An automated and closed system for patient specific CAR-T cell therapies

Autologous cell therapies, particularly chimeric antigen receptor T-cell (CAR-T) immunotherapies, are becoming a promising treatment option for difficult diseases. Immunotherapies for blood cancers have dominated the pipeline, while treatments for solid tumors have started to become more successful. However, as the market continues to grow and more clinical trials begin globally, the challenge of manufacturing autologous cell therapies remains significant. A greater number of patients will lead to an increase in cost, labor, and the complexity of logistics for scaling out the commercial production of patient specific therapies. To enable clinical and commercial success, novel manufacturing platforms, such as closed and automated systems, will be required to produce cost effective and robust therapies. This abstract highlights a successful CAR-T process translation from a manual process to an automated patient scale system. To accomplish a CAR-T process translation, we utilized a platform that automates cell seeding, activation, transduction, real time process monitoring, feeding, washing and concentration, and harvesting. In order to mimic a therapeutic CAR-T cell process, manual research scale processes were optimized, scaled up, and then programmed to run automatically without manual intervention. In these processes, 100 million peripheral blood mononuclear cells (PBMC) were first inoculated with CD3/CD28 activation beads. The following day, cells were transduced with HER-2 lentivirus vector. Cells were then expanded with a defined feeding strategy and IL-2 supplements until harvested when target yields were reached. After harvest, cells were analyzed for cell yield, viability, transduction efficiency, and an array of cell phenotype, potency and functionality via FACS and killing assays. Specifically, CAR-T cells were analyzed for the presence of naïve T cells, T stem cell memory, T central memory, T effector memory, and T effector cells. We show here how we optimized, scaled up, and automated manual processes to reach clinical requirements. Automated runs using the above process with cells transduced by HER-2 virus yielded an average of 2 x 109 cells post harvest with a viability \u3e 90%. Automated runs and associated controls were able to support the expansion of both CD4+ and CD8+ T cells with 73% CD4+ T cells and 20% CD8+ T cells. Harvested cells yielded approximately 80% NGFR+ cells with a higher detection of NGFR in the CD4+ fraction than in the CD8+ fraction for all samples. Both CD4+ and CD8+ subsets demonstrated T cell phenotype such as naïve T cells, T stem cell memory, T central memory, T effector memory, and T effector cells. Both subsets also only expressed between 15-20% of immunosuppressive regulatory T cells. Cell health was evaluated by the levels of exhaustion marker, PD-1, which was 19% in CD4+ T cells and \u3c 1% in CD8+ T cells. Furthermore, there was a negligible amount of senescent T cells and anergic cells and \u3c 10% expression of the apoptotic marker, Caspase-3. Subsequently, cells from multiple automated runs showed the specific killing of NGFR+ tumor line were correlated with high levels of effector cytokines: TNF-alpha (~34%) and IFN-gamma (20-25%) as compared to a manual control. In summary, automated CAR-T process in the Cocoon system yields a healthy populations of T cell subsets. This system is a viable solution to translate labor-intensive CAR-T process into a fully automated system, thus allowing scalability, high yield, reduction of manufacturing cost, and better process control to yield high quality CAR-T cells

Wear Particles Derived from Metal Hip Implants Induce the Generation of Multinucleated Giant Cells in a 3-Dimensional Peripheral Tissue-Equivalent Model

<div><p>Multinucleate giant cells (MGCs) are formed by the fusion of 5 to 15 monocytes or macrophages. MGCs can be generated by hip implants at the site where the metal surface of the device is in close contact with tissue. MGCs play a critical role in the inflammatory processes associated with adverse events such as aseptic loosening of the prosthetic joints and bone degeneration process called osteolysis. Upon interaction with metal wear particles, endothelial cells upregulate pro-inflammatory cytokines and other factors that enhance a localized immune response. However, the role of endothelial cells in the generation of MGCs has not been completely investigated. We developed a three-dimensional peripheral tissue-equivalent model (PTE) consisting of collagen gel, supporting a monolayer of endothelial cells and human peripheral blood mononuclear cells (PBMCs) on top, which mimics peripheral tissue under normal physiological conditions. The cultures were incubated for 14 days with Cobalt chromium alloy (CoCr ASTM F75, 1–5 micron) wear particles. PBMC were allowed to transit the endothelium and harvested cells were analyzed for MGC generation via flow cytometry. An increase in forward scatter (cell size) and in the propidium iodide (PI) uptake (DNA intercalating dye) was used to identify MGCs. Our results show that endothelial cells induce the generation of MGCs to a level 4 fold higher in 3-dimentional PTE system as compared to traditional 2-dimensional culture plates. Further characterization of MGCs showed upregulated expression of tartrate resistant alkaline phosphatase (TRAP) and dendritic cell specific transmembrane protein, (DC-STAMP), which are markers of bone degrading cells called osteoclasts. In sum, we have established a robust and relevant model to examine MGC and osteoclast formation in a tissue like environment using flow cytometry and RT-PCR. With endothelial cells help, we observed a consistent generation of metal wear particle- induced MGCs, which heralds metal on metal hip failures.</p></div

Increase in particle to cell ratio increases frequency of dead cells.

