Optimization of a mAb production process with regard to robustness and product quality using quality by design principles

Quality by Design principles are well described and widely used in biopharmaceutical industry. The characterization of a monoclonal antibody (mAb) production process is crucial for novel process development and control. Yet, the application throughout the entire upstream process was rarely demonstrated. Following previously published research, this study marks the second step toward a complete process characterization and is focused on the effect of critical process parameters on the antibody production efficiency and quality of the process. In order to conduct the complex Design of Experiments approach with optimal control and comparability, the ambr®15 micro bioreactor platform was used. Investigated parameters included the pH and dissolved oxygen set points, the initial viable cell density (iVCD) as well as the N‐1 duration. Various quality attributes (e.g., growth rate, viability, mAb titer, and peak proportion) were monitored and analyzed using multivariate data analysis to evaluate the parameter effects. The pH set point and the initial VCD were identified as key process parameters with strong influence on the cell growth as well as the mAb production and its proportion to the total protein concentration. For optimization and improvement in robustness of these quality attributes the pH must be increased to 7.2, while the iVCD must be lowered to 0.2 × 10⁶ cells/mL. Based on the defined design space, additional experiments verified the results and confirmed the intact bioactivity of the antibody. Thereby, process control strategies could be tuned toward high cell maintenance and mAb production, which enable optimal downstream processing.     

A Quadrupole Dalton-based multi-attribute method for product characterization,process development,and quality control of therapeutic proteins

During manufacturing and storage process, therapeutic proteins are subject to various post-translational modifications (PTMs), such as isomerization, deamidation, oxidation, disulfide bond modifications and glycosylation. Certain PTMs may affect bioactivity, stability or pharmacokinetics and pharmacodynamics profile and are therefore classified as potential critical quality attributes (pCQAs). Identifying, monitoring and controlling these PTMs are usually key elements of the Quality by Design (QbD) approach. Traditionally, multiple analytical methods are utilized for these purposes, which is time consuming and costly. In recent years, multi-attribute monitoring methods have been developed in the biopharmaceutical industry. However, these methods combine high-end mass spectrometry with complicated data analysis software, which could pose difficulty when implementing in a quality control (QC) environment. Here we report a multi-attribute method (MAM) using a Quadrupole Dalton (QDa) mass detector to selectively monitor and quantitate PTMs in a therapeutic monoclonal antibody. The result output from the QDa-based MAM is straightforward and automatic. Evaluation results indicate this method provides comparable results to the traditional assays. To ensure future application in the QC environment, this method was qualified according to the International Conference on Harmonization (ICH) guideline and applied in the characterization of drug substance and stability samples. The QDa-based MAM is shown to be an extremely useful tool for product and process characterization studies that facilitates facile understanding of process impact on multiple quality attributes, while being QC friendly and cost-effective.     

Automated calibration and in-line measurement of product quality during therapeutic monoclonal antibody purification using Raman spectroscopy

Current manufacturing and development processes for therapeutic monoclonal antibodies demand increasing volumes of analytical testing for both real-time process controls and high-throughput process development. The feasibility of using Raman spectroscopy as an in-line product quality measuring tool has been recently demonstrated and promises to relieve this analytical bottleneck. Here, we resolve time-consuming calibration process that requires fractionation and preparative experiments covering variations of product quality attributes (PQAs) by engineering an automation system capable of collecting Raman spectra on the order of hundreds of calibration points from two to three stock seed solutions differing in protein concentration and aggregate level using controlled mixing. We used this automated system to calibrate multi-PQA models that accurately measured product concentration and aggregation every 9.3 s using an in-line flow-cell. We demonstrate the application of a nonlinear calibration model for monitoring product quality in real-time during a biopharmaceutical purification process intended for clinical and commercial manufacturing. These results demonstrate potential feasibility to implement quality monitoring during GGMP manufacturing as well as to increase chemistry, manufacturing, and controls understanding during process development, ultimately leading to more robust and controlled manufacturing processes.     

