The scientists in the downstream process development team have 10 years of experience on average. The team has demonstrated unparallel expertise and capability in purifying a variety of proteins and developing downstream processes to satisfy Zencore's clients.
• Rapid purification of protein in various formats
• Unit operations for downstream purification utilizing standardized platform
• Capable of developing and optimizing project specific downstream unit operations for non-mAb molecules
• Risk assessment of purification unit operation
• The scale-down model and process characterization of purification process unit operation
• Clarification process (depth filtration, centrifuge process)
• Development and optimization of chromatography process (affinity, ion exchange, hydrophobic interaction, mixed-mode chromatography)
• Development of virus inactivation (low pH incubation, solvent/detergent-reduction filtration process)
• Development of tangential flow filtration (TFF) process
• Technical transfer of DSP process to pilot scale
• Lifetime studies of chromatography resin
Customized service to provide optimal formulation development for our customers. Accelerated and long-term stability tests for temperature, oxidation, light exposure, and other factors are evaluated for stability according to country specific regulations.
Robust and comprehensive platform to support process development; including chromatography and optimization, microfiltration and ultrafiltration, and viral clearance.
A project is typically completed in 1.5 months on average.
Excellent process yields, with overall yield for mAb at about 70-80%. Process and product-related impurities are significantly reduced to meet quality attributes.
More than 250+ projects, including monoclonal antibodies, bi-specific antibodies, recombinant proteins, fusion proteins, and cytokines, have been completed.
Process development or characterization platforms customizable to meet each client's requirements. The team will fully evaluate the property of each project to help guide the process development. The critical quality attributes (CQA) and critical process parameters (CPP) will be defined after comprehensive risk assessment of the product and its process. Using DoE approach, we define the design space to determine the process parameters. The criticality of these process parameters will be verified using experimentation and risk assessment procedures. Our goal is to ensure the product quality attributes can always be met when the process is scaled-up.
Issue: A relative high level of aggregation was observed for a monoclonal antibody project during the upstream stage. Aggregate removal by conventional cation exchange chromatography was not successful. Furthermore, potential product self-aggregation was observed. Both issues resulted in low purity and low product yield (around 70%).
Strategy: Based on our experience, we tested suitable hydrophobic interaction resin, optimized the operating conditions for the hydrophobic resin, and developed a process hydrophobic interaction chromatography (HIC) with a flow-through mode, and obtained the optimal process parameters for aggregate removal.
Results: Aggregates was effectively removed with HIC in flow-through mode. Furthermore, higher loading capacity was achieved with HIC than that of cation exchange chromatography. Product purity was greater than 99% for the main peak as measured by SEC, with increased step yield up to 90%. In addition, HIC chromatography process in flow-through mode was convenient and economical for manufacturing.
Issue: Low purity was observed for a bispecific antibody project upstream. Various low molecular weight impurities, such as (HC + ScFv-Fc), and homodimer (ScFv-Fc) *2, were observed. The charge or hydrophobicity of these impurities are similar to that of the target molecule and makes it difficult to separate and remove using ion exchange, hydrophobic interaction or mixed-mode chromatography resins.
Strategy: Based on the understanding of the structure of the bi-specific antibody molecule, we took advantage of the affinity binding difference between target molecule and impurities toward the selected protein A resin. After optimization of the elution parameters, separation and removal of the (HC + ScFv-Fc) and homodimer (ScFv-Fc) *2 were achieved.
Results: The (HC + ScFv-Fc) and homodimer (ScFv-Fc) * 2 were successfully removed after the isocratic elution conditions for affinity chromatography were optimized. The purity increased from 70% to 90% as measured by NR-CE. Furthermore, the robustness and scalability of this process were confirmed in 200 L pilot production. This method enabled the removal of product-related impurities during the capture step of the downstream process, significantly reducing the impurity carryover to the subsequent polishing chromatography steps.
Issue: A recombinant protein project with a complicated downstream process. There was limited process development data available. The process parameters that impact the product quality was not available.
Strategy: First, a scale-down model of each process was established. A pre-study experiment to evaluate process performance was performed and data from this study and from prior development and production batches were analyzed. Risk assessment was carried out and DoE was used to perform the process characterization studies.
Results: The pre-study results were thoroughly analyzed, a reasonable risk assessment scoring system and a DoE protocol for process characterization study were established. Furthermore, the analysis of the pre-study contributed to the selection of process parameters. A series of experiments were successfully performed for this process characterization study. After these experiments and DOE data were analyzed, the design space of process parameters was determined and were finally verified using worst-case linkage experiments.
We improved our process understanding by analyzing the pre-study results, which contributed to a reasonable scoring of risk assessment and formulating a DoE protocol for process characterization study. Furthermore, the pre-study helped us select parameters and avoid deviating from the optimal conditions of characterization range, while accelerating the study progress. A series of experiments were successfully performed for this process characterization study. After the analysis of these experiments and DOE data, we determined the design space of process parameters, which was finally verified using worst-case linkage experiments.
