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

Role of TRAIL-mediated tumor cell apoptosis.

<p>(A) DR5 expression on AB1-HA tumor cells <i>in vitro</i>. (B) Tumor growth curves in CY-treated and untreated TRAIL-deficient mice, compared with immunocompetent mice and nude mice. Data shown are mean±SEM (<i>n</i> = 10) from two combined experiments. Tumor cells were inoculated at day 0 and treated with CY at day 10. ** P<0.005 when CY in BALB/c is compared with CY in TRAIL-deficient mice.</p

Rescue of CY anti-tumor efficacy in nude mice by anti-DR5 antibodies.

<p>Tumor-bearing athymic nude mice (inoculated at day 0) were treated with CY or with PBS at day 9 (a) or day 7 (b) after tumor cell inoculation and were treated with anti-DR5 antibody (clone MD5-1) or PBS at day 8, 12 and 16 after tumor cell inoculation. Data shown are mean±SEM (<i>n</i> = 5/group for each experiment). * P<0.05 when CY is compared with CY + anti-DR5. The effect of anti-TRAIL Ab without CY is shown in (b). Two mice were disqualified from the graph as they were found dead early in the experiment.</p

Role of CD8 T cells and type-I IFN in CY-driven anti-tumor efficacy.

<p>(A) Anti-tumor responses depend on CD8⁺ T cells. Tumor-bearing mice were treated with CY at day 10 after tumor inoculation (day 0) and anti-CD8 mAbs (150 µg) were injected at days −1, 0, 2, 4, 6 and 8 with respect to CY treatment. Data shown are mean±SEM (<i>n</i> = 5) from one representative experiment from a total of three experiments with a total of 15 mice. * P<0.05 when CY is compared with CY + anti-CD8. (B) <i>In vivo</i> IFN-α/β neutralization marginally affects tumor growth in CY-treated mice. BALB/c mice bearing AB1-HA tumors were given IFN-α/β blocking antibody on days −1, +2, +4 with respect to CY treatment. Tumors were inoculated at day 0 and were treated with CY at day 9. Data shown are mean±SEM (<i>n</i> = 5) from one experiment. <i>ns</i> = not-significant.</p

CD8 T cell effector mechanisms.

<p>(A) Tumor growth and Kaplan-Meier survival curves in CY-treated IFN-γ-deficient mice and control mice. Data shown are mean±SEM (<i>n</i> = 5) from one experiment (growth curve, left panel) or total data from two experiments (survival curve, right panel). Tumor cells were inoculated at day 0, treated with CY at day 9. * P<0.05 when CY in immunocompetent mice and IFN-γ deficient mice is compared. (B) Tumor growth curves and Kaplan-Meier survival curves in CY-treated perforin-deficient and normal control mice. <i>ns</i> = not significant when CY in immuno-competent and perforin-deficient mice are compared. Tumor cells were inoculated at day 0 and treated with CY at day 8. <i>ns</i>, not significant. (C) Tumor growth and Kaplan-Meier survival curves after CY treatment in perforin/IFN-γ double-deficient mice, compared to immunocompetent mice. Data shown are mean±SEM (<i>n</i> = 5) from one experiment (growth curve, left panel) or total data from two experiments (survival curve, right panel). Tumor cells were inoculated at day 0 and treated with CY at day 9. * P<0.05, *** P<0.001 when BALB/c <i>+</i> CY is compared with IFN-γ/<i>pfp</i>-ko + CY.</p