<p>Particles were added at the time of gel polymerization at a ratio of 500:1, 100:1, or 10:1 or without particles (0:1) to PBMCs, as described previously, and incubated for 48h. Similar particle treated co-culture was set up in the absence of collagen gel in conventional 24 well plate. Cells were harvested with collagenase treatment from collagen gel, and stained with Live/Dead dye before acquisition on a flow cytometer. Cells from conventional culture plates were harvested by gentle pipetting and stained with Live/ Dead dye. 50,000 events were acquired on BD canto II and frequency of dead dye positive cells is represented in figure.</p

3-D model containing collagen gel generates a greater number of MGCs.

<p>For the 3D model, 100 million particles were added at the time of gel polymerization (a ratio of 100:1 particles: PBMCs) and a monolayer of endothelial cells was grown on top of the gel (C). For the 2D model, endothelial cells were grown to form a monolayer and the particles were added to the monolayer (B). One million PBMCs were seeded on top of the endothelial monolayer in both models and incubated for 2 weeks. As a control, PBMCs alone were exposed to gel embedded with particles (A). On the 14th day, cells were harvested (following collagenase treatment in the 3D model), fixed and permeabilized using BD cytofix/perm buffer. Cells were then stained with PI and acquired on a flow cytometer.</p

The level of IFN-γ was reduced while IL-10 level was increased in 10:1 treatment supernatants of day 14 culture.

<p>The 3-D model was prepared as previously stated, and supernatants were collected on days 4, 7, 9, and 14. Luminex Cytokine Th1/Th2 5-plex Immunoassay kit was used to measure the concentrations of IFN-γ, IL-2, IL-4, IL-5, and IL-10. The results are represented as mean +/- S.E. of three experimental samples from three independent experiments, n = 3. Asterisks, * = p < 0.05, indicate statistically significant IFN-γ decrease in 10:1 particles exposed cells at day 14 compared with those at day 4. ** = p < 0.005 indicate statistically significant IL-10 increase in 10:1 particles exposed cells at day 14 compared with those at day 4.</p

Higher frequency and number of MGC formation at a 10:1 ratio compared to 100:1 and 500:1 ratios in 3-D model.

<p>Particles were added at the time of gel polymerization at a ratio of 500:1, 100:1, or 10:1 or without particles (0:1) to PBMCs, as described previously, and incubated for 2 weeks. Cells were harvested with collagenase treatment, fixed and permeabilized using BD cytofix/ perm buffer, and stained with propidium iodide before acquisition on a flow cytometer. Frequency of MGCs per 50,000 events is represented in A, while the MGCs number is represented in B. The results are represented as mean +/- S.E. of three independent experiments, shown as n = 3 for “0:1” and “10:1”. Asterisks indicate statistically significant MGCs increase in particles exposed cells at 10:1 compared with those untreated cells, none. (** = p < 0.005; *** = p <0.0005).</p

Particles at 10:1 ratio induced protein expression the DC-STAMP and TRAP in day 14 cultures.

<p>As described above, co-cultures were set up at 10:1 ratio and incubated for 14 days. Cells were harvested by collagenase treatment, washed and intracellular stained with propidium iodide, FITC conjugated- TRAP and APC conjugated-DC-STAMP. Both the dot plots (A and B) were first gated for giant cell i.e. high Forward Scatter and high PI positive cells, and then for DC-STAMP and TRAP. Cells without particles are represented in (A) and with particles in (B).</p

Elevated mRNA levels of TRAP, DC-STAMP and GM-CSF in day 14 co-cultures.

<p>Particles were added at the time of gel polymerization at the ratio of 10:1 particles to PBMCs. Endothelial cells (EA) were grown on the gel to form a monolayer. Peripheral blood mononuclear cells (PBMCs) were seeded either on top of the monolayer. Cells were harvested by digesting the gel with RNA extraction buffer and proceeded for RT-PCR as described in method. Each bar is represented as mean +/- S.E. of two experimental samples from two independent experiments, n = 2. *Asterisks indicate statistically significant TRAP and GM-CSF increase in particles exposed cells at day 14 compared with day0, (** = p< 0.005, * = p < 0.05)</p