Optimization of Manufacturing Process for Mesenchymal Stromal Cells
Waseem, Sidrah 1; Bhatt, Shashank 2; Audet, Julie 1; Viswanathan, Sowmya 1, 2
1. Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, CA; 2. Arthritis Program, Krembil Research Institute, University Health Network, Toronto, ON, CA
Background: Human mesenchymal stromal cells (MSCs) have attracted immense amount of research interest because of their ability to secrete a multitude of cytokines and growth factors, and for their therapeutic potential in inflammatory and autoimmune diseases. The anti-inflammatory and immunomodulatory properties of MSCs are often compromised in commercial-scale expansion of MSCs. Optimized manufacturing methods that can produce scaleable and functional MSCs are therefore needed.
Methods: A design of experiments (DOE) approach will be used to develop a statistical model that will refine the manufacturing process of MSCs to simultaneously obtain improved cell yield and therapeutic efficacy of expanded MSCs, while maintaining low costs. The design domain is not fixed and will evolve during the progress of optimization, where initially, seven factors, e.g. donor variability, medium composition, seeding density, 2D vs. 3D format etc., will be used as input variables and ten responses will be used as outputs. The input parameters were selected based on failure-risk analyses. The outputs will include the gene expression of a subset of the panel of secreted factors, suggested by The International Society for Cellular Therapy (ISCT), for measuring MSC potency, including interleukins (IL-10), indoleamine 2,3-dioxygenase (IDO), tumor necrosis factor-inducible gene 6 protein (TSG-6) etc. These outputs were selected on the basis of correlation between their presence and clinical outcomes in an MSC OA trial by our lab (Chahal et al., in preparation). The statistical model will predict a series of optimal bioprocess parameter combinations which will be validated independently in lab experiments. Independent validation using protein expression to generate scalable quantities of MSCs tested in vitro assays will also be performed. In vivo validation in relevant inflammatory disease models will be undertaken by others in the lab.
Results and Conclusions: The statistical model will identify bioprocess parameter combination(s) that predict the best experimental outcomes and the results from the lab experiments will corroborate the model. This project will address the recent MSC equivocal clinical trial results, and help design next generation engineered and optimized MSC products for safe and effective clinical use in many autoimmune and inflammatory diseases.
Keywords: mesenchymal stromal cells, statistical model, optimize, bioprocess parameters, cellular therapy.