The rapid identification of elution conditions for therapeutic antibodies from cation-exchange chromatography resins using high-throughput screening

Predicting purification process fit of monoclonal antibodies using machine learning

In early-stage development of therapeutic monoclonal antibodies, assessment of the viability and ease of their purification typically requires extensive experimentation. However, the work required for upstream protein expression and downstream purification development often conflicts with timeline pressures and material constraints, limiting the number of molecules and process conditions that can reasonably be assessed. Recently, high-throughput batch-binding screen data along with improved molecular descriptors have enabled development of robust quantitative structure-property relationship (QSPR) models that predict monoclonal antibody chromatographic binding behavior from the amino acid sequence. Here, we describe a QSPR strategy for in silico monoclonal antibody purification process fit assessment. Principal Component Analysis is applied to extract a one-dimensional basis for comparison of molecular chromatographic binding behavior from multi-dimensional high-throughput batch-binding screen data. Kernel Ridge Regression is used to predict the first principal component for new molecular sequences. This workflow is demonstrated with a set of 97 monoclonal antibodies for five chromatography resins in two salt types across a range of pH and salt concentrations. Model development benchmarks four descriptor sets from biophysical structural models and protein language models. The investigation illustrates the value QSPR models can provide to purification process fit assessment, and selection of resins and operating conditions from sequence alone.

Improving process robustness of cation exchange chromatography with cationic buffers for the reduction of aggregates

Cation exchange chromatography (CEX) is commonly used to separate aggregates from monomers during the industrial manufacturing of recombinant proteins. However, the similar isoelectric point of aggregates and monomers makes the stepwise elution CEX an unstable process. In this study, the performance robustness of sodium chloride stepwise elution and cationic buffers (histidine and Bis-Tris) stepwise elution were compared through Monte Carlo simulation. While all trials achieved acceptable levels of monomer purity, sodium chloride stepwise elution exhibited significant fluctuations in yield and elution volume due to variations in elution pH and eluent concentration. In contrast, histidine or Bis-Tris stepwise elution resulted in more consistent yield and elution volume across a broad operating range. The findings indicate that the dissociation behavior of cationic buffers mitigates the impact of pH variation on ion-exchange equilibrium and thus enables a more robust CEX process.

Defining operating regimes for partition coefficient measurements in protein chromatography

Partition coefficient (Kp) measurements are widely used in early- and late-stage downstream process development for biologics to screen binding, elution, and selectivity behaviors of chromatographic resins and conditions. Although the procedure for performing these experiments is straightforward, obtaining accurate Kp and selectivity measurements can be challenging with equilibrium concentrations often being below the limit of detection (LOD) of the analyzing device, and with no guarantee that the partition coefficient measurement will sample from the linear portion of the isotherm. This work develops a theoretical framework and corresponding software tool to inform the selection of phase ratio and protein loading such that partition coefficient experiments satisfy the following three criteria: i.) equilibrium concentrations are above the LOD, ii.) measurements are sampled from the linear portion of the isotherm, and iii.) partition coefficient values fall within a practically relevant range for utility in downstream process development. First, the concept of feasibility maps is developed which calculates equilibrium concentrations, separation factors, and Kp values on the KL vs. qm plane to define a feasibility regime based on a determined LOD, minimum-required separation factor, and maximum relevant Kp. These data are then superimposed onto a large database of historical isotherm data from the literature comprised of 6,310 Langmuir isotherm points over a broad range of chromatography resins and protein modalities, which are used to binarily determine whether these three criteria are met for a given phase ratio and resin loading. Feasibility maps are calculated as a function of phase ratio and resin loading to define an operating regime bounded by a top operating curve and bottom operating line on the resin loading vs. phase ratio plane. Further, closed-form expressions for these operating curves are derived, and the sensitivity of these curves to experimental parameters such as hold-up volume, intraparticle porosity, isotherm linearity criteria, and LOD is then evaluated and discussed in the context of relative error due to isotherm curvature. The impact of measuring Kp values inside vs. outside these operating regimes is assessed by experimentally measuring Kp vs. salt sampled from these two regions and predicting elution salt by mechanistic column modeling from these equilibrium data. These results indicate that Kp measurements sampled from outside the operating regime result in substantial error in model prediction compared to column experiments. Together, this work provides a theoretical foundation for obtaining accurate partition coefficient and selectivity measurements for informing robust experimental design. Further, it develops a software tool for calculating operating regimes, which can leverage in-house historical isotherm data to calculate custom operating regimes.

