Pharmaceutical Quality by Design: Product and Process Development, Understanding, and Control

PURPOSE: The purpose of this paper is to discuss the pharmaceutical Quality by Design (QbD) and describe how it can be used to ensure pharmaceutical quality. MATERIALS AND METHODS: The QbD was described and some of its elements identified. Process parameters and quality attributes were identified for each unit operation during manufacture of solid oral dosage forms. The use of QbD was contrasted with the evaluation of product quality by testing alone. RESULTS: The QbD is a systemic approach to pharmaceutical development. It means designing and developing formulations and manufacturing processes to ensure predefined product quality. Some of the QbD elements include: Defining target product quality profile; Designing product and manufacturing processes; Identifying critical quality attributes, process parameters, and sources of variability; Controlling manufacturing processes to produce consistent quality over time. CONCLUSIONS: Using QbD, pharmaceutical quality is assured by understanding and controlling formulation and manufacturing variables. Product testing confirms the product quality. Implementation of QbD will enable transformation of the chemistry, manufacturing, and controls (CMC) review of abbreviated new drug applications (ANDAs) into a science-based pharmaceutical quality assessment.     

智能制造理念在血液制品产业的应用研究

目的：通过分析智能制造理念下,质量源于设计（quality by design,QbD）与血液制品生产的相关性、过程分析技术（process analytical technology,PAT）在血液制品QbD中的应用以及关键质量环节的QbD实施,以期推动我国血液制品行业升级,实现血液制品的智能生产。方法：采取前瞻性研究方法,查阅、检索以"智能制造" "血液制品" "质量源于设计"过程分析技术"为关键词的文献,对智能制造理念在血液制品的应用研究进行论述。结果与结论：基于我国制药工业的自动化与信息化的水平与现状,制药工业的"智能制造"已逐步发展起来,QbD已被引入我国新版药品GMP,强调了与药品注册、上市制度的有效衔接。在科学监管的要求下,QbD理念已成为血液制品行业界的共识,实施QbD,通过基于问题的审核（question-based review,QbR）,将有助于全面提高我国血液制品的质量,提升产品的竞争力。     

Understanding Pharmaceutical Quality by Design

This review further clarifies the concept of pharmaceutical quality by design (QbD) and describes its objectives. QbD elements include the following: (1) a quality target product profile (QTPP) that identifies the critical quality attributes (CQAs) of the drug product; (2) product design and understanding including identification of critical material attributes (CMAs); (3) process design and understanding including identification of critical process parameters (CPPs), linking CMAs and CPPs to CQAs; (4) a control strategy that includes specifications for the drug substance(s), excipient(s), and drug product as well as controls for each step of the manufacturing process; and (5) process capability and continual improvement. QbD tools and studies include prior knowledge, risk assessment, mechanistic models, design of experiments (DoE) and data analysis, and process analytical technology (PAT). As the pharmaceutical industry moves toward the implementation of pharmaceutical QbD, a common terminology, understanding of concepts and expectations are necessary. This understanding will facilitate better communication between those involved in risk-based drug development and drug application review.     

Advancing Product Quality: a Summary of the Inaugural FDA/PQRI Conference

On September 16 and 17, 2014, the Food and Drug Administration (FDA) and Product Quality Research Institute (PQRI) inaugurated their Conference on Evolving Product Quality. The Conference is conceived as an annual forum in which scientists from regulatory agencies, industry, and academia may exchange viewpoints and work together to advance pharmaceutical quality. This Conference Summary Report highlights key topics of this conference, including (1) risk-based approaches to pharmaceutical development, manufacturing, regulatory assessment, and post-approval changes; (2) FDA-proposed quality metrics for products, facilities, and quality management systems; (3) performance-based quality assessment and clinically relevant specifications; (4) recent developments and implementation of continuous manufacturing processes, question-based review, and European Medicines Agency (EMA)-FDA pilot for Quality-by-Design (QbD) applications; and (5) breakthrough therapies, biosimilars, and international harmonization, focusing on ICH M7 and Q3D guidelines. The second FDA/PQRI conference on advancing product quality is planned for October 5–7, 2015.     

