Cation exchange as a single polishing step for conjugated peptides.

Purification of peptides typically includes expensive reverse phase (RP) processes, which utilize high pressure and large volumes of solvent. For two conjugated peptides, chromatography process development targeted a low-pressure aqueous process that could achieve target product purities of ≥95%, comparable to purities seen with traditional RP. A high throughput screening approach of different modalities was used to identify binding and elution conditions on a cation exchange resin and small-scale columns were used in order to assess impurity removal and process yield. The parameters for load and gradient elution were optimized to increase product purity and process productivity with a wide operating window identified where high purity and productivity are achieved. Computational modeling was then used to validate experimental chromatography results and to gain insight on the effect of the chemical modifications on the surface properties of the two peptides. Both modeling and experimental data showed that with optimization, cation exchange could be utilized as a single polishing step for conjugated peptides. Similar purities were achieved as those seen with RP with up to double the productivity.

Multi attribute method implementation using a High Resolution Mass Spectrometry platform: From sample preparation to batch analysis.

Quality control of biopharmaceuticals such as monoclonal antibodies (mAbs) has been evolving and becoming more challenging as the requirements of the regulatory agencies increase due to the demanding complexity of products under evaluation. Mass Spectrometry (MS)-based methods such as the multi-attribute method (MAM) are being explored to achieve a deeper understanding of the attributes critical for the safety, efficacy, and quality of these products. MAM uses high mass accuracy/high-resolution MS data that enables the direct and simultaneous monitoring of relevant product quality attributes (PQAs, in particular, chemical modifications) in a single workflow, replacing several orthogonal methods, reducing time and costs associated with these assays. Here we describe a MAM implementation process using a QTOF high resolution platform. Method implementation was accomplished using NIST (National Institute for Standards and Technology) mAb reference material and an in-process mAb sample. PQAs as glycosylation profiles, methionine oxidation, tryptophan dioxidation, asparagine deamidation, pyro-Glu at N-terminal and glycation were monitored. Focusing on applications that require batch analysis and high-throughput, sample preparation and LC-MS parameters troubleshooting are discussed. This MAM workflow was successfully explored as reference analytical tool for comprehensive characterization of a downstream processing (DSP) polishing platform and for a comparability study following technology transfer between different laboratories.

Retrospective assessment of clonality of a legacy cell line by analytical subcloning of the master cell bank.

In recent years, assurance of clonality of the production cell line has been emphasized by health authorities during review of regulatory submissions. When insufficient assurance of clonality is provided, augmented control strategies may be required for a commercial production process. In this study, we conducted a retrospective assessment of clonality of a legacy cell line through analysis of subclones from the master cell bank (MCB). Twenty-four subclones were randomly selected based on a predetermined acceptance sampling plan. All these subclones share a conserved integration junction, thus providing a high level of assurance that the cell population in the MCB was derived from a single progenitor cell. However, Southern blot analysis indicates that at least four subpopulations possibly exist in the MCB. Additional characterization of these four subpopulations demonstrated that the resulting changes in product quality attributes of some subclones are not related to the genetic heterogeneity observed in Southern blot hybridization. Furthermore, process consistency, process comparability, and analytical comparability have been demonstrated in batches produced across varying manufacturing processes, scales, facilities, cell banks, and cell ages. Finally, process and product consistency together with a high level of assurance of clonal origin of the MCB helped clear the hurdle for regulatory approval without requirement of additional control strategies.

Pilot-scale demonstration of an end-to-end integrated and continuous biomanufacturing process.

There has been increasing momentum recently in the biopharmaceutical industry to transition from traditional batch processes to next-generation integrated and continuous biomanufacturing. This transition from batch to continuous is expected to offer several advantages which, taken together, could significantly improve access to biologics drugs for patients. Despite this recent momentum, there has not been a commercial implementation of a continuous bioprocess reported in the literature. In this study, we describe a successful pilot-scale proof-of-concept demonstration of an end-to-end integrated and continuous bioprocess for the production of a monoclonal antibody (mAb). This process incorporated all of the key unit operations found in a typical mAb production process, including the final steps of virus removal filtration, ultrafiltration, diafiltration, and formulation. The end-to-end integrated process was operated for a total of 25 days and produced a total of 4.9 kg (200 g/day or 2 g/L BRX/day) of the drug substance from a 100-L perfusion bioreactor (BRX) with acceptable product quality and minimal operator intervention. This successful proof-of-concept demonstrates that end-to-end integrated continuous bioprocessing is achievable with current technologies and represents an important step toward the realization of a commercial integrated and continuous bioprocessing process.

