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     

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.     

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.     

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.     

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.     

Mechanistic modeling based process analytical technology implementation for pooling in hydrophobic interaction chromatography

A major challenge in chromatography purification of therapeutic proteins is batch-to-batch variability with respect to impurity levels and product concentration in the feed. Mechanistic model can enable process analytical technology (PAT) implementation by predicting impact of such variations and thereby improving the robustness of the resulting process and controls. This article presents one such application of mechanistic model of hydrophobic interaction chromatography (HIC) as a PAT tool for making robust pooling decisions to enable clearance of aggregates for a monoclonal antibody (mAb) therapeutic. Model predictions were performed before the actual chromatography experiments to facilitate feedforward control. The approach has been successfully demonstrated for four different feeds with varying aggregate levels (3.84%–5.54%) and feed concentration (0.6 mg/mL–1 mg/mL). The resulting pool consistently yielded a product with 1.32 ± 0.03% aggregate vs. a target of 1.5%. A comparison of the traditional approach involving column fractionation with the proposed approach indicates that the proposed approach results in achievement of satisfactory product purity (98.68 ± 0.03% for mechanistic model based PAT controlled pooling vs. 98.64 ± 0.16% for offline column fractionation based pooling). © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 35: e2758, 2019.     

Single‐step affinity purification of enzyme biotherapeutics: A platform methodology for accelerated process development

Downstream sample purification for quality attribute analysis is a significant bottleneck in process development for non‐antibody biologics. Multi‐step chromatography process train purifications are typically required prior to many critical analytical tests. This prerequisite leads to limited throughput, long lead times to obtain purified product, and significant resource requirements. In this work, immunoaffinity purification technology has been leveraged to achieve single‐step affinity purification of two different enzyme biotherapeutics (Fabrazyme® [agalsidase beta] and Enzyme 2) with polyclonal and monoclonal antibodies, respectively, as ligands. Target molecules were rapidly isolated from cell culture harvest in sufficient purity to enable analysis of critical quality attributes (CQAs). Most importantly, this is the first study that demonstrates the application of predictive analytics techniques to predict critical quality attributes of a commercial biologic. The data obtained using the affinity columns were used to generate appropriate models to predict quality attributes that would be obtained after traditional multi‐step purification trains. These models empower process development decision‐making with drug substance‐equivalent product quality information without generation of actual drug substance. Optimization was performed to ensure maximum target recovery and minimal target protein degradation. The methodologies developed for Fabrazyme were successfully reapplied for Enzyme 2, indicating platform opportunities. The impact of the technology is significant, including reductions in time and personnel requirements, rapid product purification, and substantially increased throughput. Applications are discussed, including upstream and downstream process development support to achieve the principles of Quality by Design (QbD) as well as integration with bioprocesses as a process analytical technology (PAT). © 2014 American Institute of Chemical Engineers Biotechnol. Prog., 30:708–717, 2014     

Process analytical technology (PAT) tools for the cultivation step in biopharmaceutical production

The process analytical technology (PAT) initiative is now 10 years old. This has resulted in the development of many tools and software packages dedicated to PAT application on pharmaceutical processes. However, most applications are restricted to small molecule drugs, mainly for the relatively simple process steps like drying or tableting where only a limited number of parameters need to be controlled. A big challenge for PAT still lies in applications for biopharmaceuticals and then especially in the cultivation process step, where the quality of a biopharmaceutical product is largely determined. This review gives an overview of the currently available tools for monitoring and controlling the biopharmaceutical cultivation step and of the main challenges for the most common cell platforms (i.e. Escherichia coli, yeast, and mammalian cells) used in biopharmaceutical manufacturing. The real challenge is to understand how intracellular mechanisms (from synthesis to excretion) influence the quality of biopharmaceuticals and how these mechanisms can be monitored and controlled to yield the desired end product quality. Modern “omics” tools and advanced process analyzers have opened up the way for PAT applications for the biopharmaceutical cultivation process step.     

