PHENOS · PHENOtyping targeted single-cell via integrated digital microfluidics and optoelectronic tweezerS

Cellular populations are rich in diversity, and understanding this heterogeneity at the single-cell level is crucial in oncology, where specific subpopulations can drive tumour progression, metastasis, and therapy resistance. PHENOS (“PHENOtyping targeted single-cell via integrated digital microfluidics and optoelectronic tweezerS”) addresses this challenge by introducing the first hybrid platform for targeted single-cell analysis and manipulation. The system combines digital microfluidics (DMF) for precise liquid handling, aptamer-mediated cell surface functionalization for molecular targeting, optoelectronic tweezers (OET) for non-invasive manipulation, and advanced data analysis algorithms for high-resolution phenotypic profiling. The project is structured in four phases: (1) design and validation of DMF and OET devices, (2) integration into a hybrid opto-microfluidic platform, (3) targeted cell functionalization and longitudinal phenotyping through time-lapse imaging, and (4) development of machine learning and deep learning algorithms for classification and phenotypic stratification. Through a comprehensive and synergistic training programme bridging engineering, biology, chemistry, and computational science, PHENOS will: (1) establish a dynamic, high-precision workflow for single-cell measurement and sorting, and (2) enhance OET sensitivity and specificity, achieving ≥95% classification accuracy, in independent experiments, with an expected 20% gain from aptamer targeting. By overcoming current limitations, PHENOS will establish a novel framework for decoding cellular heterogeneity in cancer with a decision-making process, guiding personalised treatments and improving patient outcomes, while providing me a unique multidisciplinary environment to build scientific independence and long-term leadership.