Biology subjects

Cheung, K.-W.

Publications and source records attributed to Cheung, K.-W..

3 recordsLinked to original sources

bioRxiv2025

Use of cellular FAD autofluorescence as a label-free cellular attribute for the production of chimeric antigen receptor-T cells

Chimeric antigen receptor T (CAR-T) cell therapy has become an attractive approach for treating hematological malignancies. However, the accessibility of this therapy is limited by factors such as complex manufacturing process, limited capacity of manufacturing facilities and the requirement of highly skilled workforce for the manual steps of CAR-T cell production. To minimize the manual processes, CAR-T cell manufacturing field is shifting towards closed and automated systems, including analytical tools that offer intermittent monitoring of cells in production. Therefore, label-free technologies for closely monitoring CAR-T cells in closed systems are needed. Here, we evaluate the use of a flow cytometer equipped with a 405nm violet laser for investigating the NADH and FAD autofluorescence in T cells. Our results revealed the increase of NADH and FAD autofluorescence were significantly correlated with the upregulation of T cell activation marker, CD25 and the increase of extracellular lactate in spent media in the first three days after T cell activation. We demonstrate the potential use of FAD for determining the endpoint of CAR-T cell manufacture by establishing a relationship between the rate of change in the mean fluorescence intensity (MFI) of FAD in CAR-T cells and the rate of change in T cell proliferation using a G-Rex bioreactor. Collectively, these findings suggest that autofluorescence, particularly FAD autofluorescence, can serve as a label-free biomarker (cellular attribute) for monitoring T cell activation and expansion during CAR-T cell production. The use of 405nm visible light to substitute the genotoxic UV wavelengths for assessing the NADH and FAD autofluorescence, paves the way to incorporate autofluorescence measurements into closed and automated systems for in-process monitoring of CAR-T cell manufacturing.

immunology↗

bioRxiv2023

High-density microbioreactor process designed for automated point-of-care manufacturing of CAR T cells

While adoptive cell therapies have revolutionized cancer immunotherapy, current autologous chimeric antigen receptor (CAR) T cell manufacturing face challenges in scaling to meet patient demands. CAR T cell production still largely rely on fed-batch, manual, open processes that lack environmental monitoring and control, whereas most perfusion-based, automated, closed-system bioreactors currently suffer from large footprints and working volumes, thus hindering process development and scaling-out. Here, we present a means of conducting anti-CD19 CAR T cell culture-on-a-chip. We show that T cells can be activated, transduced, and expanded to densities exceeding 150 million cells/mL in a two-milliliter perfusion-capable microfluidic bioreactor, thus enabling the production of CAR T cells at clinical dose levels in a small footprint. Key functional attributes such as exhaustion phenotype and cytolytic function were comparable to T cells generated in a gas-permeable well. The process intensification and online analytics offered by the microbioreactor could facilitate high-throughput process optimization studies, as well as enable efficient scale-out of cell therapy manufacturing, while providing insights into the growth and metabolic state of the CAR T cells during ex vivo culture.

bioengineering↗

bioRxiv2019

ClassifyMe: a field-scouting software for the identification of wildlife in camera trap images.

We present ClassifyMe a software tool for the automated identification of animal species from camera trap images. ClassifyMe is intended to be used by ecologists both in the field and in the office. Users can download a pre-trained model specific to their location of interest and then upload the images from a camera trap to a laptop or workstation. ClassifyMe will identify animals and other objects (e.g. vehicles) in images, provide a report file with the most likely species detections and automatically sort the images into sub-folders corresponding to these species categories. False Triggers (no visible object present) will also be filtered and sorted. Importantly, the ClassifyMe software operates on the users local machine (own laptop or workstation) not via internet connection. This allows users access to state-of-the-art camera trap computer vision software in situ, rather than only in the office. The software also incurs minimal cost on the end-user as there is no need for expensive data uploads to cloud services. Furthermore, processing the images locally on the users end-device allows them data control and resolves privacy issues surrounding transfer and third-party access to users datasets.

ecology↗