Process control in cell culture technology using dielectric spectroscopy

In the biopharmaceutical industry, mammalian and insect cells as well as plant cell cultures are gaining worldwide importance to produce biopharmaceuticals and as products themselves, for example in stem cell therapy. These highly sophisticated cell-based production processes need to be monitored and controlled to guarantee product quality and to satisfy GMP requirements. With the process analytical technology (PAT) initiative, requirements regarding process monitoring and control have changed and real-time in-line monitoring tools are now recommended. Dielectric spectroscopy (DS) can serve as a tool to satisfy some PAT requirements. DS has been used in the medical field for quite some time and it may allow real-time process monitoring of biological cell culture parameters. DS has the potential to enable process optimization, automation, cost reduction, and a more consistent product quality. Dielectric spectroscopy is reviewed here as a tool to monitor biochemical processes. Commercially available dielectric sensing systems are discussed. The potential of this technology is demonstrated through examples of current and potential future applications in research and industry for mammalian and insect cell culture.     

Process analytical technology tools for perfusion cell culture

During cell cultivation processes for the production of biopharmaceuticals, good process performance and good product quality can be ensured by online monitoring of critical process parameters (e.g. temperature, pH, or dissolved oxygen). These data can be used in real‐time for process control, as suggested by the process analytical technology (PAT) initiative. Today, solutions for real‐time monitoring of parameters such as concentrations of cells, main nutrients, and metabolism by‐products are developing, but applications of these more complex tools in industrial settings are still limited. Here, we evaluated the use of dielectric spectroscopy (DS) and near‐infrared spectroscopy (NIRS) as PAT tools for a perfusion PER.C6^® cultivation process. We showed that DS enabled predictions of viable cell density from the cultivation vessel, with a root mean square error of prediction (RMSEP) of 4.4% of the calibration range. Additionally, predictions of glucose and lactate concentrations from the cultivation vessel (RMSEP of 10 and 14%, respectively) and from the perfusion stream (RMSEP of 12 and 10%, respectively) were achieved with NIRS. We also showed that the perfusion stream offers great opportunities for noninvasive, yet frequent process monitoring. Accurate online monitoring of critical process parameters with PAT tools is the essential first step toward increased control of process output.     

The production of biopharmaceuticals in plant systems

Biopharmaceuticals present the fastest growing segment in the pharmaceutical industry, with an ever widening scope of applications. Whole plants as well as contained plant cell culture systems are being explored for their potential as cheap, safe, and scalable production hosts. The first plant-derived biopharmaceuticals have now reached the clinic. Many biopharmaceuticals are glycoproteins; as the Golgi N-glycosylation machinery of plants differs from the mammalian machinery, the N-glycoforms introduced on plant-produced proteins need to be taken into consideration. Potent systems have been developed to change the plant N-glycoforms to a desired or even superior form compared to the native mammalian N-glycoforms. This review describes the current status of biopharmaceutical production in plants for industrial applications. The recent advances and tools which have been utilized to generate glycoengineered plants are also summarized and compared with the relevant mammalian systems whenever applicable.     

Process analytical technology (PAT) for biopharmaceutical products: Part I. concepts and applications

Process analytical technology (PAT) has been gaining momentum in the biotech community due to the potential for continuous real‐time quality assurance resulting in improved operational control and compliance. In this two part series, we address PAT as it applies to processes that produce biotech therapeutic products. In the first part, we address evolution of the underlying concepts and applications in biopharmaceutical manufacturing. We also present a literature review of applications in the areas of upstream and downstream processing to illustrate how implementation of PAT can help realize advanced approaches to ensuring product quality in real time. In the second part, we will explore similar applications in the areas of drug product manufacturing, rapid microbiology, and chemometrics as well as evolution of PAT in biotech processing. Biotechnol. Bioeng. 2010; 105: 276–284. Published 2009 Wiley Periodicals, Inc.     