Integration of QSAR models with high throughput screening to accelerate the development of polishing chromatography unit operations

The development of robust polishing chromatographic processes is a critical step in downstream bioprocess development that can be time-consuming and resource intensive. Recently, there has been an increase in diverse protein constructs that are not amenable to platform approaches, increasing the need for novel processes to be developed for effective purification. High throughput screening (HTS) is an important tool to parse chromatographic design space and identify promising conditions to continue development. Despite its utility, HTS capabilities are challenged by tight development timelines, material scarcity, and an increasingly complex pipeline of biotherapeutics. Predictive modeling can augment HTS by leveraging historical screening data to rapidly explore and prioritize process design space, effectively expanding the range of conditions considered without the need for additional experimental screening. Here we present the development of a quantitative structure activity relationship (QSAR) model, trained from internal HTS data, that predicts protein partitioning as a function of resin and mobile phase conditions. The training dataset contains a diverse collection of screening data and has more than 8000 datapoints, covering 29 therapeutic proteins and 44 resins. The model encodes partitioning by building descriptors of the mobile phase, parameters that describe the resin, and biophysical properties of the protein. Overall, the regression model has an R2=0.92 and shows 95% and 93% classification accuracy for predicting elution and strong binding conditions, respectively. Here, we highlight the model predictiveness and describe how in silico screening can be used as a first step in the HTS workflow to reduce design space and accelerate process development.

Coupling high-throughput and modeling approaches to streamline early-stage process development for biologics

Platforms have long been implemented for downstream process development of monoclonal antibodies (mAbs) to streamline development and reduce timelines. These platforms are also increasingly being used for other complex biologics modalities. While development has traditionally been conducted at the lab bench scale in a sequential manner, automated miniaturized and parallelized approaches like RoboColumns and resin plates have also been implemented for chromatographic screening. Additionally, mechanistic modeling for chromatographic separations has also seen increased use for development applications. In this manuscript, we propose a workflow with elements of both high-throughput screening and modeling that provides a streamlined roadmap for early process development. The workflow utilizes automated resin plate screens to both narrow screening conditions and calibrate binding isotherm parameters. Mechanistic models are then used to characterize a robust range of conditions suitable for an early manufacturing process. Miniaturized RoboColumns then confirm the process space, thus completing the development without the use of any traditional lab-scale columns. Case studies demonstrate the utility of this workflow for both cation-exchange (CEX) and multimodal cation-exchange (MMCEX) processes. Process parameter sensitivities across process ranges for the models are compared with typical design-of-experiment (DOE) statistical models. The models are able to predict the mAb product as well as aggregate impurities. This workflow provides a practical method to enable increased process understanding while also reducing timeline and material requirements for development.

Partition coefficient screening - An effective approach for finding the best conditions for byproduct removal as demonstrated by a bispecific antibody purification case

In recombinant protein purification, differences in isoelectric point (pI)/surface charge and hydrophobicity between the product and byproducts generally form the basis for separation. For bispecific antibodies (bsAbs), in many cases the physicochemical difference between product and byproducts is subtle, making byproduct removal considerably challenging. In a previous report, with a bsAb case study, we showed that partition coefficient (Kp) screening for the product and byproducts under various conditions facilitated finding conditions under which effective separation of two difficult-to-remove byproducts was achieved by anion exchange (AEX) chromatography. In the current work, as a follow-up study, we demonstrated that the same approach enabled identification of conditions allowing equally good byproduct removal by mixed-mode chromatography with remarkably improved yield. Results from the current and previous studies proved that separation factor determination based on Kp screening for product and byproduct is an effective approach for finding conditions enabling efficient and maximum byproduct removal, especially in challenging cases.

High-throughput in silico workflow for optimization and characterization of multimodal chromatographic processes

While high-throughput (HT) experimentation and mechanistic modeling have long been employed in chromatographic process development, it remains unclear how these techniques should be used in concert within development workflows. In this work, a process development workflow based on HT experiments and mechanistic modeling was constructed. The integration of HT and modeling approaches offers improved workflow efficiency and speed. This high-throughput in silico (HT-IS) workflow was employed to develop a Capto MMC polishing step for mAb aggregate removal. High-throughput batch isotherm data was first generated over a range of mobile phase conditions and a suite of analytics were employed. Parameters for the extended steric mass action (SMA) isotherm were regressed for the multicomponent system. Model validation was performed using the extended SMA isotherm in concert with the general rate model of chromatography using the CADET modeling software. Here, step elution profiles were predicted for eight RoboColumn runs across a range of ionic strength, pH, and load density. Optimized processes were generated through minimization of a complex objective function based on key process metrics. Processes were evaluated at lab-scale using two feedstocks, differing in composition. The results confirmed that both processes obtained high monomer yield (>85%) and removed ∼ 50 % of aggregate species. Column simulations were then carried out to determine sensitivity to a wide range of process inputs. Elution buffer pH was found to be the most critical process parameter, followed by resin ionic capacity. Overall, this study demonstrated the utility of the HT-IS workflow for rapid process development and characterization.