Enabling PAT in insect cell bioprocesses: In situ monitoring of recombinant adeno-associated virus production by fluorescence spectroscopy

The process analytical technology (PAT) initiative shifted the bioprocess development mindset towards real-time monitoring and control tools to measure relevant process variables online, and acting accordingly when undesirable deviations occur. Online monitoring is especially important in lytic production systems in which released proteases and changes in cell physiology are likely to affect product quality attributes, as is the case of the insect cell-baculovirus expression vector system (IC-BEVS), a well-established system for production of viral vectors and vaccines. Here, we applied fluorescence spectroscopy as a real-time monitoring tool for recombinant adeno-associated virus (rAAV) production in the IC-BEVS. Fluorescence spectroscopy is simple, yet sensitive and informative. To overcome the strong fluorescence background of the culture medium and improve predictive ability, we combined artificial neural network models with a genetic algorithm-based approach to optimize spectra preprocessing. We obtained predictive models for rAAV titer, cell viability and cell concentration with normalized root mean squared errors of 7%, 4%, and 7%, respectively, for leave-one-batch-out cross-validation. Our approach shows fluorescence spectroscopy allows real-time determination of the best time of harvest to maintain rAAV infectivity, an important quality attribute, and detection of deviations from the golden batch profile. This methodology can be applied to other biopharmaceuticals produced in the IC-BEVS, supporting the use of fluorescence spectroscopy as a versatile PAT tool.     

Digital twin of a continuous chromatography process for mAb purification: Design and model-based control

Model-based design of integrated continuous train coupled with online process analytical technology (PAT) tool can be a potent facilitator for monitoring and control of Critical Quality Attributes (CQAs) in real time. Charge variants are product related variants and are often regarded as CQAs as they may impact potency and efficacy of drug. Robust pooling decision is required for achieving uniform charge variant composition for mAbs as baseline separation between closely related variants is rarely achieved in process scale chromatography. In this study, we propose a digital twin of a continuous chromatography process, integrated with an online HPLC-PAT tool for delivering real time pooling decisions to achieve uniform charge variant composition. The integrated downstream process comprised continuous multicolumn capture protein A chromatography, viral inactivation in coiled flow inverter reactor (CFIR), and multicolumn CEX polishing step. An online HPLC was connected to the harvest tank before protein A chromatography. Both empirical and mechanistic modeling have been considered. The model states were updated in real time using online HPLC charge variant data for prediction of the initial and final cut point for CEX eluate, according to which the process chromatography was directed to switch from collection to waste to achieve the desired charge variant composition in the CEX pool. Two case studies were carried out to demonstrate this control strategy. In the first case study, the continuous train was run for initially 14 h for harvest of fixed charge variant composition as feed. In the second case study, charge variant composition was dynamically changed by introducing forced perturbation to mimic the deviations that may be encountered during perfusion cell culture. The control strategy was successfully implemented for more than ±5% variability in the acidic variants of the feed with its composition in the range of acidic (13%–17%), main (18%–23%), and basic (59%–68%) variants. Both the case studies yielded CEX pool of uniform distribution of acidic, main and basic profiles in the range of 15 ± 0.8, 31 ± 0.3, and 53 ± 0.5%, respectively, in the case of empirical modeling and 15 ± 0.5, 31 ± 0.3, and 53 ± 0.3%, respectively, in the case of mechanistic modeling. In both cases, process yield for main species was >85% and the use of online HPLC early in the purification train helped in making quicker decision for pooling of CEX eluate. The results thus successfully demonstrate the technical feasibility of creating digital twins of bioprocess operations and their utility for process control.     

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.     

Raman based chemometric model development for glycation and glycosylation real time monitoring in a manufacturing scale CHO cell bioreactor process

The Quality by Design (QbD) approach to the production of therapeutic monoclonal antibodies (mAbs) emphasizes an understanding of the production process ensuring product quality is maintained throughout. Current methods for measuring critical quality attributes (CQAs) such as glycation and glycosylation are time and resource intensive, often, only tested offline once per batch process. Process analytical technology (PAT) tools such as Raman spectroscopy combined with chemometric modeling can provide real time measurements process variables and are aligned with the QbD approach. This study utilizes these tools to build partial least squares (PLS) regression models to provide real time monitoring of glycation and glycosylation profiles. In total, seven cell line specific chemometric PLS models; % mono-glycated, % non-glycated, % G0F-GlcNac, % G0, % G0F, % G1F, and % G2F were considered. PLS models were initially developed using small scale data to verify the capability of Raman to measure these CQAs effectively. Accurate PLS model predictions were observed at small scale (5 L). At manufacturing scale (2000 L) some glycosylation models showed higher error, indicating that scale may be a key consideration in glycosylation profile PLS model development. Model robustness was then considered by supplementing models with a single batch of manufacturing scale data. This data addition had a significant impact on the predictive capability of each model, with an improvement of 77.5% in the case of the G2F. The finalized models show the capability of Raman as a PAT tool to deliver real time monitoring of glycation and glycosylation profiles at manufacturing scale.     

