Application of quality by design principles to the development and technology transfer of a major process improvement for the manufacture of a recombinant protein

This study describes the application of quality by design (QbD) principles to the development and implementation of a major manufacturing process improvement for a commercially distributed therapeutic protein produced in Chinese hamster ovary cell culture. The intent of this article is to focus on QbD concepts, and provide guidance and understanding on how the various components combine together to deliver a robust process in keeping with the principles of QbD. A fed-batch production culture and a virus inactivation step are described as representative examples of upstream and downstream unit operations that were characterized. A systematic approach incorporating QbD principles was applied to both unit operations, involving risk assessment of potential process failure points, small-scale model qualification, design and execution of experiments, definition of operating parameter ranges and process validation acceptance criteria followed by manufacturing-scale implementation and process validation. Statistical experimental designs were applied to the execution of process characterization studies evaluating the impact of operating parameters on product quality attributes and process performance parameters. Data from process characterization experiments were used to define the proven acceptable range and classification of operating parameters for each unit operation. Analysis of variance and Monte Carlo simulation methods were used to assess the appropriateness of process design spaces. Successful implementation and validation of the process in the manufacturing facility and the subsequent manufacture of hundreds of batches of this therapeutic protein verifies the approaches taken as a suitable model for the development, scale-up and operation of any biopharmaceutical manufacturing process.     

Characterization of a Saccharomyces cerevisiae fermentation process for production of a therapeutic recombinant protein using a multivariate Bayesian approach

The principle of quality by design (QbD) has been widely applied to biopharmaceutical manufacturing processes. Process characterization is an essential step to implement the QbD concept to establish the design space and to define the proven acceptable ranges (PAR) for critical process parameters (CPPs). In this study, we present characterization of a Saccharomyces cerevisiae fermentation process using risk assessment analysis, statistical design of experiments (DoE), and the multivariate Bayesian predictive approach. The critical quality attributes (CQAs) and CPPs were identified with a risk assessment. The statistical model for each attribute was established using the results from the DoE study with consideration given to interactions between CPPs. Both the conventional overlapping contour plot and the multivariate Bayesian predictive approaches were used to establish the region of process operating conditions where all attributes met their specifications simultaneously. The quantitative Bayesian predictive approach was chosen to define the PARs for the CPPs, which apply to the manufacturing control strategy. Experience from the 10,000 L manufacturing scale process validation, including 64 continued process verification batches, indicates that the CPPs remain under a state of control and within the established PARs. The end product quality attributes were within their drug substance specifications. The probability generated with the Bayesian approach was also used as a tool to assess CPP deviations. This approach can be extended to develop other production process characterization and quantify a reliable operating region. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:799–812, 2016     

Process Optimization of a Novel Immediate Release Film Coating System using QbD Principles

This work describes a quality-by-design (QbD) approach to determine the optimal coating process conditions and robust process operating space for an immediate release aqueous film coating system (Opadry® 200). Critical quality attributes (CQAs) or associated performance indicators of the coated tablets were measured while coating process parameters such as percent solids of the coating dispersion, coating spray rate, inlet air temperature, airflow rate and pan speed were varied, using a design of experiment protocol. The optimized process parameters were then confirmed by independent coating trials. Disintegration time of coated tablets was not affected by the coating process conditions used in this study, while tablet appearance, as determined by measurement of tablet color, coating defects and gloss was determined to be a CQA. Tablet gloss increased when low spray rate and low percent solids were used, as well as with increased coating pan speed. The study used QbD principles and experimental design models to provide a basis to identify ranges of coating process conditions which afford acceptable product quality. High productivity, color uniformity, and very low defect levels were obtained with Opadry 200 even when using a broad range of coating process conditions.     

Application of Quality by Design to the Process Development of Botanical Drug Products: A Case Study

This paper was designed to assess the value of quality by design (QbD) to improve the manufacturing process understanding of botanical drug products. Ethanol precipitation, a widely used unit operation in the manufacture of botanical drug products was employed to illustrate the use of QbD, taking the process of danshen (the dry root of Salvia miltiorrhiza Bunge) as an example. The recovery of four active pharmaceutical ingredients (APIs) and the removal of saccharides were used to represent the performance of ethanol precipitation. Potentially critical variables, including density of concentrate, ethanol consumption, and settling temperature were identified through risk assessment methods. Design of experiments (DOE) was used to evaluate the effects of the potentially critical factors on the performance of ethanol precipitation. It was observed that higher density of concentrate leads to higher removal of saccharides, but results in lower recovery of APIs. With the rise of ethanol consumption, the recovery of different APIs behaves in different ways. A potential design space of ethanol precipitation operation was established through DOE studies. The results in this work facilitate the enhanced understanding of the relationships between multiple factors (material attributes and process parameters) and the performance of ethanol precipitation. This case study demonstrated that QbD is a powerful tool to develop manufacturing process of botanical drug products.     