Tailoring polishing steps for effective removal of polysorbate-degrading host cell proteins in antibody purification

Ensuring the quality and safety of biopharmaceutical products requires the effective separation of monoclonal antibodies (mAbs) from host cell proteins (HCPs). A major challenge in this field is the enzymatic hydrolysis of polysorbates (PS) in drug products. This study addresses this issue by investigating the removal of polysorbate-degrading HCPs during the polishing steps of downstream purification, an area where knowledge about individual HCP behavior is still limited. We investigated the separation of different mAb formats from four individual polysorbate degrading hydrolases (CES1F, CES2C, LPLA2, and PAF-AH) using cation exchange (CEX) and mixed-mode chromatography (MMC) polishing steps. Our research identified a key challenge: The similar elution behavior of mAbs and HCPs during chromatographic separation. To investigate this phenomenon, we performed high-throughput binding screenings for recombinant polysorbate degrading hydrolases and representative mAb candidates on CEX and MMC chromatography resins. We then employed a three-step strategy that also served as a scale-up process, optimizing separation conditions and leading to the successful removal of specific HCPs while maintaining high mAb recovery rates (>96%). This strategy involved the use of surface response models and miniature columns for screening, followed by validation on larger columns using a chromatography system. Our results highlight the critical role of the inherent properties of mAbs for successful separation from HCPs. These results underscore the need to tailor the purification process to leverage the slight differences in binding behavior and elution profiles between mAbs and specific HCPs. This approach lays the foundation for developing more effective strategies for overcoming the challenge of enzymatic polysorbate degradation, paving the way for improved quality and safety in biopharmaceutical products.

A batch screening technique for the calculation of chromatographic separability

This paper employs a high-throughput parallel batch (microtiter plate) adsorption screen with sequential salt step increases to rapidly generate protein elution profiles for multiple resins at different pHs using a protein library. The chromatographic set used in this work includes single mode, multimodal anion-exchange (MMA), and multimodal cation-exchange (MMC) resins. The protein library consists of proteins with isoelectric points ranging from 5.1 to 11.4 with varying hydrophobicities as determined by their retention on hydrophobic interaction chromatography. The batch sequential experiments are carried out using one protein at a time with a wide set of resins at multiple pH conditions, thus enabling simple microtiter plate detection. A mathematical formulation is then used to determine the first moment of the distributions from each chromatogram (sequential step elution) generated in the parallel batch experiments. Batch data first moments (expressed in salt concentration) are then compared to results obtained from column linear salt gradient elution, and the techniques are shown to be consistent. In addition, first moment data are used to calculate one-resin separability scores, which are a measure of a resin's ability, at a specified pH, to separate the entire set of proteins in the library from one another. Again, the results from the batch and column experiments are shown to be comparable. The first moment data sets were then employed to calculate the two-resin separability scores, which are a measure of the ability of two resins to synergistically separate the entire set of proteins in the library. Importantly, these results based on the two-resin separability performances derived from the batch and column experiments were again shown to be consistent. This approach for rapidly screening large numbers of chromatographic resins and mobile phase conditions for their elution behavior may prove useful for enabling the rapid discovery of new chromatographic ligands and resins.

Improved clearance of host cell protein impurities at the polishing purification step using multimodal chromatography

In biotherapeutic protein production, host cell proteins (HCPs) are one of the main process related impurities which must be cleared and controlled through downstream processing. In this paper, we studied a novel therapeutic protein molecule which had a high level of HCP co-purification throughout the downstream process. Here, we focused on the polishing purification step and developed an effective strategy for improving HCP clearance using multimodal chromatography (MMC) resin, Nuvia cPrime. A high throughput process development (HTPD) workflow was used to identify the resin and process conditions which could enable significant HCP clearance while maintaining acceptable product quality and process performance. HCP analysis of gradient elution fractions on multimodal chromatography found that HCPs eluted at the beginning of the gradient, at a lower salt concentration than the therapeutic protein. Based on these findings, a step elution process involving an intermediate low salt wash was developed to clear weak-binding HCPs, while retaining the therapeutic protein on the column. This strategy was highly effective and enabled 80 % reduction in total HCP content, including some problematic and difficult to remove candidates such as Peroxiredoxin-1, Serine protease HTRA1, Clusterin and Lipoprotein lipase.