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.

Accurate and Rapid Protein Concentration Measurement of In-Process, High Concentration Protein Pools.

Protein concentration is a critical product quality attribute and required for any therapeutic protein. Many commercial and investigational new biologics are now formulated at high concentrations (>100 mg/ml) to achieve successful subcutaneous administration. Assaying protein concentration in high concentration formulations poses a challenge, as traditional absorption spectroscopy and UPLC/HPLC (ultra/high performance liquid chromatography) assays cannot accurately measure such high concentrations without further solution manipulation. However, recent advances in UV/vis technology have led to the creation of instruments that measure samples at relatively short (<1 cm) path lengths, which would allow them to accurately measure high concentration protein samples in accordance with Beer Lambert Law principles. In this research, samples of five different proteins at concentrations ranging from 0.15 to 242 mg/ml (corresponding to OD280 vales of 0.15-315 AU) were measured on two different instruments employing different techniques of low path length UV/vis measurements. In order for the techniques to meet MSD's acceptance criteria for release assays, measurements were required to be accurate to within 10% of a reference measurement (performed on a traditional UV/vis spectrophotometer) and to be precise within 5% CV. The results show that using a technique known as slope spectroscopy, it is possible to measure OD280 from 0.5 to 315 AU with <7% error relative to the reference measurement. If instead measurements are taken using an instrument utilizing a single, small path length, it is possible to measure absorbances from 0.2 to ~75 AU with <7% error. This article concludes that the slope spectroscopy technique performed within the acceptance criteria across the full range of measured absorbances and that the single, short path length measurement performed within the acceptance criteria up to 75 AU.

Quantitative assessment of environmental impact of biologics manufacturing using process mass intensity analysis.

Process mass intensity (PMI) is a benchmarking metric to evaluate the efficiency of a manufacturing process, which is indicative of the environmental impact of the process. Although this metric is commonly applied for small molecule manufacturing processes, it is less commonly applied to biologics. In this study, an Excel based tool developed by the ACS GCI Pharmaceutical Roundtable was used to calculate PMI of different manufacturing processes for a monoclonal antibody (mAb). For the upstream process, three different versions were compared: fed-batch, fed-batch with N-1 perfusion, and perfusion in the N-stage bioreactor. For each upstream process version, an appropriate downstream operational mode was evaluated from the following: a column chromatography process utilizing Protein A and anion exchange (AEX) resin, a Protein A column and an AEX membrane, and a three-column periodic counter-current (3C PCC) chromatography process for Protein A and an AEX membrane. The impact of these different process variations on PMI was evaluated. Of all the process inputs, water contributes about 92-94% of the overall PMI. Additionally, the upstream processes and the chromatography steps account for 32-47 and 34-54% of the overall PMI, respectively. Sensitivity analysis was performed to identify opportunities for further reducing PMI. These data indicate that a semicontinuous manufacturing process (perfusion, 3C PCC, and AEX membrane) is the most efficient process, resulting in a 23% reduction of PMI when compared with the fed batch and two-column chromatography process. Together, PMI can be used to guide the development of efficient and environmentally sustainable mAb manufacturing processes. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 34:1566-1573, 2018.

Multi-angle light scattering as a process analytical technology measuring real-time molecular weight for downstream process control.

For many protein therapeutics including monoclonal antibodies, aggregate removal process can be complex and challenging. We evaluated two different process analytical technology (PAT) applications that couple a purification unit performing preparative hydrophobic interaction chromatography (HIC) to a multi-angle light scattering (MALS) system. Using first principle measurements, the MALS detector calculates weight-average molar mass, Mw and can control aggregate levels in purification. The first application uses an in-line MALS to send start/stop fractionation trigger signals directly to the purification unit when preset Mw criteria are met or unmet. This occurs in real-time and eliminates the need for analysis after purification. The second application uses on-line ultra-high performance size-exclusion liquid chromatography to sample from the purification stream, separating the mAb species and confirming their Mw using a µMALS detector. The percent dimer (1.5%) determined by the on-line method is in agreement with the data from the in-line application (Mw increase of approximately 2750 Da). The novel HIC-MALS systems demonstrated here can be used as a powerful tool for real-time aggregate monitoring and control during biologics purification enabling future real time release of biotherapeutics.

Definition and dynamic control of a continuous chromatography process independent of cell culture titer and impurities.

