T cell transfer immunotherapy is a highly effective cancer treatment in which the immune system’s inherent ability to fight cancer is amplified by increasing the amount of T cells that are deemed most active within a patient. T cells are a lymphocyte produced as an immune response to cancerous cells. Despite this advanced form of biological therapy, current T cell expansion methods are inefficient, resulting in high manufacturing costs, which brings question to the efficacy of T cell therapies. To address this issue, the recent development of a centrifugal bioreactor aims to rapidly expand T cells for cancer immunotherapy treatments at higher cell densities and in a shorter amount of time compared to current systems on the market. We hypothesize that by producing a mathematical model of a proof-of-concept T cell line to determine substrate consumption and metabolite production over time, we will be able to optimize growth of the cell line in the bioreactor. A series of three studies were performed to produce the growth model: (1) measuring yield coefficients of lactate, ammonium ion, and glucose, (2) determining the Monod constant and maximum specific growth rate, and (3) finding critical metabolite concentrations. To measure yield coefficients, T cells were grown in a 6-well plate at 1 x 105 cells/mL in 4 mL of medium with 100 uL samples taken and frozen each day over a 5-day period. At the end of the study, samples are thawed and used with lactate and ammonium assay kits for microplate reading to determine metabolite levels over time. To determine the Monod constant and maximum specific growth rate, T cells were grown in 12-well plates at pre-calculated varying glucose concentrations in 4 mL of medium in triplicates. Cells were counted for a minimum of six days to determine expansion over time to develop a linearized growth plot. To find critical metabolite concentrations, ammonium and lactate were added to glucose-free T cell medium at four different concentrations in triplicates utilizing a 12-well plate with a seeding density of 1 x 105 cells/mL in 4 mL of medium. The T cells then remained undisturbed in culture and were counted on day three. Once all parameters are determined, we can apply them to the growth model to determine levels of glucose, lactate, and ammonium as the T cells grow to high densities in the bioreactor and, as a result, optimize the manufacturing process for cancer immunotherapy treatments.
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Optimizing Cytotoxic T Cell Growth in a Centrifugal Bioreactor through Kinetic Growth Models
Cancer is the second leading cause of death globally and remains a significant issue in medicine. Immunotherapy treatments such as Chimeric Antigen Receptor T cell (CAR-T) therapies are becoming a more promising option because of their effectiveness in killing cancer cells without harming healthy tissue in the body. CAR-T therapies, however, are inaccessible to many due to the high cost—a result of inefficient cell expansion and manufacturing methods. To address this issue, we have developed the Centrifugal Fluidized Expansion (CentriFLEX) bioreactor that balances centrifugal and fluid forces, allowing the system to operate in perfusion and maintain a high cell density. Shown in past applications for similar cell types, the CentriFLEX can expand cultures up to 2.1 billion cells in an 11.4 mL chamber over the course of one week. Recently, we have used this system to expand bovine T cells as part of a collaboration with the College of Veterinary Medicine at Washington State University. Through the project, we conducted kinetic studies to model substrate consumption and metabolite production of bovine T cells and have enhanced the bioreactor design by making it more compact to fit entirely within a biosafety cabinet— mitigating contamination concerns. Current efforts have been spent determining the remaining parameters for the kinetic models and using such models to understand how the cells grow over time and in the space of a high-population density chamber. In this presentation, we will share how we use growth models that are based on a series of kinetic studies to predict substrate and metabolite levels over time in the bioreactor, allowing us to alter feed and dosing rates of medium and nutrients to maintain cell growth at the maximum specific growth rate.
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- Award ID(s):
- 1645249
- PAR ID:
- 10310313
- Date Published:
- Journal Name:
- Annual meeting American Institute of Chemical Engineers
- ISSN:
- 0196-7282
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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