Structural study of a light chain mispaired bispecific predicts mechanism of downstream separation

Bispecific antibodies expressed and assembled from a single upstream culture require the correct balance and pairing of four different heavy and light chains (HC and LC). The increased potential for chain-mispaired species challenges the downstream purification of this new format. While clearance of HC-mispaired species, including homodimers and half-antibodies, has been assessed, removal of LC mispairs requires a more stringent approach. Here, we report two case studies in which separation is achieved, as well as the structural basis of these separations: (A) In the first case, a main species with a positively charged patch in the correctly formed variable fragment (Fv) is disrupted when paired with the wrong LC. This LC-mispaired variant binds more weakly to a cation exchange resin and can be washed off in a chromatography step. (B) A second molecule whose LC mispair introduces a negative-charge patch and hydrophobic patch in close proximity, presenting increased binding to a multimodal anion exchange resin. This LC-mispaired variant can be retained on the column under conditions in which the bispecific is recovered. In both case studies, the molecular structural analysis by protein surface properties models correlated well with the chromatography experiments. The comprehensive interpretation of experimental and computational results has provided a better understanding of strategies and potential applications for predicting the downstream purification of complex molecules.

High throughput screening for rapid and reliable prediction of monovalent antibody binding behavior in flowthrough mode

Flowthrough (FT) anion exchange (AEX) chromatography is a widely used polishing step for the purification of monoclonal antibody (mAb) formats. To accelerate downstream process development, high throughput screening (HTS) tools have proven useful. In this study, the binding behavior of six monovalent mAbs (mvAbs) was investigated by HTS in batch binding mode on different AEX and mixed-mode resins at process-relevant pH and NaCl concentrations. The HTS entailed the evaluation of mvAb partition coefficients (Kp) and visualization of results in surface-response models. Interestingly, the HTS data grouped the mvAbs into either a strong-binding group or a weak-binding/FT group independent of theoretical Isoelectric point. Mapping the charged and hydrophobic patches by in silico protein surface property analyses revealed that the distribution of patches play a major role in predicting FT behavior. Importantly, the conditions identified by HTS were successfully verified by 1 mL on-column experiments. Finally, employing the optimal FT conditions (7-9 mS/cm and pH 7.0) at a mini-pilot scale (CV = 259 mL) resulted in 99% yield and a 21-23-fold reduction of host cell protein to <100 ppm, depending on the varying host cell protein (HCP) levels in the load. This work opens the possibility of using HTS in FT mode to accelerate downstream process development for mvAb candidates in early research.

Fully automated minicolumn chromatography

Miniaturized chromatography columns (minicolumns) operated by automated liquid handlers are an integral part of bioprocess purification development. However, these systems can be limited in both their efficiency and accessibility. Because the minicolumn chromatography operation itself is higher throughput, the lower throughput pre- and post-operation activities become the bottleneck of the workflow. Additionally, method writing and operation of the systems while varying multiple parameters, using a design of experiments approach for example, can be error-prone and resource intensive. Here, we have developed a fully automated minicolumn chromatography system to both address these bottlenecks and improve the accessibility of these systems by allowing users to enter chromatography-relevant information through a simplified user interface. Methods have been developed to automate buffer preparation and protein solution titration leveraging modeling and integrated pH probes with feedback control. Chromatogram generation and fraction pooling has additionally been automated to improve the efficiency of post-chromatography operations. We have also demonstrated the flexibility of the system through an example run where both bind-and-elute chromatography and flowthrough chromatography experiments were performed in parallel. Additionally, all methodology and parameters to operate the system have been shared. We hope this will help interested parties improve the efficiency and accessibility of their minicolumn chromatography systems.