Advances in cell culture technology have enabled the production of antibody titers upwards of 30g/L. These highly productive cell culture systems can potentially lead to productivity bottlenecks in downstream purification due to lower column loadings, especially in the primary capture chromatography step. Alternative chromatography solutions to help remedy this bottleneck include the utilization of continuous processing systems such as periodic counter-current chromatography (PCC). Recent studies have provided methods to optimize and improve the design of PCC for cell culture titers up to about 3g/L. This paper defines a continuous loading strategy for PCC that is independent of cell culture background and encompasses cell culture titers up to about 31g/L. Initial experimentation showed a challenge with determining a difference in change in UV280nm signal (ie. ΔUV) between cell culture feed and monoclonal antibody (mAb) concentration. Further investigation revealed UV280nm absorbance of the cell culture feedstock without antibody was outside of the linear range of detection for a given cell pathlength. Additional experimentation showed the difference in ΔUV for various cell culture feeds can be either theoretically predicted by Beer's Law given a known absorbance of the media background and impurities or experimentally determined using various UV280nm cell pathlengths. Based on these results, a 0.35mm pathlength at UV280nm was chosen for dynamic control to overcome the background signal. The pore diffusion model showed good agreement with the experimental frontal analysis data, which resulted in definition of a ΔUV setpoint range between 20 and 70% for 3C-PCC experiments. Product quality of the elution pools was acceptable between various cell culture feeds and titers up to about 41g/L. Results indicated the following ΔUV setpoints to achieve robust dynamic control and maintain 3C-PCC yield: ∼20-45% for titers greater than 10g/L depending on UV absorbance of the HCCF and ∼45-70% for titers of up to 10g/L independent of UV absorbance of the HCCF. The strategy and results presented in this paper show column loading in a continuous chromatography step can be dynamically controlled independent of the cell culture feedstock and titer, and allow for enhanced process control built into the downstream continuous operations.

Impact of Freeze/Thaw Process on Drug Substance Storage of Therapeutics.

The storage of drug substance at subzero temperatures mitigates potential risks associated with liquid storage, such as degradation and shipping stress, making it the best solution for long-term storage. However, slower (generally uncontrolled) rates of freezing and thawing of drug substance in conventional large storage containers (>2L) can lead to greater cryoconcentration (exclusion of solute molecules) resulting in zones of higher protein and excipient concentrations and changes to the desired formulation pH and excipient concentration. These conditions can negatively impact product quality, thus changing the target product profile. Freeze/thaw studies can provide valuable knowledge on the molecule even when performed from an early formulation image. This study attempts to provide guidance and strategy for planning of drug substance freeze and thaw studies in early development using a scale-down model, evaluating the impact of the (1) freeze/thaw rate, (2) mode of freezing, (3) drug substance container, (4) drug substance concentration, and (5) formulation on the drug substance product quality. Data presented in this study showed no impact on drug substance product quality after undergoing the typical one freeze/thaw cycle process for the variables evaluated. These findings suggest that a qualified scale-down model is not required for early phases of process development and that existing small-scale models can be used for drug substance storage development studies. Based on our experience, a workflow is suggested with minimal experimental design to reduce the material requirement by >70% at early stages of product development to reduce constraints.

High throughput chromatography strategies for potential use in the formal process characterization of a monoclonal antibody.

High throughput experimental strategies are central to the rapid optimization of biologics purification processes. In this work, we extend common high throughput technologies towards the characterization of a multi-column chromatography process for a monoclonal antibody (mAb). Scale-down strategies were first evaluated by comparing breakthrough, retention, and performance (yields and clearance of aggregates and host cell protein) across miniature and lab scale columns. The process operating space was then evaluated using several integrated formats, with batch experimentation to define process testing ranges, miniature columns to evaluate the operating space, and comparison to traditional scale columns to establish scale-up correlations and verify the determined operating space. When compared to an independent characterization study at traditional lab column scale, the high throughput approach identified the same control parameters and similar process sensitivity. Importantly, the high throughput approach significantly decreased time and material needs while improving prediction robustness. Miniature columns and manufacturing scale centerpoint data comparisons support the validity of this approach, making the high throughput strategy an attractive and appropriate scale-down tool for the formal characterization of biotherapeutic processes in the future if regulatory acceptance of the miniature column data can be achieved. Biotechnol. Bioeng. 2016;113: 1273-1283. © 2015 Wiley Periodicals, Inc.

Prediction of viral filtration performance of monoclonal antibodies based on biophysical properties of feed.

