networks for AI-assisted error correction.
Main Results:
- Enhanced hydrogen peroxide oxidation sensitivity by 25.4-fold.
- Achieved rapid detection (<180 s) with low limits of detection for glucose (10.1 μM), uric acid (0.39 μM), and creatinine (141.7 μM).
- Reduced quantification errors from over 30% to below 6.3% using AI calibration.
Conclusions:
- The developed AI-assisted μPAD enables highly sensitive and selective multiplex detection of key urinary biomarkers.
- The platform integrates advanced nanomaterials, microfluidics, and AI for improved diagnostic accuracy.
- This technology holds significant potential for decentralized diagnostics and monitoring of diabetes and kidney injury.