Progress toward forecasting product quality and quantity of mammalian cell culture processes by performance‐based modeling

The production of biopharmaceuticals requires highly sophisticated, complex cell based processes. Once a process has been developed, acceptable ranges for various control parameters are typically defined based on process characterization studies often comprising several dozens of small scale bioreactor cultivations. A lot of data is generated during these studies and usually only the information needed to define acceptable ranges is processed in more detail. Making use of the wealth of information contained in such data sets, we present here a methodology that uses performance data (such as metabolite profiles) to forecast the product quality and quantity of mammalian cell culture processes based on a toolbox of advanced statistical methods. With this performance based modeling (PBM) the final product concentration and 12 quality attributes (QAs) for two different biopharmaceutical products were predicted in daily intervals throughout the main stage process. The best forecast was achieved for product concentration in a very early phase of the process. Furthermore, some glycan isoforms were predicted with good accuracy several days before the bioreactor was harvested. Overall, PBM clearly demonstrated its capability of early process endpoint prediction by only using commonly available data, even though it was not possible to predict all QAs with the desired accuracy. Knowing the product quality prior to the harvest allows the manufacturer to take counter measures in case the forecasted quality or quantity deviates from what is expected. This would be a big step towards real‐time release, an important element of the FDA's PAT initiative. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1119–1127, 2015     

Genetic engineering approaches to improve posttranslational modification of biopharmaceuticals in different production platforms

The number of approved biopharmaceuticals, where product quality attributes remain of major importance, is increasing steadily. Within the available variety of expression hosts, the production of biopharmaceuticals faces diverse limitations with respect to posttranslational modifications (PTM), while different biopharmaceuticals demand different forms and specifications of PTMs for proper functionality. With the growing toolbox of genetic engineering technologies, it is now possible to address general as well as host- or biopharmaceutical-specific product quality obstacles. In this review, we present diverse expression systems derived from mammalians, bacteria, yeast, plants, and insects as well as available genetic engineering tools. We focus on genes for knockout/knockdown and overexpression for meaningful approaches to improve biopharmaceutical PTMs and discuss their applicability as well as future trends in the field.     

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.     

Real-time detection of mAb aggregates in an integrated downstream process

The implementation of continuous processing in the biopharmaceutical industry is hindered by the scarcity of process analytical technologies (PAT). To monitor and control a continuous process, PAT tools will be crucial to measure real-time product quality attributes such as protein aggregation. Miniaturizing these analytical techniques can increase measurement speed and enable faster decision-making. A fluorescent dye (FD)-based miniaturized sensor has previously been developed: a zigzag microchannel which mixes two streams under 30 s. Bis-ANS and CCVJ, two established FDs, were employed in this micromixer to detect aggregation of the biopharmaceutical monoclonal antibody (mAb). Both FDs were able to robustly detect aggregation levels starting at 2.5%. However, the real-time measurement provided by the microfluidic sensor still needs to be implemented and assessed in an integrated continuous downstream process. In this work, the micromixer is implemented in a lab-scale integrated system for the purification of mAbs, established in an ÄKTA™ unit. A viral inactivation and two polishing steps were reproduced, sending a sample of the product pool after each phase directly to the microfluidic sensor for aggregate detection. An additional UV sensor was connected after the micromixer and an increase in its signal would indicate that aggregates were present in the sample. The at-line miniaturized PAT tool provides a fast aggregation measurement, under 10 min, enabling better process understanding and control.     

A mass spectrometry-based approach to host cell protein identification and its application in a comparability exercise

Host cell proteins (HCPs) are process-related impurities present in biopharmaceuticals and are generally considered to be critical quality attributes. Changes in a biopharmaceutical production process may result in qualitative shifts in the HCP population. These shifts are not necessarily detectable when overall HCP levels are measured with traditional approaches such as enzyme-linked immunosorbent assays (ELISAs). Thus, the development of techniques that complement the ELISA’s functionality is desirable. Here, a mass spectrometry (MS)-based approach for the analysis of HCP populations in biopharmaceuticals is presented. It consists of (i) the generation of exclusion lists that represent the masses of the active pharmaceutical ingredient (API), (ii) the compilation of inclusion lists based on an HCP catalog derived from the analysis of protein A-purified samples, and (iii) the analysis of purified biopharmaceuticals using the generated exclusion and inclusion lists. With this approach, it was possible to increase sensitivity for HCP detection compared with a standard liquid chromatography tandem MS (LC–MS/MS) run. The workflow was successfully implemented in a comparability exercise assessing HCP populations in drug substance samples before and after a process change. Furthermore, the results suggest that size can be an important factor in the copurification of HCPs and API.     

