Automated Microfluidic Platform for High-Throughput Biosensor Development

Abstract

Biorecognition elements immobilized into nanopores have transformed point-of-care (POC) diagnostics by converting molecular interactions into electrical and fluorescent signals.This study introduces Bio-Sensei, a high-throughput screening (HTS) microfluidic platform based on nanopore biosensing. Integrating a robotic sampler, electrochemical, and fluorescence setup, Bio-Sensei operates as an Internet of Things (IoT) platform with integrated data analysis. The platform's utility is demonstrated on functionalized with an amino terminal Cu(II)- and Ni(II)-binding (ATCUN) peptide ion track-etched membrane. Automated testing achieves a significantly higher F-stat value than the critical threshold, while unsupervised clustering reveals optimal nanopores pore size. The biosensor demonstrates remarkable stability, selectivity, and sensitivity with detection limits of 10−6 using fluorescence and 10−15 M using cyclic voltammetry measurements. Combining these methods enhances machine learning models for Cu2+ concentration prediction, achieving receiver operating characteristic area under the curve values exceeding 95%.