Unit Operation Optimization for the Manufacturing of Botanical Injections Using a Design Space Approach: A Case Study of Water Precipitation

Quality by design (QbD) concept is a paradigm for the improvement of botanical injection quality control. In this work, water precipitation process for the manufacturing of Xueshuantong injection, a botanical injection made from Notoginseng Radix et Rhizoma, was optimized using a design space approach as a sample. Saponin recovery and total saponin purity (TSP) in supernatant were identified as the critical quality attributes (CQAs) of water precipitation using a risk assessment for all the processes of Xueshuantong injection. An Ishikawa diagram and experiments of fractional factorial design were applied to determine critical process parameters (CPPs). Dry matter content of concentrated extract (DMCC), amount of water added (AWA), and stirring speed (SS) were identified as CPPs. Box-Behnken designed experiments were carried out to develop models between CPPs and process CQAs. Determination coefficients were higher than 0.86 for all the models. High TSP in supernatant can be obtained when DMCC is low and SS is high. Saponin recoveries decreased as DMCC increased. Incomplete collection of supernatant was the main reason for the loss of saponins. Design space was calculated using a Monte-Carlo simulation method with acceptable probability of 0.90. Recommended normal operation region are located in DMCC of 0.38–0.41 g/g, AWA of 3.7–4.9 g/g, and SS of 280–350 rpm, with a probability more than 0.919 to attain CQA criteria. Verification experiment results showed that operating DMCC, SS, and AWA within design space can attain CQA criteria with high probability.     

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.     

In silico process characterization for biopharmaceutical development following the quality by design concept

With the quality by design (QbD) initiative, regulatory authorities demand a consistent drug quality originating from a well-understood manufacturing process. This study demonstrates the application of a previously published mechanistic chromatography model to the in silico process characterization (PCS) of a monoclonal antibody polishing step. The proposed modeling workflow covered the main tasks of traditional PCS studies following the QbD principles, including criticality assessment of 11 process parameters and establishment of their proven acceptable ranges of operation. Analyzing effects of multi-variate sampling of process parameters on the purification outcome allowed identification of the edge-of-failure. Experimental validation of in silico results demanded approximately 75% less experiments compared to a purely wet-lab based PCS study. Stochastic simulation, considering the measured variances of process parameters and loading material composition, was used to estimate the capability of the process to meet the acceptance criteria for critical quality attributes and key performance indicators. The proposed workflow enables the implementation of digital process twins as QbD tool for improved development of biopharmaceutical manufacturing processes.     

Quality by design approach for viral clearance by protein a chromatography

Protein A chromatography is widely used as a capture step in monoclonal antibody (mAb) purification processes. Antibodies and Fc fusion proteins can be efficiently purified from the majority of other complex components in harvested cell culture fluid (HCCF). Protein A chromatography is also capable of removing modest levels of viruses and is often validated for viral clearance. Historical data mining of Genentech and FDA/CDER databases systematically evaluated the removal of model viruses by Protein A chromatography. First, we found that for each model virus, removal by Protein A chromatography varies significantly across mAbs, while remains consistent within a specific mAb product, even across the acceptable ranges of the process parameters. In addition, our analysis revealed a correlation between retrovirus and parvovirus removal, with retrovirus data generally possessing a greater clearance factor. Finally, we describe a multivariate approach used to evaluate process parameter impacts on viral clearance, based on the levels of retrovirus‐like particles (RVLP) present among process characterization study samples. It was shown that RVLP removal by Protein A is robust, that is, parameter effects were not observed across the ranges tested. Robustness of RVLP removal by Protein A also correlates with that for other model viruses such as X‐MuLV, MMV, and SV40. The data supports that evaluating RVLP removal using process characterization study samples can establish multivariate acceptable ranges for virus removal by the protein A step for QbD. By measuring RVLP instead of a model retrovirus, it may alleviate some of the technical and economic challenges associated with performing large, design‐of‐experiment (DoE)—type virus spiking studies. This approach could also serve to provide useful insight when designing strategies to ensure viral safety in the manufacturing of a biopharmaceutical product. Biotechnol. Bioeng. 2014;111: 95–103. © 2013 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.     

