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Updated: Jan 23, 2026

A 96 Well Microtiter Plate-based Method for Monitoring Formation and Antifungal Susceptibility Testing of Candida albicans Biofilms

A 96 Well Microtiter Plate-based Method for Monitoring Formation and Antifungal Susceptibility Testing of Candida albicans Biofilms

Published on: October 21, 2010

深層学習を活用したスリップチップによる迅速単一細胞表現型抗真菌薬感受性試験

Yan'an Ren¹, Juanxiu Qin², Min Li^2,3,4

¹School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China.

Analytical chemistry

|January 22, 2026

Abstract:

Fungal infections cause over 1.5 million deaths annually, yet current antifungal susceptibility testing (AFST) methods require 24-48 h, delaying critical treatment decisions. Here, we present a rapid, label-free, single-cell AFST (sc-AFST) platform that integrates a SlipChip microfluidic device with deep learning-based image analysis to determine minimal inhibitory concentrations (MICs) within 4 h. The SlipChip partitions fungal cells into picoliter droplets for exposure to antifungal gradients, while a ResNet-34 classifier and U-Net segmentation model automatically identify and quantify cellular growth directly from bright-field images. We validated the platform using Candida albicans and clinical isolates, achieving >98.8% sensitivity in cell detection and >93% segmentation accuracy. The sc-AFST results showed 100% categorical agreement with gold standard broth microdilution test across all 10 clinical isolates, despite one minor MIC discrepancy. This approach enables high-resolution single-cell growth analysis and population-level drug response profiling, offering a scalable, rapid, and clinically actionable tool for AFST.

キーワード:

抗真菌薬感受性試験単一細胞マイクロ流体工学深層学習迅速診断

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