# Electrochemical Biosensor for Rapid Detection of Acute Rejection in Kidney Transplants

## TL;DR

A new electrochemical biosensor can quickly detect kidney transplant rejection using urine, offering a non-invasive alternative to biopsies.

## Contribution

A rapid, label-free biosensor for detecting AR biomarkers in urine with high sensitivity and accuracy.

## Key findings

- The biosensor achieves single-digit pg/mL sensitivity for CXCL9 and CXCL10 in 15 minutes.
- A machine learning classifier using biosensor data reached 83% accuracy in AR detection.
- Combining biosensor data with clinical features improved classification accuracy to 98%.

## Abstract

Kidney transplant recipients face a high risk of acute rejection (AR), where the immune system attacks the transplanted organ. Current diagnostics rely on invasive biopsies with procedural risks, costs, and limited temporal resolution. While urinary chemokines CXCL9 and CXCL10 are promising non‐invasive AR biomarkers, clinical adoption is limited by labor‐intensive detection and lack of point‐of‐care (POC) solutions. A rapid, label‐free electrochemical biosensing platform for simultaneous quantification of CXCL9 and CXCL10 chemokines from 5 µL of unprocessed urine in 15 min, which for ELISA and biopsy is between 24–72 hrs, is presented. The system uses screen‐printed carbon electrodes modified with a Ti3C2Tx MXene‐crosslinked bovine serum albumin hydrogel, offering high conductivity, nano‐porosity, anti‐fouling properties, and signal stability for up to 30 days. The platform enables single‐digit pg/mL‐level sensitivity, meeting clinical thresholds. In a prospective clinical study, biosensor‐measured chemokine data trained a bootstrapped logistic regression classifier, achieving 83% AR classification accuracy. When combined with additional clinical and histopathological features, accuracy increased to 98%. This work integrates advanced materials, biosensor engineering, and machine learning to deliver a scalable, cost‐effective POC solution for real‐time, non‐invasive AR monitoring. The platform will help reduce biopsy dependence, enable earlier intervention, and ultimately improve long‐term transplant outcomes.

A low‐cost, rapid electrochemical immunosensor coated with a novel antifouling nanocomposite enables single‐step, dual‐biomarker profiling directly from unprocessed urine. Application in a clinical study shows accurate discrimination of acute rejection in kidney transplants from other acute kidney injuries via machine learning. This offers a potential alternative to invasive biopsies and complex multi‐step assays.