FMSG: Bio: Disposable Microfluidics Device with Integrated RF Electric Fields and Machine Learning for Biomanufacturing of mRNA-based CAR T-cells

Old Dominion University Research Foundation, Norfolk VA

Investigators

Abstract

T-cells are an important type of white blood cell that play a vital role in the adaptive immune response. Cell-based therapies, especially genetically modified T-cells from the patients themselves, can be effective for a range of diseases including cancers. These modified T-cells are called Chimeric Antigen Receptor T-cells (CAR T-cells) and are engineered in a safe manufacturing facility to express CAR molecules on T-cell surfaces. Once CAR T-cells are infused into patients, the selective conjugation of tumor cell protein and CAR T-cell protein triggers T-cell mediated cytotoxicity that kills the tumor cells. However, there are significant barriers to their wider adoption as therapies. These include: (1) safety concerns related to CAR T-cells engineered by viral gene transfer, which is the current method for CAR gene transfer into T-cells. (2) the high expense of CAR T-cell therapy. A large portion of their cost is associated with producing the CAR T-cells in centralized manufacturing facilities. To address these critical issues, this Future Manufacturing Seed Grant (FMSG) research will investigate novel, low-cost mRNA based (viral-free), distributed CAR T-cell manufacturing strategies. The objective of this research is to develop good manufacturing practice (GMP) enabled low-cost mRNA-based CAR T-cell manufacturing technologies. This project will investigate how bolus injected external cellular mRNA molecules are translated into protein molecules in a time dependent manner. Additionally, this project will study how the initial cellular protein level from bolus injected external mRNA modulates the half-life of cellular protein expression. This will be accomplished via the following aims: (1) Theoretically and experimentally study the protein expression and half-life of electroporated T-cells with mRNA molecules, and (2) Investigate the feasibility of utilizing Machine Learning algorithms to build good manufacturing practice (GMP) protocols, including biomanufacturing platforms with built-in quality control and automation. The broader impact activities will focus on the development of a workforce to meet the needs of the biomanufacturing industry. Instructional modules on theory, current practices, and trends in biomanufacturing will be incorporated into the undergraduate and graduate engineering curricula at Old Dominion University and North Dakota State University. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.