- Top of page
- Tool Description
- Case Study Setup
- Results and Discussion
Allogeneic stem cell therapies will potentially be able to treat a broad range of unmet medical needs ranging from dry eye related macular degeneration to acute myocardial infarction. They are particularly promising for treating large patient numbers as they are obtained from a universal donor and are thus more suited to manufacturing at large scale. To date, commercialized allogeneic stem cell therapies include Prochymal (Osiris, Columbia, MD) for graft-versus-host disease, approved in Canada and New Zealand, and Cartistem (Medipost, Seoul, Korea) for osteoarthritis, approved in South Korea. However, several products have faced challenges achieving scalable, robust, and cost-effective manufacturing processes (Brandenberger et al., 2011; Griffith and Naughton, 2002; Kirouac and Zandstra, 2008; Ratcliffe et al., 2011; Rowley et al., 2012). This has contributed to several notable failures due to manufacturing concerns such as high cost of goods (COG), high process variability, and loss of efficacy upon scale-up (Brandenberger et al., 2011). Hence the commercial feasibility of cell therapies is underpinned by the need to solve the manufacturing challenges posed by large-scale production. This article investigates the technical innovation required in cell expansion technologies for cell therapy products to realize their commercial potential and achieve the manufacturing success of biopharmaceuticals.
Biopharmaceuticals, such as monoclonal antibodies (mAbs), have benefited from the availability of large-scale bioprocessing technologies and the associated economies of scale (e.g., Birch and Racher, 2006; Farid, 2006; Kelley, 2007). However, this is not currently the case for allogeneic cell therapy manufacture due to its relative infancy as well as the inherent complexities of manufacturing living cells as the final product. In contrast to mAbs, only a limited number of cases of xeno-free cell culture media for cell therapy products have been reported (Lindroos et al., 2009; Rajala et al., 2010). Additionally, the culture can also include feeder cells to promote growth. Although cell lines used to generate mAbs are adapted to suspension culture, most cell therapies require adherent culture. This introduces challenges for scale-up to commercial demands. Following expansion and potential differentiation of cell therapy products, the cells are typically washed and centrifuged for cell concentration and recovery. Large-scale centrifuges such as disc stacks (Kempken et al., 1995) used in mAb manufacture are not suitable for the processing of shear-sensitive cells, and hence the use of alternative single-use recovery equipment such as closed continuous fluidized bed centrifuges (e.g., kSep® Systems, Durham, NC) is being explored. The transportation of cell therapy products is also more complex since the product cannot be lyophilized (freeze-dried) as is the case with mAbs; cell therapy products are typically delivered either fresh or cryopreserved (frozen). Both delivery options necessitate costly cold chains with the fresh state requiring careful and timely inventory management between manufacturing sites and the clinic and the cryopreserved state requiring clinics to maintain the frozen state in expensive freezers until the time of patient administration. Cryopreservation is more typical for allogeneic cell therapy treatments given the benefits of “off-the-shelf” inventory when creating many doses per lot to treat large numbers of patients. Considering facility design distinctions, although single-use technologies are increasingly being adopted in mAb manufacture for vessels typically below 2000L, their adoption is essential in cell therapy bioprocessing due to sterility concerns (Lapinskas, 2010). In contrast to the well-established mAb sector, the poor automation, labor-intensive, and more open nature of cell therapy manufacture makes it more prone to operator-mediated variability (Lopez et al., 2010), and contamination risks. Closed and automated technologies are now becoming available to address the need for greater process robustness and reproducibility.
