Integrated micro-scale protein a chromatography and Low pH viral inactivation unit operations on an automated platform

High throughput process development (HTPD) is established for time- and resource- efficient chromatographic process development. However, integration with non-chromatographic operations within a monoclonal antibody (mAb) purification train is less developed. An area of importance is the development of low pH viral inactivation (VI) that follows protein A chromatography. However, the lack of pH measurement devices at the micro-scale represents a barrier to implementation, which prevents integration with the surrounding unit operations, limiting overall process knowledge. This study is based upon the design and testing of a HTPD platform for integration of the protein A and low pH VI operations. This was achieved by using a design and simulation software before execution on an automated liquid handler. The operations were successfully translated to the micro-scale, as assessed by analysis of recoveries and molecular weight content. The integrated platform was then used as a tool to assess the effect of pH on HMWC during low pH hold. The laboratory-scale and micro-scale elution pools showed comparable HMWC across the pH range 3.2-3.7. The investigative power of the platform is highlighted by evaluating the resources required to conduct a hypothetical experiment. This results in lower resource demands and increased labor efficiency relative to the laboratory-scale. For example, the experiment can be conducted in 7 h, compared to 105 h, translating to labor hours, 3 h and 28 h for the micro-scale and laboratory-scale, respectively. This presents the opportunity for further integration beyond chromatographic operations within the purification sequence, to establish a fit-to-platform assessment tool for mAb process development.

In-line product quality monitoring during biopharmaceutical manufacturing using computational Raman spectroscopy

The implementation of process analytical technologies is positioned to play a critical role in advancing biopharmaceutical manufacturing by simultaneously resolving clinical, regulatory, and cost challenges. Raman spectroscopy is emerging as a key technology enabling in-line product quality monitoring, but laborious calibration and computational modeling efforts limit the widespread application of this promising technology. In this study, we demonstrate new capabilities for measuring product aggregation and fragmentation in real-time during a bioprocess intended for clinical manufacturing by applying hardware automation and machine learning data analysis methods. We reduced the effort needed to calibrate and validate multiple critical quality attribute models by integrating existing workflows into one robotic system. The increased data throughput resulting from this system allowed us to train calibration models that demonstrate accurate product quality measurements every 38 s. In-process analytics enable advanced process understanding in the short-term and will lead ultimately to controlled bioprocesses that can both safeguard and take necessary actions that guarantee consistent product quality.

Design and optimization of membrane chromatography for monoclonal antibody charge variant separation

The manufacturing scale implementation of membrane chromatography to purify monoclonal antibodies has gradually increased with the shift in industry focus towards flexible manufacturing and disposable technologies. Membrane chromatography are used to remove process-related impurities such as host cell proteins and DNA, leachates and endotoxins, with improved productivity and process flexibility. However, application of membrane chromatography to separate product-related variants such as charge variants has not gained major traction due to low binding capacity. The work reported here demonstrates that a holistic process development strategy to optimize static binding (pH and salt concentration) and dynamic process (membrane loading, flowrate, and gradient length) parameters can alleviate the capacity limitations. The study employed high throughput screening tools and scale-down membranes for intermediate and polishing purification of the model monoclonal antibody. An optimized process consisting of anion exchange and cation exchange membrane chromatography reduced the acidic variants present in Protein A eluate from 89.5 % to 19.2 % with 71 % recovery of the target protein. The membrane chromatography process also cleared host cell protein to below limit of detection with 6 to 30-fold higher membrane loading, compared to earlier reported values. The results confirm that membrane chromatography is effective in separating closely related product variants when supported by a well-defined process development strategy.

A framework for calculating orthogonal selectivities in multimodal systems directly from cell culture fluid

This paper presents a straightforward approach for measuring and quantifying orthogonality directly in complex cell culture fluids (CCFs) without the requirement for tracking the retention behaviors of large sets of proteins. Null-producing CCFs were fractionated using linear salt gradients at constant pH on a set of multimodal resins. Fractions were then analyzed by ultraperformance-reversed phase liquid chromatography and the resulting chromatograms provided host cell protein (HCP) "fingerprints." Using these fingerprints, an inner product vector-based approach was employed to quantify the degree of orthogonality between pairs of resins and operating conditions for these large HCP protein sets. To compare resin orthogonality behavior in different expression systems, the Chinese hamster ovary and Pichia pastoris null-producing CCFs were examined. Orthogonality in multimodal systems was found to strongly depend on the expression system and the HCPs being screened. We also identified several unexpected pairs of multimodal resins within the same family that exhibited significant orthogonality. Furthermore, "self-orthogonality" was evaluated between resins operated at different pHs, and important operating regimes were identified for maximizing orthogonal selectivities. The framework developed in this paper for calculating orthogonality without the need for labor-intensive HCP tracking has important implications for efficient process development and resin/operating condition selection for both monoclonal antibody (mAb) polishing steps and non-mAb processes. In addition, this study provides a tool to unlock the untapped potential of multimodal resins by aiding in their rational selection and incorporation. Finally, the orthogonality framework here can facilitate the development of sets of next-generation multimodal resins specifically designed to provide highly orthogonal and efficient separations tailored for different expression systems.

