Accelerating attribute-focused process and product development through the development and deployment of autonomous process analytical technology platform system.

Enabling real-time monitoring and control of the biomanufacturing processes through product quality insights continues to be an area of focus in the biopharmaceutical industry. The goal is to manufacture products with the desired quality attributes. To realize this rigorous attribute-focused Quality by Design approach, it is critical to support the development of processes that consistently deliver high-quality products and facilitate product commercialization. Time delays associated with offline analytical testing can limit the speed of process development. Thus, developing and deploying analytical technology is necessary to accelerate process development. In this study, we have developed the micro sequential injection process analyzer and the automatic assay preparation platform system. These innovations address the unmet need for an automatic, online, real-time sample acquisition and preparation platform system for in-process monitoring, control, and release of biopharmaceuticals. These systems can also be deployed in laboratory areas as an offline analytical system and on the manufacturing floor to enable rapid testing and release of products manufactured in a good manufacturing practice environment.

Engineering protein glycosylation in CHO cells to be highly similar to murine host cells.

Since 2015 more than 34 biosimilars have been approved by the FDA. This new era of biosimilar competition has stimulated renewed technology development focused on therapeutic protein or biologic manufacturing. One challenge in biosimilar development is the genetic differences in the host cell lines used to manufacture the biologics. For example, many biologics approved between 1994 and 2011 were expressed in murine NS0 and SP2/0 cell lines. Chinese Hamster ovary (CHO) cells, however, have since become the preferred hosts for production due to their increased productivity, ease of use, and stability. Differences between murine and hamster glycosylation have been identified in biologics produced using murine and CHO cells. In the case of monoclonal antibodies (mAbs), glycan structure can significantly affect critical antibody effector function, binding activity, stability, efficacy, and in vivo half-life. In an attempt to leverage the intrinsic advantages of the CHO expression system and match the reference biologic murine glycosylation, we engineered a CHO cell expressing an antibody that was originally produced in a murine cell line to produce murine-like glycans. Specifically, we overexpressed cytidine monophospho-N-acetylneuraminic acid hydroxylase (CMAH) and N-acetyllactosaminide alpha-1,3-galactosyltransferase (GGTA) to obtain glycans with N-glycolylneuraminic acid (Neu5Gc) and galactose-α-1,3-galactose (alpha gal). The resulting CHO cells were shown to produce mAbs with murine glycans, and they were then analyzed by the spectrum of analytical methods typically used to demonstrate analytical similarity as a part of demonstrating biosimilarity. This included high-resolution mass spectrometry, biochemical, as well as cell-based assays. Through selection and optimization in fed-batch cultures, two CHO cell clones were identified with similar growth and productivity criteria to the original cell line. They maintained stable production for 65 population doubling times while matching the glycosylation profile and function of the reference product expressed in murine cells. This study demonstrates the feasibility of engineering CHO cells to express mAbs with murine glycans to facilitate the development of biosimilars that are highly similar to marketed reference products expressed in murine cells. Furthermore, this technology can potentially reduce the residual uncertainty regarding biosimilarity, resulting in a higher probability of regulatory approval and potentially reduced costs and time in development.

Critical Aspects of pH Measurement for Bacteriostatic Water for Injection.

Bacteriostatic water for injection (bWFI) is a common diluent for parenteral pharmaceutical products. bWFI is sterile water for injection containing one or more suitable antimicrobial agents to suppress the growth of microbial contaminants. United States Pharmacopeia (USP) monograph describes bWFI with pH ranging from pH 4.5 to 7.0. Lacking buffering reagents, bWFI has very low ionic strength, no buffering capacity and is prone to sample contamination. These characteristics pose a challenge for accurate bWFI pH measurements which are characterized by long response times and noisy signals, resulting in inconsistent results. The challenging nature of bWFI pH measurement, however, is not fully recognized as pH is generally considered a routine analytical technique. Even with the addition of KCl to increase ionic strength as recommended by the USP bWFI monograph, variability in pH results is still observed without careful consideration of other critical measurement factors. To bring awareness to the challenges associated with bWFI pH measurement, we present a comprehensive characterization of the bWFI pH measurement process that includes an evaluation of probe suitability, measurement stabilization time, and pH meter settings. While these factors may be non-critical and sometimes overlooked when developing pH methods for buffered samples, they can have a significant impact on bWFI pH measurement. We present recommendations that can help reliable bWFI pH measurements for routine execution in a controlled environment. These recommendations also apply to other pharmaceutical solutions or water samples with low ionic strength.

