Experimental and computational approach to establish fit-for-purpose cell viability assays

Aim: Cell viability assays are critical for cell-based products. Here, we demonstrate a combined experimental and computational approach to identify fit-for-purpose cell assays that can predict changes in cell proliferation, a critical biological response in cell expansion. Materials & methods: Jurkat cells were systematically injured using heat (45 ± 1°C). Cell viability was measured at 0 h and 24 h after treatment using assays for membrane integrity, metabolic function and apoptosis. Proliferation kinetics for longer term cultures were modeled using the Gompertz distribution to establish predictive models between cell viability results and proliferation. Results & conclusion: We demonstrate an approach for ranking these assays as predictors of cell proliferation and for setting cell viability specifications when a particular proliferation response is required.In recent years, there has been a surge in the amount of cellular therapy products which have been engineered to treat patients with severe diseases. These cellular products use living cells to treat the disease, and the quality of these cell products is critical for ensuring product safety and effectiveness. Throughout the process of engineering and manufacturing these cell products, many cells can die or be in the process of dying, and the amount of dead cells in the product can impact product yield and quality. In any given cell product at any given time during the manufacturing process, cells are exposed to stresses, and these stresses can injure the cells through several mechanisms, leading to a range of cell death events that can follow different timelines. There are many existing assays which evaluate the health of the cells, known as cell viability assays, and these assays can be based on many different cell features that indicate a cell has been injured (i.e., cell membrane permeability, changes in cell metabolism, molecular markers for cell death). These cell viability assays provide different insights into the state of cell health/injury based on what cell features are being evaluated and the timing at which the viability measurements are taken, and some viability assays may be more appropriate than others for specific applications. Therefore, a method is needed to appropriately select cell viability assays that are designed to evaluate injuries to cells that occur in specific bioprocess. In this series of studies, we used a range of analytical methods to study the number of living and dead cells in a series of cell populations that we treated to induce damage to the cells, reducing their ability to grow. We then used mathematical models to determine the relationship between cell viability measurements and cell growth over time, and used the results to determine the sensitivity of the viability assays to changes in cell growth. We used a specific cell line in this example, but this technique can be applied to any cell line or cell sample population and different types of injuries can be applied to the cells. This approach can be used by manufacturers of cell-based products and therapies to identify cell viability assays that are meaningful for monitoring the production of cells and characterizing product quality.