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.     

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: 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     

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.     

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.     

Process analytical technology case study: Part II. Development and validation of quantitative near-infrared calibrations in support of a process analytical technology application for real-time release

This article is the second of a series of articles detailing the development of near-infrared (NIR) methods for solid dosage-form analysis. Experiments were conducted at the Duquesne University Center for Pharmaceutical Technology to demonstrate a method for developing and validating NIR models for the analysis of active pharmaceutical ingredient (API) content and hardness of a solid dosage form. Robustness and cross-validation testing were used to optimize the API content and hardness models. For the API content calibration, the optimal model was determined as multiplicative scatter correction with Savitsky-Golay first-derivative preprocessing followed by partial least-squares (PLS) regression including 4 latent variables. API content calibration achieved root mean squared error (RMSE) and root mean square error of cross validation (RMSECV) of 1.48 and 1.80 mg, respectively. PLS regression and baseline-fit calibration models were compared for the prediction of tablet hardness. Based on robustness testing, PLS regression was selected for the final hardness model, with RMSE and RMSECV of 8.1 and 8.8 N, respectively. Validation testing indicated that API content and hardness of production-scale tablets is predicted with root mean square error of prediction of 1.04 mg and 8.5 N, respectively. Explicit robustness testing for high-flux noise and wavelength uncertainty demonstrated the robustness of the API concentration calibration model with respect to normal instrument operating conditions. Published: October 6, 2005 The views presented in this article do not necessarily reflect those of the Food and Drug Administration.     

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.     

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.     

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     

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.     

Improved process analytical technology for protein a chromatography using predictive principal component analysis tools

Protein A chromatography is widely employed for the capture and purification of antibodies and Fc‐fusion proteins. Due to the high cost of protein A resins, there is a significant economic driving force for using these chromatographic materials for a large number of cycles. The maintenance of column performance over the resin lifetime is also a significant concern in large‐scale manufacturing. In this work, several statistical methods are employed to develop a novel principal component analysis (PCA)‐based tool for predicting protein A chromatographic column performance over time. A method is developed to carry out detection of column integrity failures before their occurrence without the need for a separate integrity test. In addition, analysis of various transitions in the chromatograms was also employed to develop PCA‐based models to predict both subtle and general trends in real‐time protein A column yield decay. The developed approach has significant potential for facilitating timely and improved decisions in large‐scale chromatographic operations in line with the process analytical technology (PAT) guidance from the Food and Drug Administration (FDA). Biotechnol. Bioeng. 2011; 108:59–68. © 2010 Wiley Periodicals, Inc.     

Strategic assay deployment as a method for countering analytical bottlenecks in high throughput process development: Case studies in ion exchange chromatography

High throughput approaches to facilitate the development of chromatographic separations have now been adopted widely in the biopharmaceutical industry, but issues of how to reduce the associated analytical burden remain. For example, acquiring experimental data by high level factorial designs in 96 well plates can place a considerable strain upon assay capabilities, generating a bottleneck that limits significantly the speed of process characterization. This article proposes an approach designed to counter this challenge; Strategic Assay Deployment (SAD). In SAD, a set of available analytical methods is investigated to determine which set of techniques is the most appropriate to use and how best to deploy these to reduce the consumption of analytical resources while still enabling accurate and complete process characterization. The approach is demonstrated by investigating how salt concentration and pH affect the binding of green fluorescent protein from Escherichia coli homogenate to an anion exchange resin presented in a 96‐well filter plate format. Compared with the deployment of routinely used analytical methods alone, the application of SAD reduced both the total assay time and total assay material consumption by at least 40% and 5%, respectively. SAD has significant utility in accelerating bioprocess development activities. © 2012 American Institute of Chemical Engineers Biotechnol. Prog., 2012     

Defining process design space for a hydrophobic interaction chromatography (HIC) purification step: Application of quality by design (QbD) principles

The concept of design space has been taking root under the quality by design paradigm as a foundation of in‐process control strategies for biopharmaceutical manufacturing processes. This paper outlines the development of a design space for a hydrophobic interaction chromatography (HIC) process step. The design space included the impact of raw material lot‐to‐lot variability and variations in the feed stream from cell culture. A failure modes and effects analysis was employed as the basis for the process characterization exercise. During mapping of the process design space, the multi‐dimensional combination of operational variables were studied to quantify the impact on process performance in terms of yield and product quality. Variability in resin hydrophobicity was found to have a significant influence on step yield and high‐molecular weight aggregate clearance through the HIC step. A robust operating window was identified for this process step that enabled a higher step yield while ensuring acceptable product quality. Biotechnol. Bioeng. 2010;107: 985–997. © 2010 Wiley Periodicals, Inc.     