A comprehensive assessment of the applicability of RoboColumn as a chromatography scale-down model for use in biopharmaceutical process validation

High-throughput process development has become a standard practice in the biopharmaceutical industry to enable time, cost, and material savings. In downstream biopharmaceutical process development, miniaturized, parallelized chromatography columns, known as RoboColumn, have become the standard for process development, as RoboColumn have shown generally comparable performance to bench and manufacturing scale columns. However, RoboColumn have yet to be widely implemented in process validation and characterization, where many multifactor experiments are typically executed, and there is a strong value proposition for performing high-throughput experiments. The hesitancy to utilize RoboColumn in process validation arises from scale differences that result in exacerbated peak broadening at RoboColumn scale relative to traditional bench or manufacturing scales. Thus, to support reliable application of RoboColumn in process validation, the present study provides a comprehensive investigation to understand how scale differences affect chromatographic performance by comparing RoboColumn, bench, and manufacturing scales using seven different production processes covering three different antibody formats, five different resin types, and three chromatographic modes of operation. RoboColumn chromatographic performance was compared at target and off-target conditions to emulate scale-down model qualification and multifactor studies, respectively. RoboColumn demonstrated good comparability at both target and off-target process conditions. To further demonstrate an understanding of comparability, a study was performed to show a rare case in which product quality offsets may occur as a result RoboColumn scale differences. By showing scale comparability and an understanding of potential offsets, this work demonstrates that RoboColumn can be used in any stage of process development, including process validation and characterization.

Purification of hydrophobic complex antibody formats using a moderately hydrophobic mixed mode cation exchange resin

Immunoglobulins of complex formats possess great potential for increased biopharmaceutical efficacy. However, challenges arise during their purification as the removal of numerous product-related impurities typically requires several expensive chromatographic steps. Additionally, many complex antibody formats have a high hydrophobicity which impairs the use of conventional mixed mode chromatography. In the present study, both of these challenges were addressed through the development of an innovative mixed mode resin with 2-amino-4methylpentanoic acid ligands that combines weak cation exchange with moderate hydrophobic interactions. Supported by high throughput partition coefficient screens for identification of preferable pH and salt concentration ranges in bind and elute mode, this mixed mode resin successfully demonstrated efficient impurity separation from an extremely hydrophobic bispecific antibody with a single unit operation. High purity (>97%) was obtained as a result of significant reduction of product-related impurities as well as process-related host cell proteins (>3 log scale), while maintaining satisfactory recovery (70%). This also supports that highly hydrophobic antibody formats can be efficiently purified using a resin with moderate hydrophobic characteristics. Studies involving additional antibodies possessing different formats and a wide range of hydrophobicity confirmed the broad applicability of the new resin. In view of its high selectivity and robust operating ranges, as well as the elimination of the need for an additional column step, the novel resin enables simplified downstream processing and economic manufacturing of complex antibody formats.

White paper on high-throughput process development for integrated continuous biomanufacturing

Continuous manufacturing is an indicator of a maturing industry, as can be seen by the example of the petrochemical industry. Patent expiry promotes a price competition between manufacturing companies, and more efficient and cheaper processes are needed to achieve lower production costs. Over the last decade, continuous biomanufacturing has had significant breakthroughs, with regulatory agencies encouraging the industry to implement this processing mode. Process development is resource and time consuming and, although it is increasingly becoming less expensive and faster through high-throughput process development (HTPD) implementation, reliable HTPD technology for integrated and continuous biomanufacturing is still lacking and is considered to be an emerging field. Therefore, this paper aims to illustrate the major gaps in HTPD and to discuss the major needs and possible solutions to achieve an end-to-end Integrated Continuous Biomanufacturing, as discussed in the context of the 2019 Integrated Continuous Biomanufacturing conference. The current HTPD state-of-the-art for several unit operations is discussed, as well as the emerging technologies which will expedite a shift to continuous biomanufacturing.

High throughput screening of fiber-based adsorbents for material and process development

There has been a growing interest in fibers and fiber-based adsorbents as alternative adsorbents for preparative chromatography. While the benefits of fiber-based adsorbents in terms of productivity have been highlighted in several recent studies, microscale tools that enable a fast characterization of these novel adsorbents, and an easy integration into process development workflows, are still lacking. In the present study an automated high-throughput screening (HTS) for fiber-based adsorbents was established on a robotic liquid handling station in 96 well filter plates. Two techniques - punching and weighing - were identified as techniques that enabled accurate and reproducible portioning of short-cut fiber-based adsorbents. The impact of several screening parameters such as phase ratio, shaking frequency, and incubation time were investigated and optimized for different types of fiber-based adsorbents. The data from the developed HTS correlated with data from packed fiber columns, and binding capacities from both scales matched closely. Subsequently, the developed HTS was utilized to optimize the hydrogel architecture of anion exchange (AEX) fiber-based adsorbent prototypes. A novel AEX fiber-based adsorbent was developed that compared favorably with existing resin and membrane adsorbents in terms of productivity and DNA binding capacity. In addition, the developed HTS was also successfully employed in order to identify step elution conditions for the purification of a monoclonal antibody from product- and process-related impurities with a cation exchange (CEX) fiber-based adsorbent. Trends from the HTS were found to be in good agreement with trends from lab scale column runs. The tool developed in this paper will enable a faster and more complete characterization of fiber-based adsorbents, easier tailoring of such adsorbents towards specific process applications, and an easier integration of such materials into processes. In comparison to previous lab scale experiments, material requirements are reduced by a factor of 3-40 and time requirements are reduced by a factor of 2-5.