Case study and application of process analytical technology (PAT) towards bioprocessing: Use of tryptophan fluorescence as at‐line tool for making pooling decisions for process chromatography

Process analytical technology (PAT) has been gaining momentum in the biopharmaceutical community due to the potential for continuous real time quality assurance resulting in improved operational control and compliance. Two imperatives for implementing any PAT tool are that “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 to bioprocessing unit operations. We have previously demonstarted that commercially available online‐high performance liquid chromatography and ultra performance liquid chromatography systems can be used for analysis that can facilitate real‐time decisions for column pooling based on product quality attributes (Rathore et al., 2008 a,b). In this article, we review an at‐line tool that can be used for pooling of process chromatography columns. We have demonstrated that our tryptophan fluorescence method offers a feasible approach and meets the requirements of a PAT application. It is significantly faster than the alternative of fractionation, offline analysis followed by pooling. Although the method as presented here is not an online method, this technique may offer better resolution for certain applications and may be a more optimal approach as it is very conducive to implementation in a manufacturing environment. This technique is also amenable to be used as an online tool via front face fluorescence measurements done concurrently with product concentration determination by UV. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009     

Multivariate PAT solutions for biopharmaceutical cultivation: current progress and limitations

Increasingly elaborate and voluminous datasets are generated by the (bio)pharmaceutical industry and are a major challenge for application of PAT and QbD principles. Multivariate data analysis (MVDA) is required to delineate relevant process information from large multi-factorial and multi-collinear datasets. Here the key role of MVDA for industrial (bio)process data is discussed, with a focus on progress and limitations of MVDA as a PAT solution for biopharmaceutical cultivation processes. MVDA based models were proven useful and should be routinely implemented for bioprocesses. It is concluded that although the highest level of PAT with process control within its design space in real-time during manufacturing is not reached yet, MVDA will be central to reach this ultimate objective for cell cultivations.     

Process analytical technology (PAT) for biopharmaceutical products: Part II. Concepts and applications

Implementing real‐time product quality control meets one or both of the key goals outlined in FDA's PAT guidance: “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.” The first part of the paper presented an overview of PAT concepts and applications in the areas of upstream and downstream processing. In this second part, we present principles and case studies to illustrate implementation of PAT for drug product manufacturing, rapid microbiology, and chemometrics. We further present our thoughts on how PAT will be applied to biotech processes going forward. The role of PAT as an enabling component of the Quality by Design framework is highlighted. Integration of PAT with the principles stated in the ICH Q8, Q9, and Q10 guidance documents is also discussed. Biotechnol. Bioeng. 2010; 105: 285–295. Published 2009 Wiley Periodicals, Inc.     

Integration of stochastic simulation with multivariate analysis: Short‐term facility fit prediction

This article describes a decision‐support tool to help pinpoint the potential root causes of sub‐optimal short‐term facility fit issues in biopharmaceutical facilities. This was achieved by creating a tool that integrated stochastic simulation with advanced multivariate statistical analysis. Process fluctuations in product titers in cell culture, step yields, and chromatography eluate volumes were mimicked using Monte Carlo simulation data derived using a stochastic discrete‐event simulation model. The resulting stochastic datasets, with the computed consequences on key metrics such as product mass loss and cost of goods, were examined using advanced multivariate statistical techniques. Principal component analysis combined with clustering algorithms was used to analyze the complex datasets from complete industrial batch processes for biopharmaceuticals. The challenge of visualizing the multidimensional nature of the dataset was addressed using hierarchical and k‐means clustering as well as stacked parallel co‐ordinate plots to help identify process fingerprints and characteristics of clusters leading to sub‐optimal facility fit issues. Industrially‐relevant case studies are presented that focus on technology transfer challenges for therapeutic antibodies moving from early phase to late phase clinical trials. The case study details how sub‐optimal facility fit can be alleviated by allocating alternative product pool tanks. The impact of this operational change is then assessed by reviewing an updated process fingerprint. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 29: 368–377, 2013     

