Cost of Goods Modeling and Quality by Design for Developing Cost-Effective Processes - Combine cost analyses with QbD to improve operations and lower costs. - BioPharm International
Increases in recombinant protein titers expressed in mammalian cells and cell culture process volumes have shifted the economic
paradigm from upstream processing to downstream processing for the manufacturing of recombinant proteins, especially monoclonal
antibodies (MAbs). Moreover, the pressure exerted by authorities on the healthcare industry to decrease the costs associated
with treatments, and the recent entry of biosimilars into the market, have forced the biopharmaceutical community to find
new solutions and strategies to reduce production costs. MAb process development currently is focused on the optimization
of yield and throughput to deliver cost-effective processes. In this article, we describe the use of a cost of goods model
in combination with a Design of Experiment approach for optimizing the capture step by affinity chromatography. The most economical
operating conditions identified through this approach imply sacrificing some protein without affecting the quality of the
final product.
Merck Serono
The market for therapeutic proteins, particularly monoclonal antibodies (MAbs), is rapidly expanding. Indeed, it represents
the industry segment with the highest growth rate over the last decade.1,2,3 To meet the increasing market demand, the biopharmaceutical industry is looking for new strategies to increase bioprocessing
productivity while minimizing production costs. Bioprocesses have to be carefully fine-tuned to ensure the consistent quality
of the material produced, and initiatives such as Quality by Design (QbD) should result in the implementation of robust and
flexible processes from the start. Additionally, biotechnology companies must develop processes that are cost effective. The
pressure from competition—molecules being approved for the same indications, patent expiry, and the arrival of biosimilars—will
put increased pressure on sale prices and as a result, the minimization of production costs will be essential for maintaining
economically viable products.1,4,5,6
Understanding manufacturing process costs is not trivial; many important factors are not directly related to the process itself—plant
capacity, equipment depreciation, allocation, and other fixed costs—can make cost estimation extremely difficult.7 For an accurate evaluation of expenses, a detailed process description with facility and equipment depreciation is needed.
An exhaustive process simulation tool such as SuperPro Designer (Intelligen, Scotch Plains, NJ) can be used to model bioprocesses.
This modeling includes a detailed description of the process steps, from vial thawing to final drug substance, with all related
costs (direct and indirect). It is then possible to accurately estimate the final unit cost of the product generated at manufacturing
scale.
Figure 1
This article describes the successful combination of a cost of goods (COGs) model (using SuperPro Designer) with a Design
of Experiments (DOE) approach to reduce the cost associated with the affinity chromatography step for the capture of a MAb.
COST OF GOODS CALCULATION
Table 1. Cost of goods estimation
SuperPro Designer is a process simulation tool developed for modeling industrial recombinant protein production processes.
SuperPro Designer takes into account all the process and subprocess steps and their associated costs. Additionally, fixed
costs related to the infrastructure, such as building and equipment, also can be incorporated. The resulting COG models generated
allow the user to predict the production costs of processes—performed at manufacturing scale—from cell thawing to final drug
substance bulk.
Figure 2
The MAb process modeled in this case study (Figure 1) was a typical three-step platform process adapted to fit into a facility
with a maximum cell culture capacity of 120,000 L, a protein titer of 2 g/L, an overall yield of 80% on the downstream process
(DSP), and an annual MAb throughput of 4,500 kg. The facility described by the model was assumed to be an entirely new plant
used at full capacity. For simplicity, the upstream process (USP)—from inoculum to clarified harvest—was lumped into a single
unit operation. To accurately calculate the upstream costs, the entire USP was modeled separately, and a cost per liter of
clarified harvest was determined. This harvest cost was then used as an input for the DSP process calculations. The different
cost categories used for calculations are listed in Table 1.
Figure 3
A more complex model also was developed to account for the progressive degradation of the capacity of the resin when increasing
the number of cycles performed on the column, a well-documented phenomenon for Protein A affinity chromatography steps. This
additional level of complexity, however, does not provide a better illustration of the concepts proposed in this case study.
Figure 4
The output of the MAb platform COG analysis is shown in Figure 2. Facility-associated costs account for almost 35% of the
total costs, while raw materials and consumables represent 31% of the entire production costs. A further breakdown of the
process-related costs for the different unit operations (Figure 3) shows that DSP accounts for more than 65% of the total
production costs. Among the three DSP steps, the capture alone accounts for 25% of the total costs. By further breaking down
the costs of this unit operation (Figure 4), you can see that the capture step contribution is driven by consumables, specifically
the Protein A resin. Therefore, to reduce a MAb process cost, decreasing the consumption of the Protein A resin, by maximizing
loading or increasing resin lifetime, for example, will have the greatest effect.
Matteo D. Costioli is a bioprocess and innovation downstream process specialist at the Center of Expertise, Merck Serono SA
Articles by Matteo D. Costioli