Table I highlights several allogeneic cell therapy treatments and their current phase of development. Most are in the clinical trials stage. To date, allogeneic cell therapy products in development have mainly consisted of mesenchymal stem cells or mesenchymal progenitor cells derived from the bone-marrow (Kebriaei et al., 2009; Goldschlager et al., 2011; Vaes et al., 2012), umbilical-cord blood (Jung et al., 2011), liver (Christ and Stock, 2012), or adipose (DelaRosa et al., 2012). Promising results have also been observed for cells differentiated from embryonic stem cells such as retinal pigment epithelial cells (Schwartz et al., 2012), or from fetuses for neuronal stem cell production (Miljan and Sinden, 2009; Tamaki et al., 2002). Table I highlights that the doses (cells/patient) typically used for cell therapy products currently range from 105 cells for indications such as dry eye related macular degeneration to 109 cells for liver disease, GvHD or cardiac disease (e.g., infarction; Reinecke et al., 2008). Accordingly, a maximum dose of 109 cells is investigated in this study. Most companies in clinical trials are using 2-D multi-layer vessels (e.g., 10-layer Cell Factories (Nunc, ThermoFischer Scientific, Waltham, MA) CellSTACKs (Corning Incorporated Life Sciences, Tewksbury, MA) as their main expansion technology (Rowley et al., 2012). It is estimated that up to 1012–1013 cells will need to be produced per lot to meet commercial demands of high dose cell therapies. This would represent the use of 10,000–100,000 10-layer vessels per lot (values calculated by the model described in this article). However, only 50–100 vessels can be handled per lot due to the need to perform labor-intensive handling tasks, rendering this type of system unsuitable for large-scale production.
Table I. Characteristics of allogeneic cell therapies currently under development
|Indication||Cell types under investigation||Dose for clinical trials (cells/dose)a|
|Acute kidney injury||Bone-marrow derived hMSCs||2 × 108 |
|Acute myocardial infarction||Bone marrow or other nonembryonic tissue source-derived Multistem||0.2, 0.5, 1 × 108 |
|Chronic Discogenic Lumbar Back Pain||Bone-marrow derived adult mesenchymal precursor cells||0.6–1.8 × 107 |
|Congestive heart failure||Bone-marrow derived adult mesenchymal precursor cells||1.5 × 108 |
|Critical limb ischemia||Placenta-derived PLX-PAD stromal cells (hMSC-like)||1.5–3 × 108 |
|Crohn's disease||Adipose-derived expanded stem cells (eASCs); Bone-marrow-derived hMSC||2, 4 × 107 ; 6–12 × 108 |
|Dry eye related macular degeneration||Embryonic Stem Cell-Derived Retinal Pigment Epithelial (RPE) Cells||0.5–2 × 105 |
|Graft vs. host disease||Umbilical cord blood-derived hMSC; Bone-marrow-derived hMSC; Bone marrow or other nonembryonic tissue source-derived Multistem||1–5 × 108 ; 1.6 × 109 ; 0.5–1 × 109 |
|Intracerebral hemorrhage (ICH)||Bone-marrow derived hMSCs||7.8 × 106 |
|Ischemic stroke||Human foetal brain stem cell-derived hNSC; Bone-marrow-derived hMSC; Bone-marrow derived hMSC||2 × 107 ; 0.5 −1.5 × 108 ; 2 × 108 |
|Liver disease||Adipose-derived stromal cells||0.1–1 × 109 |
|Osteoarthritis||Bone-marrow- derived hMSC; Umbilical cord blood-derived hMSCs (hUCB-MSCs)||5–15 × 107 ; 3.5 × 107 |
|Peripheral vascular diseases||Menstrual blood-derived Endometrial regenerative cells (hMSC-like)||0.25–1 × 108 |
|Prostate cancer||Prostate tumour-derived cancer cell line||2–4 × 107 |
|Rheumatoid arthiritis aggravated||Adipose-derived expanded stem cells (eASCs)||1–4 × 108 |
|Spinal cord injury||hESC-derived oligodendrocyte progenitor cells; Foetal-derived hNSCs; Brain-derived hNSCs||2 × 106 ; 2 × 107 ; 1 × 108 |
|Type I diabetes||Bone-marrow-derived hMSC||6 × 108 |
|Type II diabetes||Bone-marrow derived adult mesenchymal precursor cells||0.1, 0.3, 1, 2 × 108 |
|Ulcerative colitis||Bone-marrow-derived multipotent adult progenitor cell (MAPC)||1.8 × 108 [11,15]|
The need for closed systems to limit the potential points of contamination, to produce more cells per unit footprint, and for greater upstream production control has driven the production of compact multi-layered systems (e.g., HYPERStack (Corning, Incorporated Life Sciences, Tewksbury, MA)), multi-layer bioreactors (e.g., Integrity Xpansion unit (ATMI, Danbury, CT)), and scalable microcarrier-based bioreactor systems. To successfully meet higher future demands, it is necessary to determine the practical and economic feasibility of each technology.