Online- and offline- monitoring of stem cell expansion on microcarrier

In the biopharmaceutical industry, adherent growing stem cell cultures gain worldwide importance as cell products. The cultivation process of these cells, such as in stirred tank reactors or in fixed bed reactors, is highly sophisticated. Cultivations need to be monitored and controlled to guarantee product quality and to satisfy GMP requirements. With the process analytical technology (PAT) initiative, requirements regarding process monitoring and control have changed and real-time on-line monitoring tools are recommended. A tool meeting the new requirements may be the dielectric spectroscopy for online viable cell mass determination by measurement of the permittivity. To establish these tools, proper offline methods for data correlation are required. The cell number determination of adherent cells on microcarrier is difficult, as it requires cell detachment from the carrier, which highly increases the statistical error. As an offline method, a fluorescence assay based on SYBR^®GreenI was developed allowing fast and easy total cell concentration determination without the need to detach the cells from the carrier. The assay is suitable for glass carriers used in stirred tank reactor systems or in fixed bed systems, may be suitable for different cell lines and can be applied to high sample numbers easily. The linear dependency of permittivity to cell concentration of suspended stem cells with the dielectric spectroscopy is shown for even very small cell concentrations. With this offline-method, a correlation of the cell concentration grown on carrier to the permittivity data measured by the dielectric spectroscopy was done successfully.     

Large scale demonstration of a process analytical technology application in bioprocessing: Use of on‐line high performance liquid chromatography for making real time pooling decisions for process chromatography

Process Analytical Technology (PAT) has been gaining a lot of momentum in the biopharmaceutical community because of the potential for continuous real time quality assurance resulting in improved operational control and compliance. In previous publications, we have demonstrated feasibility of applications involving use of high performance liquid chromatography (HPLC) and ultra performance liquid chromatography (UPLC) for real‐time pooling of process chromatography column. In this article we follow a similar approach to perform lab studies and create a model for a chromatography step of a different modality (hydrophobic interaction chromatography). It is seen that the predictions of the model compare well to actual experimental data, demonstrating the usefulness of the approach across the different modes of chromatography. Also, use of online HPLC when the step is scaled up to pilot scale (a 2294 fold scale‐up from a 3.4 mL column in the lab to a 7.8 L column in the pilot plant) and eventually to manufacturing scale (a 45930 fold scale‐up from a 3.4 mL column in the lab to a 158 L column in the manufacturing plant) is examined. Overall, the results confirm that for the application under consideration, online‐HPLC offers a feasible approach for analysis that can facilitate real‐time decisions for column pooling based on product quality attributes. The observations demonstrate that the proposed analytical scheme allows us to meet two of the key goals that have been outlined for PAT, i.e., “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”. The application presented here can be extended to other modes of process chromatography and/or HPLC analysis. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2010     

微针用于生物大分子及纳米药物透皮给药的尝试与挑战

生物大分子及纳米药物,比如,亚单位疫苗、DNA疫苗、以及针对真皮层的治疗药物,作为近年来新兴的治疗药物,在有些治疗领域有着透皮给药的需求。由于具有靶向性高,疗效显著等特点,生物大分子及纳米药物逐渐成为新的研究热点。微针作为一种新型的给药技术,不仅具有无痛、给药方便等优点,而且运用物理手段可大幅提高大分子甚至纳米药物的透皮吸收及皮层靶向,能够避过胃肠道消化作用以及肝脏首过效用。将微针技术与生物大分子药物相结合,能够同时发挥两者的优势,实现高靶向生物药物的无痛给药。本文简述微针透皮给药技术、以及生物大分子给药的研究进展,对微针技术用于生物大分子及纳米药物透皮给药的尝试研究做了介绍和总结,对存在的技术挑战进行了分析和展望。     

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.     

