In recent years, improving downstream manufacturing has become an emerging challenge to the biopharmaceutical industry. Initially, the bottleneck in biopharmaceutical manufacturing existed in the output of bioreactors. Due to advances in cell line development and upstream process (i.e., perfusion), the output of bioreactors has increased at a much faster pace than downstream processing capacity.
For monoclonal antibodies (mAbs), titers have increased almost 30-fold over a 15-year period.1 In addition, mAbs and other therapeutic biologics represent the fastest growing sector of the entire pharmaceutical market with many pipeline candidates reaching late-stage development, including 53 mAbs in phase III trials as of late 2015.2 By 2019, the biological market is expected to exceed 20% of the global pharmaceutical market share at a value of $386.7 billion.3 The rapid growth of biopharmaceuticals and increasing upstream production yield has imposed substantial pressure to the existing downstream processing capacity.
Traditionally, downstream purification has been governed by batch chromatography, in which desired products are captured and purified via a single large chromatography column. An imbedded drawback of batch chromatography lies in its limited ability to expand processing capacity. Once installed, switching the existing capture column to a larger-size column is often physically and economically challenging. Another design flaw in batch chromatography is its inability to load chromatography resin to its full capacity since product breakthrough must be avoided, which can translate to an underutilization of the resin and hence considerable resource waste.
To cope with the increasing demand on downstream processing, capture columns generally have to be cycled multiple times, which creates additional holding time when the load material is not being processed .
The biopharma industry would benefit greatly from an improved process to more efficiently use the resin in the capture step. Multi-column chromatography achieves both better productivity and cost reduction, making it an attractive solution to meet this challenge. Most importantly, remarkable recent progress has been made in this area, enabling smooth implementation of MCC into downstream bioprocessing.
MCC is based on the same fundamental principles as batch chromatography with slight differences in design, operation and application.1
How It Works
In a multi-column paradigm, product is captured during the load phases using a series of small columns connected in series to create a load zone, instead of one large column in batch mode. Each column size can be 10 to 20 (or more) times smaller than a single conventional batch column.5 Effluent material from the first column is passed over a second column, thereby collecting any breakthrough product not bound by the first column in the series. During operation, once the first column is fully loaded and washed, it is disconnected from the series and the second column becomes the lead-loading column in the load phase. The first column is then eluted, regenerated, equilibrated and cycled back to the end of the column series while the second column reaches saturation and is ready to be separated from the system. Product breakthrough is no longer a major concern in MCC since the unbound products are bound by the second column in the load series.
In a complete MCC cycle, a column is loaded before going through wash, elution, regeneration and equilibration steps sequentially without even interrupting the loading of the other columns, thus achieving continuous processing. By contrast, in batch chromatography, the loading is stopped well before the saturation of the resin with the product, and the whole column must be processed through the entire sequence of phases before additional load material can be processed.
Overall, MCC must still operate within the limitations of the inherent binding kinetics of a given target molecule and resin, but the configuration of sequential columns optimizes the process to allow higher operating binding capacity compared to batch mode chromatography. This major improvement in MCC allows the operational binding capacity to approach equilibrium binding capacity, or complete resin utilization. Conversely, in batch chromatography, the resin is typically loaded to less than 80% of the dynamic binding capacity (where product breakthrough is observed), which corresponds to ~60% of the complete utilization that MCC targets.5
Bio SMB Technology
MCC not only enhances resin capacity utilization but also significantly increases productivity (grams of product purified per liter of resin per hour, g/L/hr) and reduces the volume of resin needed as well as buffer consumption. In a comparison study of a typical clinical-scale (2,000-liter bioreactor; 3.5 g/L mAb) Protein A capture process, the MCC process using Cadence BioSMB technology (Pall Corporation) achieved a productivity of 50 g/L/hr using 8 columns with 20 centimeter (cm) internal diameter (ID) and 7 cm of bed height and 17 liters of resin. The corresponding batch process reached a productivity of 8.17 g/L/hr using a single column with an ID of 80 cm and height of 20 cm and 100 liters of resin. Total buffer consumption was reduced by more than 30%.1, 7 Overall, BioSMB technology requires reduced resin volume to operate but offers a higher degree of flexibility to accommodate capacity demands. The system can readily meet the desired processing capacity by adjusting the number of columns, and possibly switch times.
Straightforward Transition from Batch to MCC
The MCC platform is quite comparable to batch chromatography as they both are developed based on the same principles and use the same chromatography media and buffer systems. The product and process knowledge accumulated by batch processing can be used to set up and optimize MCC process. In addition, MCC technology is designed to be compatible with existing manufacturing setups. Therefore, converting a batch process into an MCC-based continuous process is surprisingly simple and straightforward.