Quality attributes of recombinant therapeutic proteins: an assessment of impact on safety and efficacy as part of a quality by design development approach

Quality by Design (QbD) is a new approach to the development of recombinant therapeutic protein products that promotes a better understanding of the product and its manufacturing process. The first step in the QbD approach consists in identifying the critical quality attributes (CQA), i.e., those quality attributes of the product that have an impact on its clinical efficacy or safety. CQAs are identified through a science-based risk assessment taking into consideration a combination of clinical and nonclinical data obtained with the molecule or other similar molecules or platform products, as well as the published literature. The purpose of this article is to perform a comprehensive review of the published literature, supporting an assessment of the impact on safety and efficacy of the quality attributes commonly encountered in recombinant therapeutic proteins, more specifically those produced in mammalian cell expression systems. Quality attributes generally observed in biopharmaceutical proteins including product-related impurities and substances, process-related impurities, product attributes, and contaminants are evaluated one by one for their impact on biological activity, pharmacokinetics and pharmacodynamics, immunogenicity, and overall safety/toxicity.     

Strategies for developing design spaces for viral clearance by anion exchange chromatography during monoclonal antibody production

The quality‐by‐design (QbD) regulatory initiative promotes the development of process design spaces describing the multidimensional effects and interactions of process variables on critical quality attributes of therapeutic products. However, because of the complex nature of production processes, strategies must be devised to provide for design space development with reasonable allocation of resources while maintaining highly dependable results. Here, we discuss strategies for the determination of design spaces for viral clearance by anion exchange chromatography (AEX) during purification of monoclonal antibodies. We developed a risk assessment for AEX using a formalized method and applying previous knowledge of the effects of certain variables and the mechanism of action for virus removal by this process. We then use design‐of‐experiments (DOE) concepts to perform a highly fractionated factorial experiment and show that varying many process parameters simultaneously over wide ranges does not affect the ability of the AEX process to remove endogenous retrovirus‐like particles from CHO‐cell derived feedstocks. Finally, we performed a full factorial design and observed that a high degree of viral clearance was obtained for three different model viruses when the most significant process parameters were varied over ranges relevant to typical manufacturing processes. These experiments indicate the robust nature of viral clearance by the AEX process as well as the design space where removal of viral impurities and contaminants can be assured. In addition, the concepts and methodology presented here provides a general approach for the development of design spaces to assure that quality of biotherapeutic products is maintained. © 2010 American Institute of Chemical Engineers Biotechnol. Prog., 2010     

Towards the implementation of quality by design to the production of therapeutic monoclonal antibodies with desired glycosylation patterns

Quality by design (QbD) is a scheme for the development, manufacture, and approval of pharmaceutical products. The end goal of QbD is to ensure product quality by building it into the manufacturing process. The main regulatory bodies are encouraging its implementation to the manufacture of all new pharmaceuticals including biological products. Monoclonal antibodies (mAbs) are currently the leading products of the biopharmaceutical industry. It has been widely reported that glycosylation directly influences the therapeutic mechanisms by which mAbs function in vivo. In addition, glycosylation has been identified as one of the main sources of monoclonal antibody heterogeneity, and thus, a critical parameter to follow during mAb manufacture. This article reviews the research on glycosylation of mAbs over the past 2 decades under the QbD scope. The categories presented under this scope are: (a) definition of the desired clinical effects of mAbs, (b) definition of the glycosylation‐associated critical quality attributes (glycCQAs) of mAbs, (c) assessment of process parameters that pose a risk for mAb glycCQAs, and (d) methods for accurately quantifying glycCQAs of mAbs. The information available in all four areas leads us to conclude that implementation of QbD to the manufacture of mAbs with specific glycosylation patterns will be a reality in the near future. We also foresee that the implementation of QbD will lead to the development of more robust and efficient manufacturing processes and to a new generation of mAbs with increased clinical efficacy. © 2010 American Institute of Chemical Engineers Biotechnol. Prog., 2010     

Process development for robust removal of aggregates using cation exchange chromatography in monoclonal antibody purification with implementation of quality by design

