Integrated Droplet Microfluidic Platform for Single-Spheroid Photothermal Nanotherapy and Morphology-Driven Response Prediction

Abstract

Photothermal therapy (PTT) is a promising cancer treatment modality, but its evaluation remains limited by the lack of physiologically relevant and quantitatively controlled in vitro platforms. Here, we present a droplet-based microfluidic platform that enables single-spheroid formation, programmable nanoparticle delivery, and in situ laser irradiation with real-time thermal monitoring. The platform enables temperature multiplexing within a single experiment, allowing construction of single-spheroid dose–response relationships and the definition of a temperature-based inhibitory metric (IT50). This provides a direct and physically meaningful quantification of photothermal efficacy. In parallel, a label-free, spheroid morphology-based machine learning approach predicts treatment response across cell types, nanoparticle incubation conditions, and therapeutic regimes while preserving intrinsic single-spheroid variability. Despite a limited dataset size and biological heterogeneity, the system achieves robust and reproducible predictive performance. Overall, this work establishes a scalable and versatile microfluidic framework for quantitative photothermal nanotherapy screening, integrating controlled thermal dosing, 3D tumor models, and morphological data-driven analysis within a single-spheroid platform.