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.     

Nepem‐211 ion exchange conductive membrane immobilized tris(2,2´‐bipyridyl) ruthenium(II) electrogenerated chemiluminescence flow sensor for high‐performance liquid chromatography and its application

We developed a sensitive and robust electrogenerated chemiluminescence (ECL) flow sensor based on Ru(bpy)₃²⁺ immobilized with a Nepem‐211 perfluorinated ion exchange conductance membrane, which has robustness and stability under a wide range of chemical and physical conditions, good electrical conductivity, isotropy and a high exchange capacity for immobilization of Ru(bpy)₃²⁺. The flow sensor has been used as a post‐column detector in high‐performance liquid chromatography for determination of erythromycin and clarithromycin in honey and pork, and tricyclic antidepressant drugs in human urine. Under optimal conditions, the linear ranges were 0.03–26 ng/μL and 0.01–1 ng/μL for macrolides and tricyclic antidepressant drugs, respectively. The detection limits were 0.02, 0.01, 0.01, 0.06 and 0.003 ng/μL for erythromycin, clarithromycin, doxepin, amitriptyline and clomipramine, respectively. There is no post‐column reagent addition. In addition to the conservation expensive reagents, the experimental setup was simplified. The flow sensor was used for 2 years with high sensitivity and stability. Copyright © 2013 John Wiley & Sons, Ltd.     

Quantification of uridine 5'-diphosphate (UDP)-glucose by high-performance liquid chromatography and its application to a nonradioactive assay for nucleoside diphosphate kinase using UDP-glucose pyrophosphorylase as a coupling enzyme

We describe a method for the detection and quantification of nucleoside diphosphate kinase (NDPK). NDPK catalyzes the transfer of the gamma-phosphate of cytidine 5'-triphosphate on uridine 5'-diphosphate (UDP) to produce uridine 5'-triphosphate (UTP). The method uses a nonradioactive coupled enzyme assay in which UTP produced by NDPK is utilized by UDP-glucose pyrophosphorylase. This latter enzyme synthesizes UDP-glucose and inorganic phosphate in the presence of glucose 1-phosphate. UDP-glucose is detected at 260 nm after separation of the reaction mixture by high-performance liquid chromatography (HPLC) on a strong anion-exchange column. The assay is reliable, specific, and linear with respect to time and enzyme amount. Using 15 min incubation time, the method allows detection of NDPK activity below 10 pmol/min. It can be used to analyze kinetic behavior and to quantify NDPK from a wide variety of animal, microbial, and plant sources. It also provides an alternative to radiometric assays and an improvement on pyruvate kinase-linked spectrophotometric assays, which can be hampered by pigments present in crude extracts. Furthermore, we show that the HPLC method developed here can be directly used to assay enzymes for which UDP-glucose is a product.     

Development of high performance liquid chromatography/electrospray ionization mass spectrometry for assay of ginkgolic acid (15:1) in rat plasma and its application to pharmacokinetics study

A highly sensitive HPLC–ESI-MS method has been developed and validated for the quantification of ginkgolic acid (15:1) in a small quantity of rat plasma (50 μL) using its homologous compound ginkgolic acid (17:1) as an internal standard. GA (15:1) and GA (17:1) were extracted from biological matrix by direct protein precipitation with 5-fold volume of methanol and separated on an Elite hypersil BDS C₁₈ column (2.1 × 100 mm, 3 μm), eluted with acetonitrile:water (92:8, v/v, containing 0.3% glacial acetic acid). Linear range was 8–1000 ng/mL with the square regression coefficient (r²) of 0.996. The lowest concentration (8 ng/mL) in the calibration curve was estimated as LLOQ with both deviation of accuracy and RSD of precision <20% (n = 6). The intra- and inter-day precision ranged from 3.6% to 9.9%, and the intra- and inter-day accuracy was between 89.9% and 101.3%. This method was successfully applied to study pharmacokinetics of GA (15:1) in rats after oral administration at a dose of 10 mg/kg. GA (15:1) pharmacokinetic parameters C_max, T_max, t_1/2, AUC_0–12h are 1552.9 ± 241.0 ng/mL, 0.9 ± 0.7 h, 5.5 ± 2.6 h, 3356.0 ± 795.3 ng h/mL, respectively.