Abstract

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.

Highlights

  • Introduction mesenchymal stromal cells (MSCs) are a cell type with a wide range of potential therapeutic applications

  • The issue is further compounded in specific patient groups, such as the elderly or those with diabetes, owing to an impaired in vivo niche for BM-MSCs resulting in fewer isolatable BM-MSCs per milliliter bone marrow aspirate and with potential qualitative impairment compared with healthy individuals [13]

  • Simple factors like draw volume and syringe volume are reported to influence initial BM-MSC yield per milliliter, with greater draw volumes correlating with lower BMMSC yield per draw, as the aspirate becomes contaminated with peripheral blood [15]

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Summary

Introduction

Introduction mesenchymal stromal cells (MSCs) are a cell type with a wide range of potential therapeutic applications. There is some literature evidence that allogeneic MSCs may elicit immune responses [6,7], and that rejection of MSCs after differentiation may compromise clinical effectiveness [8] These risks may be reduced by expansion of the patient’s own cells to create autologous ‘manufactured’ hBM-MSCs. These risks may be reduced by expansion of the patient’s own cells to create autologous ‘manufactured’ hBM-MSCs Such an approach comes with its own challenges of variable starting material and potentially more complex logistics of patient-specific processes and delivery timings. The results of multiple clinical trials show that there have been successes and failures with both approaches; the reasons for inconsistency likely lie in the complexity of heterogenous non-comparable cell populations between trials and inconsistent effects of processing methodologies including variable reagents and preservation methodologies [9] Both allogeneic and autologous strategies are being actively pursued for near-term clinical application. Alongside biological factors like disease state or patient age, process factors including shipping conditions and duration can result in cell losses post-isolation [16]

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