Investigation of a failed DNA assay leads to identification of an unexpected contaminant in a commonly used chromatography buffer.

For mammalian cell-derived recombinant biotherapeutics, controlling host cell DNA levels below a threshold is a regulatory requirement to ensure patient safety. DNA removal during drug substance manufacture is accomplished by a series of chromatography-based purification steps and a qPCR-based analytical method is most used to measure DNA content in the purified drug substance to enable material disposition. While the qPCR approach is mature and its application to DNA measurement is widespread in the industry, it is susceptible to trace levels of process-related contaminants that are carried forward. In this study, we observed failures in spike recovery studies that are an integral component of the qPCR-based DNA testing, suggesting the presence of an inhibitory compound in the sample matrix. We generated hypotheses around the origin of the inhibitory compound and generated multiple sample matrices and deployed a suite of analytical techniques including Raman and NMR spectroscopy to determine the origin and identity of the inhibitory compound. The caustic wash step and depth filter extractables were ruled out as root causes after extensive experimentation and DNA testing. Subsequently, 2-(N-morpholino)ethanesulfonic acid (MES), a buffer used in the chromatography unit operations, was identified as the source of the contaminant. A 500-fold concentration followed by Raman and NMR spectroscopy analysis revealed the identity of the inhibitory compound as polyvinyl sulfone (PVS), an impurity that originates in the MES manufacturing process. We have implemented PVS concentration controls for incoming MES raw material, and our work highlights the need for rigor in raw material qualification and control.

State-of-the-art and emerging trends in analytical approaches to pharmaceutical-product commercialization.

The biopharmaceutical landscape continues to evolve rapidly, and associated modality complexity and the need to improve molecular understanding require concomitant advances in analytical approaches used to characterize and release the product. The Product Quality Attribute Assessment (PQAA) and Quality Target Product Profile (QTPP) frameworks help catalog and translate molecular understanding to process and product-design targets, thereby enabling reliable manufacturing of high-quality product. The analytical target profile forms the basis of identifying best-fit analytical methods for attribute measurement and continues to be successfully used to develop robust analytical methods for detailed product characterization as well as release and stability testing. Despite maturity across multiple testing platforms, advances continue to be made, several with the potential to alter testing paradigms. There is an increasing role for mass spectrometry beyond product characterization and into routine release testing as seen by the progress in multi-attribute methods and technologies, applications to aggregate measurement, the development of capillary zone electrophoresis (CZE) coupled with mass spectrometry (MS) and capillary isoelectric focusing (CIEF) with MS for measurement of glycans and charged species, respectively, and increased application to host cell protein measurement. Multitarget engaging multispecific modalities will drive advances in bioassay platforms and recent advances both in 1- and 2-D NMR approaches could make it the method of choice for characterizing higher-order structures. Additionally, rigorous understanding of raw material and container attributes is necessary to complement product understanding, and these collectively can enable robust supply of high-quality product to patients.

A high-resolution multi-attribute method for product characterization, process characterization, and quality control of therapeutic proteins.

