Chia Hung Chen’s Biography

Chia Hung Chen, Assistant Professor, National University of Singapore

Chia-Hung Chen is an Assistant Professor in Biomedical Engineering at the National University of Singapore. His current research is focused on developing a continuous flow microfluidic device as a functional flow-cytometer for applications in systems biology, drug screening, bio-fabrication, clinical detections and precision medicine. As a principal investigator at NUS, Chia-Hung has successfully obtained external (government/industry) funding to support my research team, with ~3M USD of research expenditures over ~5 years, and his lab has delivered research outcomes. Moreover, Chia-Hung has effectively interacted with a diverse community of students and faculty to address challenges in device development and healthcare to fabricate novel products. Given his expertise in systems engineering and fluidic devices, he has collaborated with bioinformatics researchers and clinicians at the National University Hospital of Singapore (NUHS) and Massachusetts General Hospital (MGH) to develop diagnostic tools for use in translational medicine and a real-time monitoring system for individual therapeutics.

Single Cell Clinical Enzyme Analysis for Precision Medicine by Using Continuous Flow Microfluidics

Precision medicine refers to giving the right therapeutics, to the right patient, at the right time. In the context of cancer, successful implementation of precision medicine, requires treatment individualization not only taking into account patient and tumor factors, but also tumor heterogeneity and tumor evolution over time. In this study, a continuous flow microfluidic device was developed as a functional flow cytometer (Droplet FACS) to detect secreted multiplexed protease activities at single cell resolution. The individual cells from patient samples are encapsulated within water-in-oil droplets for single cell multiplexed protease assay. We modified FRET (fluorescence resonance energy transfer)-based substrates to accommodate different fluorescent pairs with distinct excitation and emission wavelengths to obtain multiple signals from droplets containing single cells. Four substrate-protease reactions in a droplet were simultaneously monitored at three distinct pairs of fluorescent excitation (UV: 400nm, B: 470nm, G: 546nm, R: 635nm) and emission (B: 520nm, G: 580nm, R: 670nm) wavelengths. To infer a quantitative profile of multiple proteolytic activities from single cells, we applied the computational method Proteolytic Activity Matrix Analysis (PrAMA). The capability to determine multiple protease activities at single cell resolution has the potential to characterize tumor progress of individual patients.