Rapid optimization of processes for the integrated purification of biopharmaceuticals

Straight‐through chromatography, wherein the eluate from one column passes directly onto another column without adjustment, is one strategy to integrate and intensify manufacturing processes for biologics. Development and optimization of such straight‐through chromatographic processes is a challenge, however. Conventional high‐throughput screening methods optimize each chromatographic step independently, with limited consideration for the connectivity of steps. Here, we demonstrate a method for the development and optimization of fully integrated, multi‐column processes for straight‐through purification. Selection of resins was performed using an in silico tool for the prediction of processes for straight‐through purification based on a one‐time characterization of host‐cell proteins combined with the chromatographic behavior of the product. A two‐step optimization was then conducted to determine the buffer conditions that maximized yield while minimizing process‐ and product‐related impurities. This optimization of buffer conditions included a series of range‐finding experiments on each individual column, similar to conventional screening, followed by the development of a statistical model for the fully integrated, multi‐column process using design of experiments. We used this methodology to develop and optimize integrated purification processes for a single‐domain antibody and a cytokine, obtaining yields of 88% and 86%, respectively, with process‐ and product‐related variants reduced to phase‐appropriate levels for nonclinical material.

High throughput screening of particle conditioning operations: II. Evaluation of scale-up heuristics with prokaryotically expressed polysaccharide vaccines

Multivalent polysaccharide conjugate vaccines are typically comprised of several different polysaccharides produced with distinct and complex production processes. Particle conditioning steps, such as precipitation and flocculation, may be used to aid the recovery and purification of such microbial vaccine products. An ultra scale-down approach to purify vaccine polysaccharides at the micro-scale would greatly enhance productivity, robustness, and speed the development of novel conjugate vaccines. In part one of this series, we described a modular and high throughput approach to develop particle conditioning processes (HTPC) for biologicals that combines flocculation, solids removal, and streamlined analytics. In this second part of the series, we applied HTPC to industrially relevant feedstreams comprised of capsular polysaccharides (CPS) from several bacterial species. The scalability of HTPC was evaluated between 0.8 mL and 13 L scales, with several different scaling methodologies examined. Clarification, polysaccharide yield, impurity clearance, and product quality achieved with HTPC were reproducible and comparable with larger scales. Particle sizing was the response with greatest sensitivity to differences in processing scale and enabled the identification of useful scaling rules. Scaling with constant impeller tip speed or power per volume in the impeller swept zone offered the most accurate scale up, with evidence that time integration of these values provided the optimal basis for scaling. The capability to develop a process at the micro-scale combined with evidence-based scaling metrics provide a significant advance for purification process development of vaccine processes. The USD system offers similar opportunities for HTPC of proteins and other complex biological molecules.

High throughput screening of particle conditioning operations: I. System design and method development

The biotech industry is under increasing pressure to decrease both time to market and development costs. Simultaneously, regulators are expecting increased process understanding. High throughput process development (HTPD) employs small volumes, parallel processing, and high throughput analytics to reduce development costs and speed the development of novel therapeutics. As such, HTPD is increasingly viewed as integral to improving developmental productivity and deepening process understanding. Particle conditioning steps such as precipitation and flocculation may be used to aid the recovery and purification of biological products. In this first part of two articles, we describe an ultra scale-down system (USD) for high throughput particle conditioning (HTPC) composed of off-the-shelf components. The apparatus is comprised of a temperature-controlled microplate with magnetically driven stirrers and integrated with a Tecan liquid handling robot. With this system, 96 individual reaction conditions can be evaluated in parallel, including downstream centrifugal clarification. A comprehensive suite of high throughput analytics enables measurement of product titer, product quality, impurity clearance, clarification efficiency, and particle characterization. HTPC at the 1 mL scale was evaluated with fermentation broth containing a vaccine polysaccharide. The response profile was compared with the Pilot-scale performance of a non-geometrically similar, 3 L reactor. An engineering characterization of the reactors and scale-up context examines theoretical considerations for comparing this USD system with larger scale stirred reactors. In the second paper, we will explore application of this system to industrially relevant vaccines and test different scale-up heuristics.

Optimization of random PEGylation reactions by means of high throughput screening

Since the first FDA approval of a PEGylated product in 1990, so called random PEGylation reactions are still used to increase the efficacy of biopharmaceuticals and represent the major technology of all approved PEG-modified drugs. However, the great influence of process parameters on PEGylation degree and the PEG-binding site results in a lack of reaction specificity which can have severe impact on the product profile. Consequently, reproducible and well characterized processes are essential to meet increasing regulative requirements resulting from the quality-by-design (QbD) initiative, especially for this kind of modification type. In this study we present a general approach which combines the simple chemistry of random PEGylation reactions with high throughput experimentation (HTE) to achieve a well-defined process. Robotic based batch experiments have been established in a 96-well plate format and were analyzed to investigate the influence of different PEGylation conditions for lysozyme as model protein. With common SEC analytics highly reproducible reaction kinetics were measured and a significant influence of PEG-excess, buffer pH, and reaction time could be investigated. Additional mono-PEG-lysozyme analytics showed the impact of varying buffer pH on the isoform distribution, which allowed us to identify optimal process parameters to get a maximum concentration of each isoform. Employing Micrococcus lysodeikticus based activity assays, PEG-lysozyme33 was identified to be the isoform with the highest residual activity, followed by PEG-lysozyme1 . Based on these results, a control space for a PEGylation reaction was defined with respect to an optimal overall volumetric activity of mono-PEG-lysozyme isoform mixtures.