Implementation of quality by design toward processing of food products

Quality by design (QbD) is a systematic approach that begins with predefined objectives and emphasizes product and process understanding and process control. It is an approach based on principles of sound science and quality risk management. As the food processing industry continues to embrace the idea of in-line, online, and/or at-line sensors and real-time characterization for process monitoring and control, the existing gaps with regard to our ability to monitor multiple parameters/variables associated with the manufacturing process will be alleviated over time. Investments made for development of tools and approaches that facilitate high-throughput analytical and process development, process analytical technology, design of experiments, risk analysis, knowledge management, and enhancement of process/product understanding would pave way for operational and economic benefits later in the commercialization process and across other product pipelines. This article aims to achieve two major objectives. First, to review the progress that has been made in the recent years on the topic of QbD implementation in processing of food products and second, present a case study that illustrates benefits of such QbD implementation.     

Development of a quantitative mass spectrometry multi-attribute method for characterization,quality control testing and disposition of biologics

Regulatory agencies have recently recommended a Quality by Design (QbD) approach for the manufacturing of therapeutic molecules. A QbD strategy requires deep understanding at the molecular level of the attributes that are crucial for safety and efficacy and for insuring that the desired quality of the purified protein drug product is met at the end of the manufacturing process. A mass spectrometry (MS)-based approach to simultaneously monitor the extensive array of product quality attributes (PQAs) present on therapeutic molecules has been developed. This multi-attribute method (MAM) uses a combination of high mass accuracy / high resolution MS data generated by Orbitrap technology and automated identification and relative quantification of PQAs with dedicated software (Pinpoint). The MAM has the potential to replace several conventional electrophoretic and chromatographic methods currently used in Quality Control to release therapeutic molecules. The MAM represents an optimized analytical solution to focus on the attributes of the therapeutic molecule essential for function and implement QbD principles across process development, manufacturing and drug disposition.     

Evaluation of manometric temperature measurement, a process analytical technology tool for freeze-drying: Part I, product temperature measurement

This study examines the factors that may cause systematic errors in the manometric temperature measurement (MTM) procedure used to evaluate product temperature during primary drying. MTM was conducted during primary drying using different vial loads, and the MTM product temperatures were compared with temperatures directly measured by thermocouples. To clarify the impact of freeze-drying load on MTM product temperatures, simulation of the MTM vapor pressure rise was performed, and the results were compared with the experimental results. The effect of product temperature heterogeneity in MTM product temperature determination was investigated by comparing the MTM product temperatures with directly measured thermocouple product temperatures in systems differing in temperature heterogeneity. Both the simulated and experimental results showed that at least 50 vials (5 mL) were needed to give sufficiently rapid pressure rise during the MTM data collection period (25 seconds) in the freeze dryer, to allow accurate determination of the product temperature. The product temperature is location dependent, with higher temperature for vials on the edge of the array and lower temperature for the vials in the center of the array. The product temperature heterogeneity is also dependent upon the freeze-drying conditions. In product temperature heterogeneous systems, MTM measures a temperature close to the coldest product temperature, even, if only a small fraction of the samples have the coldest product temperature. The MTM method is valid even at very low product temperature (−45°C). Published: February 10, 2006     

Case study and application of process analytical technology (PAT) towards bioprocessing: use of on-line high-performance liquid chromatography (HPLC) for making real-time pooling decisions for process chromatography

Process analytical technology (PAT) has been gaining a lot of momentum in the biopharmaceutical community due to the potential for continuous real time quality assurance resulting in improved operational control and compliance. This paper presents a PAT application for one of the most commonly used unit operation in bioprocessing, namely liquid chromatography. Feasibility of using a commercially available online-high performance liquid chromatography (HPLC) system for real-time pooling of process chromatography column is examined. Further, experimental data from the feasibility studies are modeled and predictions of the model are compared to actual experimental data. It is found that indeed for the application under consideration, the online-HPLC offers a feasible approach for analysis that can facilitate real-time decisions for column pooling based on product quality attributes. It is shown that implementing this analytical scheme allows us to meet two of the key goals that have been outlined for PAT, that is, "variability is managed by the process" and "product quality attributes can be accurately and reliably predicted over the design space established for materials used, process parameters, manufacturing, environmental, and other conditions." Finally, the implications of implementing such a PAT application in a manufacturing environment are discussed. The application presented here can be extended to other modes of process chromatography and/or HPLC analysis.     