Quality by design (QbD) approaches in current pharmaceutical set-up

Introduction: Quality by design (QbD) encourages the pharmaceutical industry to use risk management and science-based manufacturing principles to gain process and product understanding and thus assures quality of the product. With the objective to curb the rising costs for development and regulatory barriers to innovation and creativity, QbD is being widely promoted by Food and Drug Administration (FDA) and International Conference on Harmonization (ICH).

Areas covered: This review describes the elements, different design and tools of QbD as well as multidimensional applications of QbD ranging from dosage form and method development to meeting latest regulatory requirements.

Expert opinion: The understanding of a process is facilitated by proper identification of sources of variation, management of variability by process design, and prediction of product quality attributes using design space. The pharmaceutical industry is rapidly adopting the QbD principles for fabrication of safe, effective and quality products; however, we are still on a journey and the process of gathering all experience and metrics required for connecting and demonstrating QbD benefits to all stakeholders is still in progress. Understanding the formulation and process parameters with the philosophy of QbD will be useful for the optimization of complex drug delivery systems in the near future.     

Misunderstanding <Emphasis Type="Italic">Design Space</Emphasis>: a Robust Drug Product Control Strategy Is the Key to Quality Assurance

ICH guidelines Q8/11, Q9, and Q10 introduced risk-based approaches and enhanced scientific understanding as an opportunity to encourage continuous process improvement for pharmaceutical manufacturing. Conceptually, Quality by Design (QbD) promised to improve confidence in quality through the lifecycle of pharmaceutical products. A primary incentive for industry is the prospect of global regulatory concordance for new applications and post approval changes. Unfortunately, during the last decade, the industry has experienced regulatory divergence regarding the interpretation of ICH guidelines across geographic regions. Rather than truly harmonized regulatory expectations, localized interpretations of ICH guidance have resulted in different technical requirements posing significant challenges for a global industry. As a result, the increased complexity of manufacturing supply chains and the regulatory burden associated with maintaining compliance with these diverse regulatory expectations serves as a barrier to continual improvement and innovation. The QbD paradigm has effectively demonstrated a risk-based link between a product’s control strategy and patient needs that has prompted meaningful improvement in the industry’s approach to product quality assurance. Divergent interpretations of the concepts and definitions used in the modern QbD approach to product development and manufacturing, however, has led to challenges in achieving a common implementation of design space, control strategy, prior knowledge, proven acceptable range, and normal operating range. While the concept of design space remains an appealing focal point for demonstrating process understanding, the authors suggest that Control Strategy is the most important QbD concept, and one that assures product quality for patients. A focus by both regulators and manufacturers on the significance of Control Strategy could facilitate management of post approval changes to improve manufacturing processes and enhance product quality while also engendering regulatory harmonization.     

A Tutorial for Developing a Topical Cream Formulation Based on the Quality by Design Approach

The pharmaceutical industry has entered in a new era, as there is a growing interest in increasing the quality standards of dosage forms, through the implementation of more structured development and manufacturing approaches. For many decades, the manufacturing of drug products was controlled by a regulatory framework to guarantee the quality of the final product through a fixed process and exhaustive testing. Limitations related to the Quality by Test system have been widely acknowledged. The emergence of Quality by Design (QbD) as a systematic and risk-based approach introduced a new quality concept based on a good understanding of how raw materials and process parameters influence the final quality profile. Although the QbD system has been recognized as a revolutionary approach to product development and manufacturing, its full implementation in the pharmaceutical field is still limited. This is particularly evident in the case of semisolid complex formulation development. The present review aims at establishing a practical QbD framework to describe all stages comprised in the pharmaceutical development of a conventional cream in a comprehensible manner.     

Overcoming Inherent Limits to Pharmaceutical Manufacturing Quality Performance with QbD (Quality by Design)

Pharmaceutical development and manufacturing systems typically rely on a Quality by Testing (QbT) model that use release testing and other measures to ensure product quality. However, there is a significant gap between typical pharmaceutical production system capability and supplied quality. To sustain high levels of product supply quality, the industry incurs a high cost of quality and retains value at risk. This paper presents research results from a systems engineering perspective using case study data that quantitatively evaluates the gap between pharmaceutical production system sigma and supplied quality. It also identifies the extent to which emerging Quality by Design (QbD) eliminates system contradictions that prohibit higher production system sigma performance.     