The configuration starts with a few small-scale single column breakthrough experiments to determine the breakthrough curves that are used to determine the ideal operating bind capacity (OBC) for MCC (i.e., the amount of product bound to the first column before product breakthrough occurs onto the second column).7 Another important parameter in MCC is the residence time calculated by dividing column volume with flow rate (column volume/flow rate).8 The design space can then be modeled through a series of single column experiments to determine the range of optimal loading residence times to achieve desired productivity.
To facilitate the process transition, many MCC systems offer complementary software that enables in silico modeling of the MCC system. This computational approach can be a valuable tool in predicting the impact of process variability on process performance as well as selecting process parameters, especially during process scale-up. In addition, the simulation data generated from the software is fairly accurate in predicting physical performance of the process as it is verified by the experimental results.9
Another appealing feature of MCC is automation. The BioSMB technology, for example, is a fully automated MCC system in which the only manual labor required is to set up the buffer and column connections prior to the continuous run. Moreover, the BioSMB control software provides on-line monitoring and control functions that include UV/vis absorbance, conductivity and pH monitoring of multiple outlets, as well as pressure measurements at all inlets.1 In addition, the use of disposable technologies, such as pre-packed columns, with BioSMB can further simplify the process and reduce labor cost and human error. In MCC processes, pre-packed columns are much preferred to ensure column performance consistency.
CMC Biologics Leads the Transition towards MCC-Based Downstream Manufacturing
The multi-column chromatography technology offers prominent productivity gains and economic advantages for downstream bioprocessing. Despite the upfront capital expenses required for adopting MCC technology, the significant cost savings achieved from resin reduction and productivity improvement make it a justifiable investment, which will benefit the drug developer in the long run. Furthermore, the MCC process is especially beneficial for clinical stage biologics production when the manufacturing budgets are constrained.
Recognizing the financial burden associated with generating clinical products, CMC Biologics has become the first contract development and manufacturing organization (CDMO) that offers multi-column chromatography using BioSMB technology to help clients reduce clinical manufacturing cost through improved resin utilization. CMC Biologics’ technology vendor, Pall Life Sciences, is proactively interacting with the U.S. Food and Drug Administration (FDA) emerging-technology group on topics relating to BioSMB and continuous biomanufacturing. With enabling technology and expertise in place, CMC biologics is playing a pivotal role in helping the biopharma industry transform from batch processing to MCC-based manufacturing.
- Bisschops, Marc, Lynne Frick, Scott Fulton, Tom Ransohoff. “Single-Use, Continuous-Countercurrent, Multicolumn Chromatography.” BioProcess International. 1 June 2009. Web.
- Reichert, Janice M. “Antibodies to Watch in 2016.” mAbs 8.2 (2015): 197-204. Web.
- Biologic Therapeutic Drugs: Technologies and Global Markets. Rep. BCC Research. Jan. 2015. Web.
- Zydney, Andrew L. “Continuous Antibody Capture with Protein A Countercurrent Tangential Chromatography: A New Column-Free Approach for Antibody Purification.” Proc. of Integrated Continuous Biomanufacturing, Castelldefels. ECI. 21 Oct. 2013. Web.
- Hernandez, Randi. “Continuous Manufacturing: A Changing Processing Paradigm.” BioPharm International. 1 Apr. 2015. Web.
- Noel, Rob, Yuki Abe, Andrew Sinclair, Lynne Frick. “Process Time and Cost Savings Achieved through Automation and Islands of Integration in Existing Facilities.” Proc. of Integrated Continuous Biomanufacturing II, Berkeley. ECI. Web.
- Gantier, Rene, Karl Rogler, Xhorxhi Gjoka, Ron Noel, Alexander Martino, et al. “Simple Method Transfer from Batch to Continuous Chromatography Process to Fit Parameters to Business Needs.” Proc. of Integrated Continuous Biomanufacturing II, Berkeley. ECI. Nov. 2015. Web.
- Gjoka, Xhorxhi, Karl Rogler, Richard A. Martino, Rene Gantier, Mark Schofield. “A Straightforward Methodology for Designing Continuous Monoclonal Antibody Capture Multi-column Chromatography Processes.” Journal of Chromatography A 1416 (2015): 38-46. Web.
- Girard, Valérie, Nicolas-Julian Hilbold, Candy K.S. Ng, Laurence Pegon, Waël Chahim, et al.“Large-scale Monoclonal Antibody Purification by Continuous Chromatography, from Process Design to Scale-up.” Journal of Biotechnology 213 (2015): 65-73. Web.