Your browser doesn't support javascript.
loading
Automating CAR-T Transfection with Micro and Nano-Technologies.
Hu, Tianmu; Kumar, Arun Rk; Luo, Yikai; Tay, Andy.
Afiliación
  • Hu T; Engineering Science Programme, National University of Singapore, Singapore, 117575, Singapore.
  • Kumar AR; Department of Biomedical Engineering, National University of Singapore, Singapore, 117583, Singapore.
  • Luo Y; Institute for Health Innovation & Technology, National University of Singapore, Singapore, 117599, Singapore.
  • Tay A; Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117597, Singapore.
Small Methods ; : e2301300, 2023 Dec 06.
Article en En | MEDLINE | ID: mdl-38054597
ABSTRACT
Cancer poses a significant health challenge, with traditional treatments like surgery, radiotherapy, and chemotherapy often lacking in cell specificity and long-term curative potential. Chimeric antigen receptor T cell (CAR-T) therapy,utilizing genetically engineered T cells to target cancer cells, is a promising alternative. However, its high cost limits widespread application. CAR-T manufacturing process encompasses three stages cell isolation and activation, transfection, and expansion.While the first and last stages have straightforward, commercially available automation technologies, the transfection stage lags behind. Current automated transfection relies on viral vectors or bulk electroporation, which have drawbacks such as limited cargo capacity and significant cell disturbance. Conversely, micro and nano-tool methods offer higher throughput and cargo flexibility, yet their automation remains underexplored.In this perspective, the progress in micro and nano-engineering tools for CAR-T transfection followed by a discussion to automate them is described. It is anticipated that this work can inspire the community working on micro and nano transfection techniques to examine how their protocols can be automated to align with the growing interest in automating CAR-T manufacturing.
Palabras clave

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Año: 2023 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Año: 2023 Tipo del documento: Article