Model-based analysis on the relationship of signal quality to real-time extraction of information in bioprocesses

Quality by design (QbD) is a current structured approach to design processes yielding a quality product. Knowledge and process understanding cannot be achieved without proper experimental data; hence requirements for measurement error and frequency of measurement of bioprocess variables have to be defined. In this contribution, a model-based approach is used to investigate impact factors on calculated rates to predict the obtainable information from real-time measurements (= signal quality). Measurement error, biological activity, and averaging window (= period of observation) were identified as biggest impact factors on signal quality. Moreover, signal quality has been set in context with a quantifiable measure using statistical error testing, which can be used as a benchmark for process analytics and exploitation of data. Results have been validated with data from an E. coli batch process. This approach is useful to get an idea which process dynamics can be observed with a given bioprocess setup and sampling strategy beforehand.     

Biomanufacturing process analytical technology (PAT) application for downstream processing: Using dissolved oxygen as an indicator of product quality for a protein refolding reaction

Process analytical technology (PAT) is an initiative from the US FDA combining analytical and statistical tools to improve manufacturing operations and ensure regulatory compliance. This work describes the use of a continuous monitoring system for a protein refolding reaction to provide consistency in product quality and process performance across batches. A small‐scale bioreactor (3 L) is used to understand the impact of aeration for refolding recombinant human vascular endothelial growth factor (rhVEGF) in a reducing environment. A reverse‐phase HPLC assay is used to assess product quality. The goal in understanding the oxygen needs of the reaction and its impact to quality, is to make a product that is efficiently refolded to its native and active form with minimum oxidative degradation from batch to batch. Because this refolding process is heavily dependent on oxygen, the % dissolved oxygen (DO) profile is explored as a PAT tool to regulate process performance at commercial manufacturing scale. A dynamic gassing out approach using constant mass transfer (k_La) is used for scale‐up of the aeration parameters to manufacturing scale tanks (2,000 L, 15,000 L). The resulting DO profiles of the refolding reaction show similar trends across scales and these are analyzed using rpHPLC. The desired product quality attributes are then achieved through alternating air and nitrogen sparging triggered by changes in the monitored DO profile. This approach mitigates the impact of differences in equipment or feedstock components between runs, and is directly inline with the key goal of PAT to “actively manage process variability using a knowledge‐based approach.” Biotechnol. Bioeng. 2009; 104: 340–351 © 2009 Wiley Periodicals, Inc.     

At‐line process analytical technology (PAT) for more efficient scale up of biopharmaceutical microfiltration unit operations

Tangential flow microfiltration (MF) is a cost‐effective and robust bioprocess separation technique, but successful full scale implementation is hindered by the empirical, trial‐and‐error nature of scale‐up. We present an integrated approach leveraging at‐line process analytical technology (PAT) and mass balance based modeling to de‐risk MF scale‐up. Chromatography‐based PAT was employed to improve the consistency of an MF step that had been a bottleneck in the process used to manufacture a therapeutic protein. A 10‐min reverse phase ultra high performance liquid chromatography (RP‐UPLC) assay was developed to provide at‐line monitoring of protein concentration. The method was successfully validated and method performance was comparable to previously validated methods. The PAT tool revealed areas of divergence from a mass balance‐based model, highlighting specific opportunities for process improvement. Adjustment of appropriate process controls led to improved operability and significantly increased yield, providing a successful example of PAT deployment in the downstream purification of a therapeutic protein. The general approach presented here should be broadly applicable to reduce risk during scale‐up of filtration processes and should be suitable for feed‐forward and feed‐back process control. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 32:108–115, 2016     

Fermentanomics: Relating quality attributes of a monoclonal antibody to cell culture process variables and raw materials using multivariate data analysis

Fermentanomics is an emerging field of research and involves understanding the underlying controlled process variables and their effect on process yield and product quality. Although major advancements have occurred in process analytics over the past two decades, accurate real‐time measurement of significant quality attributes for a biotech product during production culture is still not feasible. Researchers have used an amalgam of process models and analytical measurements for monitoring and process control during production. This article focuses on using multivariate data analysis as a tool for monitoring the internal bioreactor dynamics, the metabolic state of the cell, and interactions among them during culture. Quality attributes of the monoclonal antibody product that were monitored include glycosylation profile of the final product along with process attributes, such as viable cell density and level of antibody expression. These were related to process variables, raw materials components of the chemically defined hybridoma media, concentration of metabolites formed during the course of the culture, aeration‐related parameters, and supplemented raw materials such as glucose, methionine, threonine, tryptophan, and tyrosine. This article demonstrates the utility of multivariate data analysis for correlating the product quality attributes (especially glycosylation) to process variables and raw materials (especially amino acid supplements in cell culture media). The proposed approach can be applied for process optimization to increase product expression, improve consistency of product quality, and target the desired quality attribute profile. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1586–1599, 2015     