To date, there has been a limited number of studies addressing impact on costs and expansion technology limitations in the cell therapy industry. Hambor (2012) identified the probable need for increasing automation and controlled bioreactor systems for the production of clinical grade cell therapy products. Automation has been advanced by the introduction of robotically controlled equipment such as TAP Biosystems' SelectT and CompactT systems, which increase the potential of T flasks. Prior studies estimating the number and type of expansion technologies required to meet a demand (Rowley et al., 2012; Want et al., 2012) were solely based on technical inputs such as surface area, size, and density. In another study, based on interviews and various model assumptions, Malik (2012) estimated the cost to produce allogeneic cell therapy products for a fixed demand of 2,500 doses/year, where a single dose represented 108 mesenchymal stem cells using T-flasks with automation.
This article presents an integrated decisional tool combining bioprocess economics and optimization for addressing cell therapy manufacturing challenges. The detailed cost model accounts for both technical inputs such as media requirements as well as financial inputs such as resource costs. The bioprocess economics model presented in this article focuses on the upstream processing cost of goods (COGUSP) components that are expected to be more affected by the choice of different expansion technologies for allogeneic cell therapy manufacture, that is, raw materials (particularly cell culture media and single-use technologies), labor, and depreciation of equipment directly related to the cell expansion step. It also incorporates QC costs associated with lot release testing such that different manufacturing options in terms of lot size and number of lots per year can be compared.
The novelty of this work lies in the integration of bioprocess economics and optimization approaches to systematically assess the economic competitiveness of planar and microcarrier-based cell expansion technologies, predict the optimal and most cost-effective technology for different scales, identify gaps in the available technologies and predict future performance targets necessary to meet commercial demands for cell therapies.
Case Study Setup
- Top of page
- Tool Description
- Case Study Setup
- Results and Discussion
An industrially relevant case study was set up to illustrate and examine the ability of the proposed tool to discover optimal cell expansion strategies for the design of cell therapy manufacturing processes. The case study focuses on therapies using mesenchymal stem cells derived from bone marrow. Different allogeneic cell therapy products are considered, with doses within the range identified from Table I and with potential for high commercial demands of up to 500,000 doses/year (e.g., assuming a 10% market share of a 5 million patient population, as indicated for heart disease by Mason and Dunnill, 2009). The goal of the study was to investigate which commercially available technologies would be the most cost-effective for meeting production demands. This analysis would allow for resources to be allocated appropriately for relevant experimental validation and optimization of the most promising technologies at earlier stages of development, thus potentially reducing risk.
