A Monte Carlo framework for managing biological variability in manufacture of autologous cell therapy from mesenchymal stromal cells therapies.

Manufacturing processes for autologous cell therapy need to reproducibly generate in specification (quality and quantity) clinical product. However, patient variability prevents the level of control of cell input material that could be achieved in a cell line or allogeneic-based process. We have applied literature data on bone marrow-derived mesenchymal stromal cells variability to estimate probability distributions for stem cell yields given underlying truncated normal distributions in total nucleated cell concentration, stem cell percentage and plausible aspirate volumes. Monte Carlo simulation identified potential variability in harvested stem cell number in excess of an order of magnitude. The source material variability was used to identify the proportion of donor manufacturing runs that would achieve a target yield specification of 2E7 cells in a fixed time window with given proliferative rates and different aspirate volumes. A rapid, screening, development approach was undertaken to assess culture materials and process parameters (T-flask surface, medium, feed schedule) to specify a protocol with identified proliferative rate and a consequent model-based target aspirate volume. Finally, four engineering runs of the candidate process were conducted and a range of relevant quality parameters measured including expression of markers CD105, CD73, CD44, CD45, CD34, CD11b, CD19, HLA-DR, CD146 (melanoma cell adhesion molecule), CD106 (vascular cell adhesion molecule) and SSEA-4, specific metabolic activity and vascular endothelial growth factor secretion, and osteogenic differentiation potential. Our approach of using estimated distributions from publicly available information provides a route for data-poor earl- stage developers to plan manufacture with defined risk based on rational assumptions; furthermore, the models produced by such assumptions can be used to evaluate candidate processes, and can be incrementally improved with accumulating distribution understanding or subdivision by new process variables.

Mesenchymal stem cell isolation from human umbilical cord tissue: understanding and minimizing variability in cell yield for process optimization.

Human tissue banks are a potential source of cellular material for the nascent cell-based therapy industry; umbilical cord (UC) tissue is increasingly privately banked in such facilities as a source of mesenchymal stem cells for future therapeutic use. However, early handling of UC tissue is relatively uncontrolled due to the clinical demands of the birth environment and subsequent transport logistics. It is therefore necessary to develop extraction methods that are robust to real-world operating conditions, rather than idealized operation. Cell yield, growth, and differentiation potential of UC tissue extracted cells was analyzed from tissue processed by explant and enzymatic digestion. Variability of cell yield extracted with the digestion method was significantly greater than with the explant method. This was primarily due to location within the cord tissue (higher yield from placental end) and time delay before tissue processing (substantially reduced yield with time). In contrast, extraction of cells by explant culture was more robust to these processing variables. All cells isolated showed comparable proliferative and differentiation functionality. In conclusion, given the challenge of tightly controlled operating conditions associated with isolation and shipping of UC tissue to banking facilities, explant extraction of cells offers a more robust and lower-variability extraction method than enzymatic digestion.