Case study and application of process analytical technology (PAT) towards bioprocessing: II. Use of ultra-performance liquid chromatography (UPLC) for making real-time pooling decisions for process chromatography

Process analytical technology (PAT) has been gaining a lot of momentum in the biopharmaceutical community due to the potential for continuous real-time quality assurance resulting in improved operational control and compliance. Two of the key goals that have been outlined for PAT are "variability is managed by the process" and "product quality attributes can be accurately and reliably predicted over the design space established for materials used, process parameters, manufacturing, environmental, and other conditions". Recently, we have been examining the feasibility of applying different analytical tools for designing PAT applications for bioprocessing. We have previously shown that a commercially available online high performance liquid chromatography (HPLC) system can be used for analysis that can facilitate real-time decisions for column pooling based on product quality attributes (Rathore et al., 2008). In this article we test the feasibility of using a commercially available ultra- performance liquid chromatography (UPLC) system for real-time pooling of process chromatography columns. It is demonstrated that the UPLC system offers a feasible approach and meets the requirements of a PAT application. While the application presented here is of a reversed phase assay, the approach and the hardware can be easily applied to other modes of liquid chromatography.     

Evaluation of manometric temperature measurement (MTM), a process analytical technology tool in freeze drying, part III: Heat and mass transfer measurement

This article evaluates the procedures for determining the vial heat transfer coefficient and the extent of primary drying through manometric temperature measurement (MTM). The vial heat transfer coefficients (K_v) were calculated from the MTM-determined temperature and resistance and compared with K_v values determined by a gravimetric method. The differences between the MTM vial heat transfer coefficients and the gravimetric values are large at low shelf temperature but smaller when higher shelf temperatures were used. The differences also became smaller at higher chamber pressure and smaller when higher resistance materials were being freeze-dried. In all cases, using thermal shields greatly improved the accuracy of the MTM K_v measurement. With use of thermal shields, the thickness of the frozen layer calculated from MTM is in good agreement with values obtained gravimetrically. The heat transfer coefficient “error” is largely a direct result of the error in the dry layer resistance (ie, MTM-determined resistance is too low). This problem can be minimized if thermal shields are used for freeze-drying. With suitable use of thermal shields, accurate K_v values are obtained by MTM; thus allowing accurate calculations of heat and mass flow rates. The extent of primary drying can be monitored by real-time calculation of the amount of remaining ice using MTM data, thus providing a process analytical tool that greatly improves the freeze-drying process design and control.     

层次分析法对南水北调中线水源区的水质评价

层次分析法(AHP)是一种多指标多因素综合评价法,其理论内容深刻而表现形式简单,包括递阶层次结构模型、判断矩阵的建立及其求值、一致性检验和综合指数计算等运算过程.在南水北调中线水源区3个采样点进行了2a的水体浮游植物和9项理化指标的检测,并应用层次分析法通过季节4因素和6项理化指标对水质进行综合评价.结果表明:层次分析综合指数PI在3采样点有差异并且变化灵敏,渠首 (陶岔S1 ) PI=0.5697,水质属于污染;库心 (小太平洋S2 ) PI=0.3619,水质属于尚清洁;丹江入库上游 (大石桥S3 ), PI=0.7755,水质属于中污染;AHP分析结果与实际基本相符.根据结果分析认为:层次分析法做为综合评价法对水质评价有重要性,值得推广应用;丹江口水库是重要的水资源,但目前水质状况并不理想,因此做好水源区的长期生态监测,加强理论和技术研究,改善水质,极为重要.     