Table II presents the different planar technologies evaluated for cell expansion and specific characteristics of each candidate, generated using information from literature, vendor communications, as well as advice sought from industrial experts so as to capture trade-offs in surface area, cost, equipment, and labor requirements. Six types of planar technologies were considered and generic names were given: T-flasks (T), multi-layers (L), compact flasks (cT), compact multi-layers (cL), multi-layer bioreactors (bL), and hollow-fiber bioreactors (HF). Examples of associated commercial names are shown in the footnote of Table II. Each type of technology is sized by surface area or the number of layers and this is represented by numerical values (e.g., T175 is a T-flask with 175 cm2 of surface area and L-10 has 10 layers). The use of additional automation equipment is indicated by the suffix “(aut),” as in the case of L-40 and cL-120. It is assumed that these two technologies have a similar footprint and 4 units can be handled simultaneously by a robot (automated cell factory manipulator, ACFM) performing seeding (filling) and harvesting (emptying) operations. The use of microcarriers in SUBs was also considered as a candidate technology for cell expansion but only for those demand scenarios where the use of planar systems would exceed the maximum number of units imposed by Equation (10). This was implemented to reflect the current industrial preference for planar cell expansion technologies. The parameters used for different SUB sizes are presented in Table III. The values for the surface area (cm2/g) and density (g/L) of the microcarrier-based technology assumed in the case study were based on literature data. Ranges of 360–5,500 cm2/g and 3.3–9.3 g/L have been reported in the literature for the expansion of adult stem cells using non-porous microcarriers, as shown in Table IV. The mid-point values of 2,930 cm2/g and 6.3 g/L were used for the microcarrier surface area and density, respectively. Although these values were initially used to estimate the required size and number of SUBs to meet large demands, a sensitivity analysis was subsequently carried out in order to determine the impact of the variation of the microcarrier surface area on the optimal expansion strategy across different demand scenarios.
Table II. Key parameters for candidate planar cell expansion technologies
|Type||Name||Surface area, ai (cm2)||Consumables unit price, pconsum ($)||Media req., Vmedia (mL/cm2)||Labor requirements (time per operator to handle max # units)||Requires biosafety cabinet||Incubator capacity, Uincub (# units)||Ancillary control and automation equipment|
|Seed time, tseed (h)||Feed time, tfeed (h)||Harvest time, tharvest (h)||Max # unitsa||Capacity, Uanc (# units)||Price, panc ($)|
|Hollow fiber bioreactorsh||HF||21,000||12,000||0.37||0.20||0||0.20||1||N||—||1||150,000|
Table III. Key process and cost assumptions used in the case study
|Number of expansion stages (N)||4|
|Seeding density ||3,000 cells/cm2|
|Harvest density ||25,000 cells/cm2|
|Overall process yield (y)||85%|
|Maximum # units/lot (umax for planar technologies)||80|
|Maximum #SUBs/lot (umax for microcarriers)||8|
|Microcarrier surface area (amicrocarrier)||2930 cm2/g|
|Microcarrier seed concentration (cmicrocarrier)||6.3 g/L|
|Single-use bioreactor working volume ratio (λ)||75%|
|Cell culture media (pmedia)||$150/L|
|Single-use bioreactor bag (pSUB(Vbior))||$2,000 (20L); $4,500 (200L); $5,850 (500L); $8,850 (1000L); $10,500 (2000L)|
|Single-use bioreactor support equipment (panc for microcarriers (Vbior))||$185,000 (20L); $215,000 (200L); $320,000 (500L); $425,000 (1000L); $575,000 (2000L)|
|L-40/cL-120 incubator (pincub for L-40 and cL120 systems)||$30,000|
|Double stack incubator (pincub for other systems)||$17,835|
|Biosafety cabinet (pBSC)||$17,000|
|Operating labor ||$200/h|
|QC testing ||$10,000/lot|
|Other labor cost multiplier (β)||2.2|
|Depreciation period (tdep)||10 years|
Table IV. Reported ranges for microcarrier surface area and density values for mesenchymal stem cells
|Type of microcarrier||Surface area (cm2/g)||Density (g/L)|
|Sources: Vendors (Percell Biolytica, GE Healthcare, Thermo Fisher Scientific, SoloHill Engineering), Sart et al. (2010), Wu et al. (2003), Rubin et al. (2007), Yang et al. (2007), Frauenschuh et al. (2007), Zayzafoon et al. (2004), Meyers et al. (2005), Whitford and Fairbank (2011).|
The tool was run for different scenarios in terms of annual demand (1,000–500,000 doses/year) and manufacturing lot size (50–10,000 doses/lot) in order to determine the most cost-effective cell expansion technologies and identify the limits of existing technologies. The key process and cost parameters used in the model for the case study are shown in Table III.