Controlling viral contamination is an important issue in the process development of monoclonal antibodies (MAbs) produced from mammalian cell lines. Virus filtration (VF) has been demonstrated to be a robust and effective clearance step which can provide ≥4 logs of reduction via size exclusion. The minimization of VF area by increasing flux and filter loading is critical to achieving cost targets as VFs are single use and often represent up to 10% of total purification costs. The research presented in this publication describes a development strategy focused on biophysical attributes of product streams that are directly applicable to VF process performance. This article summarizes a case study where biophysical tools (high-pressure size exclusion chromatography, dynamic light scattering, and absolute size exclusion chromatography) were applied to a specific MAb program to illustrate how changes in feed composition (pH, sodium chloride concentration, and buffer salt type) can change biophysical properties which correlate with VF performance. The approach was subsequently refined and expanded over the course of development of three MAbs where performance metrics (i.e., loading and flux) were evaluated for two specific virus filters (Viresolve Pro and Planova 20N) during both unspiked control runs and virus clearance experiments. The analyses of feed attributes can be applied to a decision tree to guide the recommendation of a VF filter and operating conditions for use in future MAb program development. The understanding of the biophysical properties of the feed can be correlated to virus filter performance to significantly reduce the mass of product, time, and costs associated with virus filter step development.

Purification of proteins using displacement chromatography.

Displacement chromatography has several advantages over the nonlinear elution technique, as well as the linear elution mode, such as the recovery of purified components at high concentrations, less tailing during elution, high throughput and high resolution. Displacer affinity and its utilization are the critical components of displacement chromatography. Particularly, the nonspecific interactions between the displacer and the stationary phase can be exploited to generate high affinity displacers. This chapter will discuss the design and execution of displacer selection and implementation in a separation specifically focusing on its utilization in ion exchange chromatography.

Maximizing productivity of chromatography steps for purification of monoclonal antibodies.

The large scale production of monoclonal antibodies presents a challenge to design efficient and cost effective downstream purification processes. We explored a two stage resin screening approach to identify the best candidates to be utilized for the platform purification of monoclonal antibodies. The study focused on commercially available affinity resins including Protein A, mimetic and mixed-mode interaction resins as well as ion exchangers used in polishing steps. An initial screening using pure proteins was followed by a final screening where selected resins were utilized for the purification of MAbs in complex mixtures. Initial screenings aimed to measure the theoretical upper limit for dynamic binding capacity (DBC) at 1% breakthrough and productivity. We confirmed that DBC of affinity, mimetic and mixed-mode resins was a strong function of the linear velocity used for loading. Productivities >27 g/(L-h), were obtained for rProtein A FF, Mabselect and Prosep rA Ultra at 2 min residence time. For the cation exchangers, we identified UNOsphere S and Fractogel SO(3) as the best candidates for our purification based on DBC. For anion exchangers operated in flowthrough mode, Q Sepharose XL and UNOsphere Q were selected from the initial screening based on DBC and resolution of IgG from BSA. Finally, a three step purification scheme was implemented using the selected affinity and ion exchangers for the purification of IgG from complex feedstocks. We found that Mabselect followed by UNOsphere Q and UNOsphere S provided the best purification scheme for our applications based on productivity.

Parallel screening of selective and high-affinity displacers for proteins in ion-exchange systems.

This paper employs a parallel batch screening technique for the identification of both selective and high-affinity displacers for a model binary mixture of proteins in a cation-exchange system. A variety of molecules were screened as possible displacers for the proteins ribonuclease A (RNAseA) and alpha-chymotrypsinogen A (alpha-chyA) on high performance Sepharose SP. The batch screening data for each protein was used to select leads for selective and high-affinity displacers and column experiments were carried out to evaluate the performance of the selected leads. The data from the batch displacements was also employed to generate quantitative structure-efficacy relationship (QSER) models based on a support vector machine regression approach. The resulting models had high correlation coefficients and were able to predict the behaviour of molecules not included in the training set. The descriptors selected in the QSER models for both proteins were examined to provide insights into factors influencing displacer selectivity in ion-exchange systems. The results presented in this paper demonstrate that this parallel batch screening-QSER approach can be employed for the identification of selective and high-affinity displacers for protein mixtures.

Identification of chemically selective displacers using parallel batch screening experiments and quantitative structure efficacy relationship models.

