Stability Program in Dendritic Cell Vaccines: A "Real-World" Experience in the Immuno-Gene Therapy Factory of Romagna Cancer Center

Abstract

Advanced therapy medical products (ATMPs) are rapidly growing as innovative medicines for the treatment of several diseases. Hence, the role of quality analytical tests to ensure consistent product safety and quality has become highly relevant. Several clinical trials involving dendritic cell (DC)-based vaccines for cancer treatment are ongoing at our institute. The DC-based vaccine is prepared via CD14+ monocyte differentiation. A fresh dose of 10 million DCs is administered to the patient, while the remaining DCs are aliquoted, frozen, and stored in nitrogen vapor for subsequent treatment doses. To evaluate the maintenance of quality parameters and to establish a shelf life of frozen vaccine aliquots, a stability program was developed. Several parameters of the DC final product at 0, 6, 12, 18, and 24 months were evaluated. Our results reveal that after 24 months of storage in nitrogen vapor, the cell viability is in a range between 82% and 99%, the expression of maturation markers remains inside the criteria for batch release, the sterility tests are compliant, and the cell costimulatory capacity unchanged. Thus, the data collected demonstrate that freezing and thawing do not perturb the DC vaccine product maintaining over time its functional and quality characteristics.

Keywords: ATMP; dendritic cell vaccine; immunotherapy; quality control; stability.

Figure 1

(a) Representative graphical of DCs vaccine manufacturing. Patients’ monocytes are obtained by leukapheresis procedure and subsequently differentiated into DCs. Cells are cultured with GM-CSF and IL-4; on day 6, DCs are pulsed with autologous tumor homogenate derived from surgically removed tumor; and on day 7 are matured for 48 h with TNFa, IL-1b, IL-6, and PGE2. Finally, a fresh final product is administered to the patient. (b) Representative graphical abstract of experimental plan of stability program created with Biorender.com.

Figure 2

Functional testing of viable cell count. (a) The viability of DCs intra-batch was evaluated in a time-dependent manner. (b) The graph shows the viability analysis of all batches analyzed in the stability program. The red lines indicate the median value.

Figure 3

Flow cytometry analysis of the DCs vaccines at different time points. (a) Flow cytometry gating strategy. (b–e) Graph shows the percentage expression analysis of DCs maturation markers (HLA-DR, CD80, CD86, CD83). The black lines indicate the mean percent positive for each marker.

Figure 4

(a) Results of the ELISPOT Costim assay are shown as a bar-plot of SFCs (mean ± SD) at several time points. The different symbols shapes represent the mean of quadruplicate of each activated CD3+ T cell donor. (b) Regression analysis of poolability of all batches. Pooled regression line of the batches resulting after the tests of equality of slopes and intercepts of the regression lines. Each circle represents the mean value of the replicates of each donor at different time points.