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.     

Hybrid modeling framework for process analytical technology: application to Bordetella pertussis cultures

In the process analytical technology (PAT) initiative, the application of sensors technology and modeling methods is promoted. The emphasis is on Quality by Design, online monitoring, and closed-loop control with the general aim of building in product quality into manufacturing operations. As a result, online high-throughput process analyzers find increasing application and therewith high amounts of highly correlated data become available online. In this study, an hybrid chemometric/mathematical modeling method is adopted for data analysis, which is shown to be advantageous over the commonly used chemometric techniques in PAT applications. This methodology was applied to the analysis of process data of Bordetella pertussis cultivations, namely online data of near-infrared, (NIR), pH, temperature and dissolved oxygen, and off-line data of biomass, glutamate, and lactate concentrations. The hybrid model structure consisted of macroscopic material balance equations in which the specific reactions rates are modeled by nonlinear partial least square (PLS). This methodology revealed a significant higher statistical confidence in comparison to PLSs, translated in a reduction of mean squared prediction errors (e.g., individual root mean squared prediction errors calibration/validation obtained through the hybrid model for the concentrations of lactate: 0.8699/0.7190 mmol/L; glutamate: 0.6057/0.2917 mmol/L; and biomass: 0.0520/0.0283 OD; and obtained through the PLS model for the concentrations of lactate: 1.3549/1.0087 mmol/L; glutamate: 0.7628/0.3504 mmol/L; and biomass: 0.0949/0.0412 OD). Moreover, the analysis of loadings and scores in the hybrid approach revealed that process features can, as for PLS, be extracted by the hybrid method.     

Design of a microfluidic mixer channel: First steps into creating a fluorescent dye-based biosensor for mAb aggregate detection

A major challenge in the transition to continuous biomanufacturing is the lack of process analytical technology (PAT) tools which are able to collect real-time information on the process and elicit a response to facilitate control. One of the critical quality attributes (CQAs) of interest during monoclonal antibodies production is aggregate formation. The development of a real-time PAT tool to monitor aggregate formation is then crucial to have immediate feedback and process control. Miniaturized sensors placed after each unit operation can be a powerful solution to speed up an analytical measurement due to their characteristic short reaction time. In this work, a micromixer structure capable of mixing two streams is presented, to be employed in the detection of mAb aggregates using fluorescent dyes. Computational fluid dynamics (CFD) simulations were used to compare the mixing performance of a series of the proposed designs. A final design of a zigzag microchannel with 45° angle was reached and this structure was subsequently fabricated and experimentally validated with colour dyes and, later, with a FITC-IgG molecule. The designed zigzag micromixer presents a mixing index of around 90%, obtained in less than 30 seconds. Therefore, a micromixer channel capable of a fast and efficient mixing is hereby demonstrated, to be used as a real-time PAT tool for a fluorescence based detection of protein aggregation.     

Towards robust cell culture processes — Unraveling the impact of media preparation by spectroscopic online monitoring

Biopharmaceutical manufacturing processes can be affected by variability in cell culture media, e.g. caused by raw material impurities. Although efforts have been made in industry and academia to characterize cell culture media and raw materials with advanced analytics, the process of industrial cell culture media preparation itself has not been reported so far. Within this publication, we first compare mid‐infrared and two‐dimensional fluorescence spectroscopy with respect to their suitability as online monitoring tools during cell culture media preparation, followed by a thorough assessment of the impact of preparation parameters on media quality. Through the application of spectroscopic methods, we can show that media variability and its corresponding root cause can be detected online during the preparation process. This methodology is a powerful tool to avoid batch failure and is a valuable technology for media troubleshooting activities. Moreover, in a design of experiments approach, including additional liquid chromatography–mass spectrometry analytics, it is shown that variable preparation parameters such as temperature, power input and preparation time can have a strong impact on the physico‐chemical composition of the media. The effect on cell culture process performance and product quality in subsequent fed‐batch processes was also investigated. The presented results reveal the need for online spectroscopic methods during the preparation process and show that media variability can already be introduced by variation in media preparation parameters, with a potential impact on scale‐up to a commercial manufacturing process.     

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.