Parallel batch screening experiments were carried out to examine how displacer chemistry and salt counterions affect the selectivity of batch protein displacements in anion exchange chromatographic systems. The results indicate that both salt type and displacer chemistry can have a significant impact on the amount of protein displaced. Importantly, the results indicate that, by changing the displacer, salt counterion, or both, one can induce significant selectivity changes in the relative displacement of two model proteins. This indicates that highly selective separations can be developed in ion exchange systems by the appropriate selection of displacer chemistry and salt counterion. The experimental batch screening data were also used in conjunction with various molecular descriptors to generate quantitative structure efficacy relationship (QSER) models based on a support vector machine feature selection and regression tool. The models resulted in good correlations and successful predictions for an external test set of displacers. A star plot approach was shown to be a powerful tool to aid in the interpretation of the QSER models. These results indicate that this modeling approach can be employed for the a priori prediction of displacer efficacy as well as for providing insight into displacer design and the selection of proper mobile-phase conditions for highly selective separations.

Prediction of the effect of mobile-phase salt type on protein retention and selectivity in anion exchange systems.

This study examines the effect of different salt types on protein retention and selectivity in anion exchange systems. Particularly, linear retention data for various proteins were obtained on two structurally different anion exchange stationary-phase materials in the presence of three salts with different counterions. The data indicated that the effects are, for the most part, nonspecific, although various specific effects could also be observed. Quantitative structure retention relationship (QSRR) models based on support vector machine feature selection and regression models were developed using the experimental chromatographic data in conjunction with various molecular descriptors computed from protein crystal structure geometries. Star plots for each descriptor used in the final model were generated to aid in interpretation. The resulting QSRR models were predictive, with cross-validated r2 values of 0.9445, 0.9676, and 0.8897 for Source 15Q and 0.9561, 0.9876, and 0.9760 for Q Sepharose resins in the presence of three different salts. The predictive power of these models was validated using a set of test proteins that were not used in the generation of these models. Interpretation of the models revealed that particular trends for proteins and salts could be captured using QSRR techniques.

Prediction of protein retention times in anion-exchange chromatography systems using support vector regression.

Quantitative Structure-Retention Relationship (QSRR) models are developed for the prediction of protein retention times in anion-exchange chromatography systems. Topological, subdivided surface area, and TAE (Transferable Atom Equivalent) electron-density-based descriptors are computed directly for a set of proteins using molecular connectivity patterns and crystal structure geometries. A novel algorithm based on Support Vector Machine (SVM) regression has been employed to obtain predictive QSRR models using a two-step computational strategy. In the first step, a sparse linear SVM was utilized as a feature selection procedure to remove irrelevant or redundant information. Subsequently, the selected features were used to produce an ensemble of nonlinear SVM regression models that were combined using bootstrap aggregation (bagging) techniques, where various combinations of training and validation data sets were selected from the pool of available data. A visualization scheme (star plots) was used to display the relative importance of each selected descriptor in the final set of "bagged" models. Once these predictive models have been validated, they can be used as an automated prediction tool for virtual high-throughput screening (VHTS).

Stationary phase effects on the dynamic affinity of low-molecular-mass displacers.

In this paper, the selectivity of a variety of cation-exchange stationary phases was investigated using a homologous series of displacer molecules based on pentaerythritol. These displacers were derived from pentaerythritol and contained either four trimethyl ammonium groups [pentaerythrityl-(trimethylammonium chloride)4, PE(TMA)4], benzene rings [pentaerythrityl-(benzyl dimethylammonium chloride)4, PE(DMABzCl)4], heptyl groups [pentaerythrityl-(heptyl dimethylammonium iodide)4, PE(DMAHepI)4] or cyclohexyl groups [pentaerythrityl-(cyclohexyl dimethylammonium iodide)4, PE(DMACyI)4]. This series enabled us to probe the secondary interactions that can play a role in the affinity of low-molecular-mass displacers for different stationary phases. The relative affinities of these displacers were examined using a displacer ranking plot based on the steric mass action (SMA) isotherm model. While hydrophobicity and aromaticity played important roles in generating the affinity to the hydrophilized polystyrene-divinylbenzene (Source 15S) and polymethacrylate-based (Toyopearl 650M) resins, these secondary interactions had a minimal impact on the selectivity in agarose resins coated with dextran (SP Sepharose XL), "gel in a shell" (S Ceramic HyperD F), and monolithic (Bio-Rad Uno S6) cation-exchange materials. Further, the results with a tentacular stationary phase (Fractogel EMD) suggest that the alkyl chains on PE(DMAHepI)4 play an important role in increasing the affinity, possibly because of strong interactions between the alkyl moiety and the polymer matrix as well as between the charged groups and the polyelectrolyte tentacles. The results of this study provide insight into the design of high affinity, low-molecular-mass displacers for different cation-exchange stationary phase materials.