During the manufacturing of therapeutic proteins, Critical Quality Attributes (CQAs) have been monitored by conventional methods, such as cation exchange chromatography (CEX), reduced capillary electrophoresis-sodium dodecyl sulfate (rCE-SDS), and 1,2-diamino-4,5-methylenedioxybenzene (DMB) labelling method. The conventional methods often generate individual peaks that contain multiple components, which may obscure the detection and the quantification of individual critical quality attributes (CQAs). Alternatively, Multi-Attribute Method (MAM) enables detection and quantification of specific CQAs. A high resolution MAM has been developed and qualified to replace several conventional methods in monitoring product quality attributes, such as oxidation, deamidation, clipping, and glycosylation. The qualified MAM was implemented in process characterization, as well as release and stability assays in quality control (QC). In combination with a design-of-experiments (DoE), the MAM method identified multivariate process parameter ranges that yield acceptable CQA level, which provides operational flexibility for manufacturing.

Enabling development, manufacturing, and regulatory approval of biotherapeutics through advances in mass spectrometry.

Rapid technological advances have significantly improved the capability, versatility, and robustness of mass spectrometers which has led to them playing a central role in the development, characterization, and regulatory filings of biopharmaceuticals. Their application spans the entire continuum of drug development, starting with discovery research through product development, characterization, and marketing authorization and continues well into product life cycle management. The scope of application extends beyond traditional protein characterization and includes elements like clone selection, cell culture physiology and bioprocess optimization, investigation support, and process analytical technology. More recently, advances in the MS-based multi-attribute method are enabling the introduction of MS in a cGMP environment for routine release and stability testing. While most applications of MS to date have been for monoclonal antibodies, the successes and learnings should translate to the characterization of next-gen biotherapeutics where modalities like multispecifics could be more prevalent. In this review, we describe the most significant advances in MS and correlate them to the broad spectrum of applications to biotherapeutic development. We anticipate rapid technological improvements to continue that will further accelerate widespread deployment of MS, thereby elevating our overall understanding of product quality and enabling attribute-focused product development.

Improving product quality and productivity of bispecific molecules through the application of continuous perfusion principles.

Bispecific protein scaffolds can be more complex than traditional monoclonal antibodies (MAbs) because two different sites/domains for epitope binding are needed. Because of this increased molecular complexity, bispecific molecules are difficult to express and can be more prone to physical and chemical degradation compared to MAbs, leading to higher levels of protein aggregates, clipped species, or modified residues in cell culture. In this study, we investigated cell culture performance for the production of three types of bispecific molecules developed at Amgen. In particular, we cultured a total of six CHO cell lines in both an approximately 12-day fed-batch process and an approximately 40-day high-density perfusion process. Harvested cell culture fluid from each process was purified and analyzed for product quality attributes including aggregate levels, clipped species, charge variants, individual amino acid modifications and host cell protein (HCP) content. Our studies showed that in average, the intensified perfusion process increased 15-fold the integrated viable cell density and the total harvested product (and fivefold the daily volumetric productivity) compared to fed-batch. Furthermore, bispecific product quality improved in perfusion culture (as analyzed in affinity-capture pools) with reduction in levels of aggregates (up to 72% decrease), clipped species (up to 75% decrease), acidic variants (up to 76% decrease), deamidated/isomerized species in complementarity-determining regions, and HCP (up to 84% decrease). In summary, the intensified perfusion process exhibited better productivity and product quality, highlighting the potential to use it as part of a continuous manufacturing process for bispecific scaffolds.

Methods for Estimating the Probability of Clonality in Cell Line Development.

Mammalian cell banks for biopharmaceutical production are usually derived from a single progenitor cell. Different methods to estimate the probability that the cell banks are clonally derived, or the probability of clonality (PoC), associated with various cloning workflows have been reported previously. In this review, a systematic analysis and comparison of the methods used to calculate the PoC are provided. As the single cell deposition and high-resolution imaging technologies continue to advance and the cloning workflow evolves, an aligned understanding and best practice on estimating the PoC is necessary to compare different cloning workflows adopted across the biopharmaceutical industry and it will help to accelerate regulatory acceptance.

Characterization of phenotypic and genotypic diversity in subclones derived from a clonal cell line.