Aggregate removal is one of the most important aspects in monoclonal antibody (mAb) purification. Cation-exchange chromatography (CEX), a widely used polishing step in mAb purification, is able to clear both process-related impurities and product-related impurities. In this study, with the implementation of quality by design (QbD), a process development approach for robust removal of aggregates using CEX is described. First, resin screening studies were performed and a suitable CEX resin was chosen because of its relatively better selectivity and higher dynamic binding capacity. Second, a pH-conductivity hybrid gradient elution method for the CEX was established, and the risk assessment for the process was carried out. Third, a process characterization study was used to evaluate the impact of the potentially important process parameters on the process performance with respect to aggregate removal. Accordingly, a process design space was established. Aggregate level in load is the critical parameter. Its operating range is set at 0-3% and the acceptable range is set at 0-5%. Equilibration buffer is the key parameter. Its operating range is set at 40 ± 5 mM acetate, pH 5.0 ± 0.1, and acceptable range is set at 40 ± 10 mM acetate, pH 5.0 ± 0.2. Elution buffer, load mass, and gradient elution volume are non-key parameters; their operating ranges and acceptable ranges are equally set at 250 ± 10 mM acetate, pH 6.0 ± 0.2, 45 ± 10 g/L resin, and 10 ± 20% CV respectively. Finally, the process was scaled up 80 times and the impurities removal profiles were revealed. Three scaled-up runs showed that the size-exclusion chromatography (SEC) purity of the CEX pool was 99.8% or above and the step yield was above 92%, thereby proving that the process is both consistent and robust.     

Using Manufacturing Design Space Concepts for Stability Risk Assessment—Gabapentin NIPTE/FDA Case Study

A quantitative, model-based risk assessment process was evaluated using Bayesian parameter estimation to determine the posterior distribution of the probability of a model tablet formulation’s (gabapentin) ability to meet end-of-expiry stability criteria-based manufacturing controls. Experimental data was obtained from an FDA-supported, multi-year project that involved researchers at nine universities working collaboratively with industrial and governmental scientists under the leadership of the National Institute for Pharmaceutical Technology and Education (NITPE). The risk assessment process involved the development of a design space manufacturing model and shelf life stability model that shared stability-related critical quality attributes (CQAs). Monte Carlo simulations of the design space and shelf life models that uses model parameter uncertainty to estimate the probability of shelf life failure as a function of manufacturing control. The resultant linked design space and shelf life stability models were tested by comparing model predicted and observed long-term stability data generated under a variety of pilot scale production conditions.     

Quality by Design and Process Analytical Technology for Sterile Products—Where Are We Now?

Quality by design (QbD) and process analytical technology (PAT) have become priorities for the Center for Drug Evaluation and Research (CDER) at the Food and Drug Administration (FDA). Numerous recent initiatives within CDER and FDA have had the objective of encouraging the pharmaceutical industry to utilize QbD and PAT in their product development and manufacturing processes. Although sterile products may be a minority compared to non-sterile dosage forms (e.g., solid orals), their absolute requirement for sterility make design and control of the manufacturing processes extremely critical. This emphasis on the manufacturing process makes the sterile drug product an obvious target for QbD and PAT. Although the FDA encourages QbD submissions, the utilization of QbD and PAT for sterile products so far is still limited. This paper will examine the present state of QbD and PAT for sterile products and review some examples currently in use. Additional potential applications of QbD and PAT for sterile product development and manufacturing will also be discussed.     

Characterizing the effect of multiple Fc glycan attributes on the effector functions and FcγRIIIa receptor binding activity of an IgG1 antibody

N‐linked Fc glycosylation of IgG1 monoclonal antibody therapeutics can directly influence their mechanism of action by impacting IgG effector functions such as antibody‐dependent cell‐mediated cytotoxicity (ADCC) and complement‐dependent cytotoxicity (CDC). Therefore, identification and detailed characterization of Fc glycan critical quality attributes (CQAs) provides important information for process design and control. A two‐step approach was used to identify and characterize the Fc glycan CQAs for an IgG1 Mab with effector function. First, single factor experiments were performed to identify glycan critical quality attributes that influence ADCC and CDC activities. Next, a full‐factorial design of experiment (DOE) to characterize the possible interactions and relative effect of these three glycan species on ADCC, CDC, and FcγRIIIa binding was employed. Additionally, the DOE data were used to develop models to predict ADCC, CDC, and FcγRIIIa binding of a given configuration of the three glycan species for this IgG1 molecule. The results demonstrate that for ADCC, afuco mono/bi has the largest effect, followed by HM and β‐gal, while FcγRIIIa binding is affected by afuco mono/bi and β‐gal. CDC, in contrast, is affected by β‐gal only. This type of glycan characterization and modeling can provide valuable information for development, manufacturing support and process improvements for IgG products that require effector function for efficacy. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1181–1192, 2016     