Highland games: A benchmarking exercise in predicting biophysical and drug properties of monoclonal antibodies from amino acid sequences

Biopharmaceutical product and process development do not yet take advantage of predictive computational modeling to nearly the degree seen in industries based on smaller molecules. To assess and advance progress in this area, spirited coopetition (mutually beneficial collaboration between competitors) was successfully used to motivate industrial scientists to develop, share, and compare data and methods which would normally have remained confidential. The first "Highland Games" competition was held in conjunction with the October 2018 Recovery of Biological Products Conference in Ashville, NC, with the goal of benchmarking and assessment of the ability to predict development-related properties of six antibodies from their amino acid sequences alone. Predictions included purification-influencing properties such as isoelectric point and protein A elution pH, and biophysical properties such as stability and viscosity at very high concentrations. Essential contributions were made by a large variety of individuals, including companies which consented to provide antibody amino acid sequences and test materials, volunteers who undertook the preparation and experimental characterization of these materials, and prediction teams who attempted to predict antibody properties from sequence alone. Best practices were identified and shared, and areas in which the community excels at making predictions were identified, as well as areas presenting opportunities for considerable improvement. Predictions of isoelectric point and protein A elution pH were especially good with all-prediction average errors of 0.2 and 1.6 pH unit, respectively, while predictions of some other properties were notably less good. This manuscript presents the events, methods, and results of the competition, and can serve as a tutorial and as a reference for in-house benchmarking by others. Organizations vary in their policies concerning disclosure of methods, but most managements were very cooperative with the Highland Games exercise, and considerable insight into common and best practices is available from the contributed methods. The accumulated data set will serve as a benchmarking tool for further development of in silico prediction tools.

Recent Developments in Bioprocessing of Recombinant Proteins: Expression Hosts and Process Development

Infectious diseases, along with cancers, are among the main causes of death among humans worldwide. The production of therapeutic proteins for treating diseases at large scale for millions of individuals is one of the essential needs of mankind. Recent progress in the area of recombinant DNA technologies has paved the way to producing recombinant proteins that can be used as therapeutics, vaccines, and diagnostic reagents. Recombinant proteins for these applications are mainly produced using prokaryotic and eukaryotic expression host systems such as mammalian cells, bacteria, yeast, insect cells, and transgenic plants at laboratory scale as well as in large-scale settings. The development of efficient bioprocessing strategies is crucial for industrial production of recombinant proteins of therapeutic and prophylactic importance. Recently, advances have been made in the various areas of bioprocessing and are being utilized to develop effective processes for producing recombinant proteins. These include the use of high-throughput devices for effective bioprocess optimization and of disposable systems, continuous upstream processing, continuous chromatography, integrated continuous bioprocessing, Quality by Design, and process analytical technologies to achieve quality product with higher yield. This review summarizes recent developments in the bioprocessing of recombinant proteins, including in various expression systems, bioprocess development, and the upstream and downstream processing of recombinant proteins.

High-Throughput Process Development for Biopharmaceuticals

The ability to conduct multiple experiments in parallel significantly reduces the time that it takes to develop a manufacturing process for a biopharmaceutical. This is particularly significant before clinical entry, because process development and manufacturing are on the "critical path" for a drug candidate to enter clinical development. High-throughput process development (HTPD) methodologies can be similarly impactful during late-stage development, both for developing the final commercial process as well as for process characterization and scale-down validation activities that form a key component of the licensure filing package. This review examines the current state of the art for HTPD methodologies as they apply to cell culture, downstream purification, and analytical techniques. In addition, we provide a vision of how HTPD activities across all of these spaces can integrate to create a rapid process development engine that can accelerate biopharmaceutical drug development. Graphical Abstract.