The future of host cell protein (HCP) identification during process development and manufacturing linked to a risk‐based management for their control

The use of biological systems to synthesize complex therapeutic products has been a remarkable success. However, during product development, great attention must be devoted to defining acceptable levels of impurities that derive from that biological system, heading this list are host cell proteins (HCPs). Recent advances in proteomic analytics have shown how diverse this class of impurities is; as such knowledge and capability grows inevitable questions have arisen about how thorough current approaches to measuring HCPs are. The fundamental issue is how to adequately measure (and in turn monitor and control) such a large number of protein species (potentially thousands of components) to ensure safe and efficacious products. A rather elegant solution is to use an immunoassay (enzyme‐linked immunosorbent assay [ELISA]) based on polyclonal antibodies raised to the host cell (biological system) used to synthesize a particular therapeutic product. However, the measurement is entirely dependent on the antibody serum used, which dictates the sensitivity of the assay and the degree of coverage of the HCP spectrum. It provides one summed analog value for HCP amount; a positive if all HCP components can be considered equal, a negative in the more likely event one associates greater risk with certain components of the HCP proteome. In a thorough risk‐based approach, one would wish to be able to account for this. These issues have led to the investigation of orthogonal analytical methods; most prominently mass spectrometry. These techniques can potentially both identify and quantify HCPs. The ability to measure and monitor thousands of proteins proportionally increases the amount of data acquired. Significant benefits exist if the information can be used to determine critical HCPs and thereby create an improved basis for risk management. We describe a nascent approach to risk assessment of HCPs based upon such data, drawing attention to timeliness in relation to biosimilar initiatives. The development of such an approach requires databases based on cumulative knowledge of multiple risk factors that would require national and international regulators, standards authorities (e.g., NIST and NIBSC), industry and academia to all be involved in shaping what is the best approach to the adoption of the latest bioanalytical technology to this area, which is vital to delivering safe efficacious biological medicines of all types. Biotechnol. Bioeng. 2015;112: 1727–1737. © 2015 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.     

Association of polymorphisms in calpain 1, (mu/I) large subunit,calpastatin, and cathepsin D genes with meat quality traits in double‐muscled Piemontese cattle

Five single‐nucleotide polymorphisms (SNPs) located in the calpain 1, (mu/I) large subunit (CAPN1), calpastatin (CAST), and cathepsin D (CTSD) genes were analyzed in a large sample of Piemontese cattle. The aim of this study was to evaluate allele and genotype frequencies of these SNPs and to investigate associations of CAPN1, CAST, and CTSD gene variants with meat quality traits. Minor allele frequencies ranged from 30 to 48%. The presence of the A allele at CAPN530 increased yellowness and drip loss. The CAST282 G allele was associated with an increased drip loss compared to the C allele, and the CAST2959 A allele decreased redness compared to the G allele.     

Leaf development, temperature and light stress control of the expression of early light-inducible proteins (ELIPs) in Vitis vinifera L.

Early light inducible proteins (ELIPs) are thylakoid proteins transiently induced by light. They are found in many species, most of which are annual plants. Studies on perennial plants are scarce and in grapevine almost nil. Because grapevines normally grow in sites with high radiation, we aimed to characterize the ELIP expression to evaluate whether they have a role in photoprotection in this species. ELIP expression was characterized in leaves at different temperatures, times of induction and natural light intensities. Very low expression was found in mature leaves. In young leaves, ELIP expression was high but began at temperatures higher than 13 °C. Maximal expression was obtained at 30 °C after 4 h of induction at 1000 μmol PAR m⁻² s⁻¹. At this intensity, the level of photoinhibition was also maximal. We conclude that in grapevine leaves, ELIP expression is developmentally dependent, occurring mainly in developing leaves, Finally, our results showed that the light intensity dependence of the ELIP expression correlated with the extent of photoinhibition indicating that ELIP induction is controlled by the strength of light stress and suggesting a role of these proteins in photoprotection.     

Plant/pathogen interactions observed during host range testing of the rust fungus Uromyces pencanus,a classical biological control agent for Chilean needle grass (Nassella neesiana) in Australia and New Zealand

Nassella neesiana (Chilean needle grass) is a South American grass species that is a serious weed in Australia and New Zealand. The rust fungus Uromyces pencanus is a promising biocontrol agent that could be used to control the weed in both countries. Extensive host range testing has been conducted to explore the specificity of the rust. In this paper we discuss the different degrees of invasion by the rust of the tissues of target and non-target species; the plant defences elicited by such invasion at the cellular level; and their relevance to the biological control of Chilean needle grass.