Quality by Design I: Application of Failure Mode Effect Analysis (FMEA) and Plackett–Burman Design of Experiments in the Identification of “Main Factors” in the Formulation and Process Design Space for Roller-Compacted Ciprofloxacin Hydrochloride Immediate-Release Tablets

As outlined in the ICH Q8(R2) guidance, identifying the critical quality attributes (CQA) is a crucial part of dosage form development; however, the number of possible formulation and processing factors that could influence the manufacturing of a pharmaceutical dosage form is enormous obviating formal study of all possible parameters and their interactions. Thus, the objective of this study is to examine how quality risk management can be used to prioritize the number of experiments needed to identify the CQA, while still maintaining an acceptable product risk profile. To conduct the study, immediate-release ciprofloxacin tablets manufactured via roller compaction were used as a prototype system. Granules were manufactured using an Alexanderwerk WP120 roller compactor and tablets were compressed on a Stokes B2 tablet press. In the early stages of development, prior knowledge was systematically incorporated into the risk assessment using failure mode and effect analysis (FMEA). The factors identified using FMEA were then followed by a quantitative assessed using a Plackett–Burman screening design. Results show that by using prior experience, literature data, and preformulation data the number of experiments could be reduced to an acceptable level, and the use of FMEA and screening designs such as the Plackett Burman can rationally guide the process of reducing the number experiments to a manageable level.KEY WORDS: failure mode effect analysis (FMEA), Plackett–Burman, quality by design (QbD), quality risk management, roller compaction, tablet and ciprofloxacin     

Optimization of the Ethanol Recycling Reflux Extraction Process for Saponins Using a Design Space Approach

A solvent recycling reflux extraction process for Panax notoginseng was optimized using a design space approach to improve the batch-to-batch consistency of the extract. Saponin yields, total saponin purity, and pigment yield were defined as the process critical quality attributes (CQAs). Ethanol content, extraction time, and the ratio of the recycling ethanol flow rate and initial solvent volume in the extraction tank (RES) were identified as the critical process parameters (CPPs) via quantitative risk assessment. Box-Behnken design experiments were performed. Quadratic models between CPPs and process CQAs were developed, with determination coefficients higher than 0.88. As the ethanol concentration decreases, saponin yields first increase and then decrease. A longer extraction time leads to higher yields of the ginsenosides Rb₁ and Rd. The total saponin purity increases as the ethanol concentration increases. The pigment yield increases as the ethanol concentration decreases or extraction time increases. The design space was calculated using a Monte-Carlo simulation method with an acceptable probability of 0.90. Normal operation ranges to attain process CQA criteria with a probability of more than 0.914 are recommended as follows: ethanol content of 79–82%, extraction time of 6.1–7.1 h, and RES of 0.039–0.040 min⁻¹. Most of the results of the verification experiments agreed well with the predictions. The verification experiment results showed that the selection of proper operating ethanol content, extraction time, and RES within the design space can ensure that the CQA criteria are met.     

Current challenges and recent advances on the path towards continuous biomanufacturing

Continuous biopharmaceutical manufacturing is currently a field of intense research due to its potential to make the entire production process more optimal for the modern, ever-evolving biopharmaceutical market. Compared to traditional batch manufacturing, continuous bioprocessing is more efficient, adjustable, and sustainable and has reduced capital costs. However, despite its clear advantages, continuous bioprocessing is yet to be widely adopted in commercial manufacturing. This article provides an overview of the technological roadblocks for extensive adoptions and points out the recent advances that could help overcome them. In total, three key areas for improvement are identified: Quality by Design (QbD) implementation, integration of upstream and downstream technologies, and data and knowledge management. First, the challenges to QbD implementation are explored. Specifically, process control, process analytical technology (PAT), critical process parameter (CPP) identification, and mathematical models for bioprocess control and design are recognized as crucial for successful QbD realizations. Next, the difficulties of end-to-end process integration are examined, with a particular emphasis on downstream processing. Finally, the problem of data and knowledge management and its potential solutions are outlined where ontologies and data standards are pointed out as key drivers of progress.     

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.