Regulatory guidelines require the sponsors to provide assurance of clonality of the production cell line, and when such evidence is not available, additional studies are typically required to further ensure consistent long-term manufacturing of the product. One potential approach to provide such assurance of clonal derivation of a production cell line is to characterize subclones generated from the original cell line and assess their phenotypic and genotypic similarity with the hypothesis that cell lines derived from a clonal bank will share performance, productivity and product quality characteristics. In this study, a production cell line that was cloned by a validated FACS approach coupled with day 0 imaging for verification of single-cell deposition was subcloned using validated FACS and imaging methods. A total of 46 subclones were analyzed for growth, productivity, product quality, copy number, and integration site analysis. Significant diversity in cell growth, protein productivity, product quality attributes, and copy number was observed between the subclones, despite stability of the parent clone over time. The diversity in protein productivity and quality of the subclones were reproduced across time and production scales, suggesting that the resulting population post sub-cloning originating from a single cell is stable but with unique properties. Overall, this work demonstrates that the characteristics of isolated subclones are not predictive of a clonally derived parental clone. Consequently, the analysis of subclones may not be an effective approach to demonstrate clonal origin of a cell bank. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 34:613-623, 2018.

A Comparative Transcriptomics Workflow for Analyzing Microarray Data From CHO Cell Cultures.

Microarray-based comparative transcriptomics analysis is a powerful tool to understand therapeutic protein producing mammalian cell lines at the gene expression level. However, an integrated analysis workflow specifically designed for end-to-end analysis of microarray data for CHO cells, the most prevalent host for commercial recombinant protein production, is lacking. To address this gap, an automated data analysis workflow in R that leverages public domain analysis modules is developed to analyze microarray based gene expression data. In addition to testing the global transcriptome differences of CHO cells at different conditions, the workflow identifies differentially expressed genes and pathways with intuitive visualizations as the outputs. The utility of this automated workflow is demonstrated by comparing the transcriptomic profiles of recombinant protein expressing CHO cells with and without a temperature shift. Statistically significant differential expression at the gene, pathway, and global transcriptome levels are identified and visualized. An automated workflow like the one developed in this study will enable rapid translation of CHO culture microarray data into biologically relevant information for mechanism-driven cell line optimization and bioprocess development.

Accelerating patient access to novel biologics using stable pool-derived product for non-clinical studies and single clone-derived product for clinical studies.

Cell cloning and subsequent process development activities are on the critical path directly impacting the timeline for advancement of next generation therapies to patients with unmet medical needs. The use of stable cell pools for early stage material generation and process development activities is an enabling technology to reduce timelines. To successfully use stable pools during development, it is important that bioprocess performance and requisite product quality attributes be comparable to those observed from clonally derived cell lines. To better understand the relationship between pool and clone derived cell lines, we compared data across recent first in human (FIH) programs at Amgen including both mAb and Fc-fusion modalities. We compared expression and phenotypic stability, bioprocess performance, and product quality attributes between material derived from stable pools and clonally derived cells. Overall, our results indicated the feasibility of matching bioprocess performance and product quality attributes between stable pools and subsequently derived clones. These findings support the use of stable pools to accelerate the advancement of novel biologics to the clinic. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 33:1476-1482, 2017.

Evaluation of two public genome references for chinese hamster ovary cells in the context of rna-seq based gene expression analysis.

RNA-Seq is a powerful transcriptomics tool for mammalian cell culture process development. Successful RNA-Seq data analysis requires a high quality reference for read mapping and gene expression quantification. Currently, there are two public genome references for Chinese hamster ovary (CHO) cells, the predominant mammalian cell line in the biopharmaceutical industry. In this study, we compared these two references by analyzing 60 RNA-Seq samples from a variety of CHO cell culture conditions. Among the 20,891 common genes in both references, we observed that 31.5% have more than 7.1% quantification differences, implying gene definition differences in the two references. We propose a framework to quantify this difference using two metrics, Consistency and Stringency, which account for the average quantification difference between the two references over all samples, and the sample-specific effect on the quantification result, respectively. These two metrics can be used to identify potential genes for future gene model improvement and to understand the reliability of differentially expressed genes identified by RNA-Seq data analysis. Before a more comprehensive genome reference for CHO cells emerges, the strategy proposed in this study can enable more robust transcriptome analysis from CHO cell RNA-Seq data. Biotechnol. Bioeng. 2017;114: 1603-1613. © 2017 Wiley Periodicals, Inc.

