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 Monoclonal Antibody Cell Culture Production Process Using a Quality by Design Approach

The goal of quality by design (QbD) in cell culture manufacturing is to develop manufacturing processes which deliver products with consistent critical quality attributes (CQAs). QbD approaches can lead to better process understanding through the use of process parameter risk ranking and statistical design of experiments (DOE). The QbD process starts with an analysis of process parameter risk with respect to CQAs and key performance indicators (KPIs). Initial DOE study designs and their factor test ranges are based on the outcomes of the process parameter risk ranking exercises. Initial DOE studies screen factors for significant influences on CQAs as well as characterize responses for process KPIs. In the case study provided here, multifactor process characterization studies using a scale-down model resulted in significant variation in charge heterogeneity of a monoclonal antibody (MAb) as measured by ion-exchange chromatography (IEC). Iterative DOE studies, using both screening and response surface designs, were used to narrow the operating parameter ranges so that charge heterogeneity could be controlled to an acceptable level. The data from the DOE studies were used to predict worst-case conditions, which were then verified by testing at those conditions. Using the approach described here, multivariate process parameter ranges were identified that yield acceptable CQA levels and that still provide operational flexibility for manufacturing.     

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     

Application of QbD Principles for the Evaluation of Empty Hard Capsules as an Input Parameter in Formulation Development and Manufacturing

Understanding the product and process variable on the final product performance is an essential part of the quality-by-design (QbD) principles in pharmaceutical development. The hard capsule is an established pharmaceutical dosage form used worldwide in development and manufacturing. The empty hard capsules are supplied as an excipient that is filled by pharmaceutical manufacturers with a variety of different formulations and products. To understand the potential variations of the empty hard capsules as an input parameter and its potential impact on the finished product quality, a study was performed investigating the critical quality parameters within and in between different batches of empty hard gelatin capsules. The variability of the hard capsules showed high consistency within the specification of the critical quality parameters. This also accounts for the disintegration times, when automatic endpoint detection was used. Based on these data, hard capsules can be considered as a suitable excipient for product development using QbD principles.     

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     

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.     

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.     

Implementation of quality by design toward processing of food products

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

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.     

Straightforward method for calibration of mechanistic cation exchange chromatography models for industrial applications

Mechanistic modeling of chromatography processes is one of the most promising techniques for the digitalization of biopharmaceutical process development. Possible applications of chromatography models range from in silico process optimization in early phase development to in silico root cause investigation during manufacturing. Nonetheless, the cumbersome and complex model calibration still decelerates the implementation of mechanistic modeling in industry. Therefore, the industry demands model calibration strategies that ensure adequate model certainty in a limited amount of time. This study introduces a directed and straightforward approach for the calibration of pH-dependent, multicomponent steric mass action (SMA) isotherm models for industrial applications. In the case investigated, the method was applied to a monoclonal antibody (mAb) polishing step including four protein species. The developed strategy combined well-established theories of preparative chromatography (e.g. Yamamoto method) and allowed a systematic reduction of unknown model parameters to 7 from initially 32. Model uncertainty was reduced by designing two representative calibration experiments for the inverse estimation of remaining model parameters. Dedicated experiments with aggregate-enriched load material led to a significant reduction of model uncertainty for the estimates of this low-concentrated product-related impurity. The model was validated beyond the operating ranges of the final unit operation, enabling its application to late-stage downstream process development. With the proposed model calibration strategy, a systematic experimental design is provided, calibration effort is strongly reduced, and local minima are avoided.     

High-throughput process development for biopharmaceutical drug substances

Quality by Design (QbD) is gaining industry acceptance as an approach towards development and commercialization of biotechnology therapeutic products that are expressed via microbial or mammalian cell lines. In QbD, the process is designed and controlled to deliver specified quality attributes consistently. To acquire the enhanced understanding that is necessary to achieve the above, however, requires more extensive experimentation to establish the design space for the process and the product. With biotechnology companies operating under ever-increasing pressure towards lowering the cost of manufacturing, the use of high-throughput tools has emerged as a necessary enabler of QbD in a time- and resource-constrained environment. We review this topic for those in academia and industry that are engaged in drug substance process development.     

Process intensification in peptide manufacturing: Recombinant lethal toxin neutralizing factor (rLTNF) as a case study

Process intensification is necessary to create economical processes. Cleavage reaction is one of the critical unit operations in peptide manufacturing processes as it involves cutting of concatemer expressed to obtain monomer. In this paper, solubilization and cleavage reaction have been merged into a single unit operation so as to allow for simultaneous solubilization and cleavage. Critical variables such as urea concentration, calcium chloride concentration, pH, and enzyme loading were optimized using quality by design (QbD) principles. The subsequent RP-HPLC unit operation was also intensified with respect to elution gradient and product stability in elution buffer so as to facilitate direct freeze-drying and storage. The proposed three-step process was analysed for its economics and compared with the previous generation process, showing significant improvements including a 21% reduction in batch time, 27% increase in productivity, and 30% reduction in manufacturing cost. The work illustrates the effectiveness of applying QbD principles and process intensification for creation of a more efficient manufacturing bioprocess.     

Integrating Artificial and Human Intelligence into Tablet Production Process

We developed a new machine learning-based method in order to facilitate the manufacturing processes of pharmaceutical products, such as tablets, in accordance with the Process Analytical Technology (PAT) and Quality by Design (QbD) initiatives. Our approach combines the data, available from prior production runs, with machine learning algorithms that are assisted by a human operator with expert knowledge of the production process. The process parameters encompass those that relate to the attributes of the precursor raw materials and those that relate to the manufacturing process itself. During manufacturing, our method allows production operator to inspect the impacts of various settings of process parameters within their proven acceptable range with the purpose of choosing the most promising values in advance of the actual batch manufacture. The interaction between the human operator and the artificial intelligence system provides improved performance and quality. We successfully implemented the method on data provided by a pharmaceutical company for a particular product, a tablet, under development. We tested the accuracy of the method in comparison with some other machine learning approaches. The method is especially suitable for analyzing manufacturing processes characterized by a limited amount of data.KEY WORDS: artificial intelligence, machine learning, process analytical technology, process optimization, tablet manufacture     

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     

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.     

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.     

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.     

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.     

Application of Quality by Design (QbD) Approach to Ultrasonic Atomization Spray Coating of Drug-Eluting Stents

The drug coating process for coated drug-eluting stents (DES) has been identified as a key source of inter- and intra-batch variability in drug elution rates. Quality-by-design (QbD) principles were applied to gain an understanding of the ultrasonic spray coating process of DES. Statistically based design of experiments (DOE) were used to understand the relationship between ultrasonic atomization spray coating parameters and dependent variables such as coating mass ratio, roughness, drug solid state composite microstructure, and elution kinetics. Defect-free DES coatings composed of 70% 85:15 poly(dl-lactide-co-glycolide) and 30% everolimus were fabricated with a constant coating mass. The drug elution profile was characterized by a mathematical model describing biphasic release kinetics. Model coefficients were analyzed as a DOE response. Changes in ultrasonic coating processing conditions resulted in substantial changes in roughness and elution kinetics. Based on the outcome from the DOE study, a design space was defined in terms of the critical coating process parameters resulting in optimum coating roughness and drug elution. This QbD methodology can be useful to enhance the quality of coated DES.KEY WORDS: biodegradable polymers, coating, drug-eluting stents, processing, quality by design