Technology outlook for real-time quality attribute and process parameter monitoring in biopharmaceutical development—A review

Real-time monitoring of bioprocesses by the integration of analytics at critical unit operations is one of the paramount necessities for quality by design manufacturing and real-time release (RTR) of biopharmaceuticals. A well-defined process analytical technology (PAT) roadmap enables the monitoring of critical process parameters and quality attributes at appropriate unit operations to develop an analytical paradigm that is capable of providing real-time data. We believe a comprehensive PAT roadmap should entail not only integration of analytical tools into the bioprocess but also should address automated-data piping, analysis, aggregation, visualization, and smart utility of data for advanced-data analytics such as machine and deep learning for holistic process understanding. In this review, we discuss a broad spectrum of PAT technologies spanning from vibrational spectroscopy, multivariate data analysis, multiattribute chromatography, mass spectrometry, sensors, and automated-sampling technologies. We also provide insights, based on our experience in clinical and commercial manufacturing, into data automation, data visualization, and smart utility of data for advanced-analytics in PAT. This review is catered for a broad audience, including those new to the field to those well versed in applying these technologies. The article is also intended to give some insight into the strategies we have undertaken to implement PAT tools in biologics process development with the vision of realizing RTR testing in biomanufacturing and to meet regulatory expectations.     

An assessment of the impact of Raman based glucose feedback control on CHO cell bioreactor process development

Process analytical technology (PAT) tools such as Raman Spectroscopy have become established tools for real time measurement of CHO cell bioreactor process variables and are aligned with the QbD approach to manufacturing. These tools can have a significant impact on process development if adopted early, creating an end-to-end PAT/QbD focused process. This study assessed the impact of Raman based feedback control on early and late phase development bioreactors by using a Raman based PLS model and PAT management system to control glucose in two CHO cell line bioreactor processes. The impact was then compared to bioreactor processes which used manual bolus fed methods for glucose feed delivery. Process improvements were observed in terms of overall bioreactor health, product output and product quality. Raman controlled batches for Cell Line 1 showed a reduction in glycation of 43.4% and 57.9%, respectively. Cell Line 2 batches with Raman based feedback control showed an improved growth profile with higher VCD and viability and a resulting 25% increase in overall product titer with an improved glycation profile. The results presented here demonstrate that Raman spectroscopy can be used in both early and late-stage process development and design for consistent and controlled glucose feed delivery.     

Advances in on-line monitoring and control of mammalian cell cultures: Supporting the PAT initiative

In recent years, much attention has been directed towards the development of global methods for on-line process monitoring, especially since the Food and Drug Administration (FDA) launched the Process Analytical Technology (PAT) guidance, stimulating biopharmaceutical companies to update their monitoring tools to ensure a pre-defined final product quality. The ideal technologies for biopharmaceutical processes should operate in situ, be non-invasive and generate on-line information about multiple key bioprocess and/or metabolic variables. A wide range of spectroscopic techniques based on in situ probes have already been tested in mammalian cell cultures, such as near infrared (NIR), mid infrared (MIR), 2D fluorescence and dielectric capacitance spectroscopy; similarly, the electronic nose technique based on chemical array sensors has been tested for in situ off-gas analysis of mammalian cell cultures. All these methods provide series of spectra, from which meaningful information must be extracted. In this sense, data mining techniques such as principal components regression (PCR), partial least squares (PLS) or artificial neural networks (ANN) have been applied to handle the dense flow of data generated from the real-time process analyzers. Furthermore, the implementation of feedback control methods would help to improve process performance and ultimately ensure reproducibility. This review discusses the suitability of several spectroscopic techniques coupled with chemometric methods for improved monitoring and control of mammalian cell processes.