An automated RNA-Seq analysis pipeline to identify and visualize differentially expressed genes and pathways in CHO cells.

Recent advances in RNA-Seq based comparative transcriptomics have opened up a unique opportunity to understand the mechanisms of different phenotypes in bioprocessing-related cell lines including Chinese hamster ovary (CHO) cells. However, simple and powerful tools are needed to translate large data sets into biologically relevant information that can be leveraged for genetic engineering and cell culture medium and process development. While tools exist to perform specific tasks associated with transcriptomics analysis, integrated end to end solutions that span the entire spectrum of raw data processing to visualization of gene expression changes on canonical pathways are rare. Additionally, these are not automated and require substantial user intervention. To address this gap, we have developed an automated RNA-Seq analysis pipeline in R which leverages the latest public domain statistical advances in transcriptomics data analysis. This pipeline reads RNA-Seq gene count data, identifies differentially expressed genes and differentially expressed pathways, and provides multiple intuitive visualizations as outputs. By using two publicly available CHO RNA-Seq datasets, we have demonstrated the utility of this pipeline. Subsequently, this pipeline was used to demonstrate transcriptomic similarity between laboratory- and pilot-scale bioreactors, helping make a case for the suitability of the lab-scale bioreactor as a scaled-down model. Automated end to end RNA-Seq data analysis approaches such as the one presented in this study will shorten the time required from acquiring sequencing data to biological interpretation of the results and can help accelerate the adoption of RNA-Seq analysis and thus mechanism-driven approaches for cell line and bioprocess optimization.

Elucidating the role of copper in CHO cell energy metabolism using (13)C metabolic flux analysis.

(13)C-metabolic flux analysis was used to understand copper deficiency-related restructuring of energy metabolism, which leads to excessive lactate production in recombinant protein-producing CHO cells. Stationary-phase labeling experiments with U-(13)C glucose were conducted on CHO cells grown under high and limiting copper in 3 L fed-batch bioreactors. The resultant labeling patterns of soluble metabolites were measured by GC-MS and used to estimate metabolic fluxes in the central carbon metabolism pathways using OpenFlux. Fluxes were evaluated 300 times from stoichiometrically feasible random guess values and their confidence intervals calculated by Monte Carlo simulations. Results from metabolic flux analysis exhibited significant carbon redistribution throughout the metabolic network in cells under Cu deficiency. Specifically, glycolytic fluxes increased (25%-79% relative to glucose uptake) whereas fluxes through the TCA and pentose phosphate pathway (PPP) were lower (15%-23% and 74%, respectively) compared with the Cu-containing condition. Furthermore, under Cu deficiency, 33% of the flux entering TCA via the pyruvate node was redirected to lactate and malate production. Based on these results, we hypothesize that Cu deficiency disrupts the electron transport chain causing ATP deficiency, redox imbalance, and oxidative stress, which in turn drive copper-deficient CHO cells to produce energy via aerobic glycolysis, which is associated with excessive lactate production, rather than the more efficient route of oxidative phosphorylation.

An evaluation of public genomic references for mapping RNA-Seq data from Chinese hamster ovary cells.

While RNA-Seq is increasingly used as the method of choice for transcriptome analysis of mammalian cell culture processes, no universal genomic reference for mapping RNA-Seq reads from CHO cells has been reported. In previous publications, de novo transcriptomes assembled using these RNA-Seq reads were subsequently used for mapping. Potential caveats with this approach include the incomplete coverage and the non-universal nature of the de novo assemblies, leading to challenges in comparing results across studies. In order to facilitate future RNA-Seq studies in CHO cells, we performed a comprehensive evaluation of four public genomic references for CHO cells hosted by the NCBI Reference Sequence Database (RefSeq), including two annotated genomes released in 2012 and 2014 and their accompanying transcriptomes. Each genome showed significantly higher mapped rates compared to its accompanying transcriptome. Furthermore, higher mapped rates in deep intra-genic regions, especially within exons, were observed for the more recent genome release (2014) compared to the older one (2012), indicating that the 2014 genome was the preeminent reference among the four. Sequential addition of human and mouse genomes increased the total mapped rate to 87.3 and 89.7%, respectively, from 73.5% using the 2014 Chinese hamster genome alone. Thus, the sequential combination of the 2014 RefSeq Chinese hamster genome, the Ensembl human genome (h38), and the Ensembl mouse genome (m38) was suggested as the most effective strategy for mapping RNA-Seq data from CHO cells.

Characterization of intrinsic variability in time-series metabolomic data of cultured mammalian cells.

In an attempt to rigorously characterize the intrinsic variability associated with Chinese Hamster Ovary (CHO) cell metabolomics studies, supernatant and intracellular samples taken at 5 time points from duplicate lab-scale bioreactors were analyzed using a combination of gas chromatography (GC)- and liquid chromatography-mass spectrometry (LC-MS) based metabolomics. The intrinsic variability between them was quantified using the relative standard deviation (RSD), and the median RSD was 9.4% and 12.4% for supernatant and intracellular samples, respectively. When exploring metabolic changes between lab- and pilot-scale bioreactors, a high number of metabolites (65-105) were significantly different when no corrections were made for this intrinsic variability. This distinction also extended to principal component and metabolic pathway analysis. However, when intrinsic variability was taken into account, the number of metabolite with significant changes reduced substantially (20-25) as did the separation in principal component and metabolic pathway analysis, suggesting a much smaller change in physiology across bioreactor scale. Our results also suggested the contribution of biological variability to the total variability across replicates (∼0.4%) was significantly lower than that from technical variability (∼9-12%). Our study highlights the need for understanding and accounting for intrinsic variability in CHO cell metabolomics studies. Failure to do so can result in incorrect biological interpretation of the observations which could ultimately lead to the identification of a suboptimal set of targets for genetic engineering or process development considerations.

Evaluating the impact of high Pluronic® F68 concentrations on antibody producing CHO cell lines.

Pluronic® F68 (P-F68) is an important component of chemically-defined cell culture medium because it protects cells from hydrodynamic and bubble-induced shear in the bioreactor. While P-F68 is typically used in cell culture medium at a concentration of 1 g/L (0.1%), higher concentrations can offer additional shear protection and have also been shown to be beneficial during cryopreservation. Recent industry experience with variability in P-F68-associated shear-protection has opened up the possibility of elevated P-F68 concentrations in cell culture media, a topic that has not been previously explored in the context of industrial cell culture processes. Recognizing this gap, we first evaluated the effect of 1-5 g/L P-F68 concentrations in shake flask cultures over ten 3-day passages for cell lines A and B. Increase in terminal cell density and cell size was seen over time at higher P-F68 concentrations but protein productivity was not impacted. Results from this preliminary screening study suggested no adverse impact of high P-F68 concentrations. Subsequently fed-batch bioreactor experiments were conducted at 1 and 5 g/L P-F68 concentrations with both cell lines where cell growth, viability, metabolism, and product quality were examined under process conditions reflective of a commercial process. Results from these bioreactor experiments confirmed findings from the preliminary screen and also indicated no impact of elevated P-F68 concentration on product quality. If additional shear protection is desired, either due to raw material variability, cell line sensitivity, or a high-shear cell culture process, our results suggest this can be accomplished by elevating the P-F68 concentration in the cell culture medium without impacting cell culture performance and product quality.