API Quality by Design Example from the Torcetrapib Manufacturing Process

The concept and application of quality by design (QbD) principles has been and will undoubtedly continue to be an evolving topic in the pharmaceutical industry. However, there are few and limited examples that demonstrate the actual practice of incorporating QbD assessments, especially for active pharmaceutical ingredients (API) manufacturing processes described in regulatory submissions. We recognize there are some inherent and fundamental differences in developing QbD approaches for drug substance (or API) vs drug product manufacturing processes. In particular, the development of relevant process understanding for API manufacturing is somewhat challenging relative to criteria outlined in ICH Q8 (http://www.ich.org/cache/compo/276–254–1.html) guidelines, which are primarily oriented toward application of QbD for drug product manufacturing. This position paper provides a perspective of QbD application for API manufacture using an example from the torcetrapib API manufacturing process. The work includes a risk assessment, examples of multivariate design, and a proposed criticality assessment, all of which coalesce into an example of design space. Torcetrapib was a project in phase III development as a potent and selective inhibitor of cholesteryl ester transfer protein before being terminated in late 2006. The intent of Pfizer was to submit torcetrapib under the QbD paradigm (route selection, robustness, and reagent/solvent selection during phases I to III are significantly important in establishing a manufacturing process that would have the most flexibility in the final design space. For more information on this development phase for torcetrapib see Damon et al., Org Process Res Dev, 10(3):464–71, 2006, Org Process Res Dev, 10(3):472–80, 2006).     

The Impact of Product and Process Related Critical Quality Attributes on Immunogenicity and Adverse Immunological Effects of Biotherapeutics

The pharmaceutical industry has experienced great successes with protein therapeutics in the last two decades and with novel modalities, including cell therapies and gene therapies, more recently. Biotherapeutics are complex in structure and present challenges for discovery, development, regulatory, and life cycle management. Biotherapeutics can interact with the immune system that may lead to undesired immunological responses, including immunogenicity, hypersensitivity reactions (HSR), injection site reactions (ISR), and others. Many product and process related critical quality attributes (CQAs) have the potential to trigger or augment such immunological responses to the product. Tremendous efforts, both clinically and preclinically, have been invested to understand the impact of product and process related CQAs on adverse immunological effects. The information and knowledge are critical for the implementation of Quality by Design (QbD), which requires risk assessment and establishment of specifications and control strategies for CQAs. A quality target product profile (QTPP) that identifies the key CQAs through process development can help assign severity scores based on safety, immunogenicity, pharmacokinetics (PK) and pharmacodynamics (PD) of the molecule. Gaps and future directions related to biotherapeutics and emerging novel modalities are presented.     

A quality by design approach using artificial intelligence techniques to control the critical quality attributes of ramipril tablets manufactured by wet granulation

Quality by design (QbD) is an essential part of the modern approach to pharmaceutical quality. This study was conducted in the framework of a QbD project involving ramipril tablets. Preliminary work included identification of the critical quality attributes (CQAs) and critical process parameters (CPPs) based on the quality target product profiles (QTPPs) using the historical data and risk assessment method failure mode and effect analysis (FMEA). Compendial and in-house specifications were selected as QTPPs for ramipril tablets. CPPs that affected the product and process were used to establish an experimental design. The results thus obtained can be used to facilitate definition of the design space using tools such as design of experiments (DoE), the response surface method (RSM) and artificial neural networks (ANNs). The project was aimed at discovering hidden knowledge associated with the manufacture of ramipril tablets using a range of artificial intelligence-based software, with the intention of establishing a multi-dimensional design space that ensures consistent product quality. At the end of the study, a design space was developed based on the study data and specifications, and a new formulation was optimized. On the basis of this formulation, a new laboratory batch formulation was prepared and tested. It was confirmed that the explored formulation was within the design space.     

模型设计在制剂研发及生产过程质量控制中的应用

“质量源于设计”概念的提出,将药品的质量控制从生产过程扩展至整个药品生命周期中,而这一概念的核心便是模型设计。介绍模型设计在制剂研发和及生产过程工艺阶段质量控制中的应用情况及模型建立的原理和模型预测结果,并结合笔者所在实验室的模型预测结果,对模型设计在制剂研发生产过程质量控制中的应用进行了评价和展望。     

Quality by design approach for formulation development: a case study of dispersible tablets

The focus of the current investigations was to apply quality by design (QbD) approach to the development of dispersible tablets. Critical material and process parameters are linked to the critical quality attributes of the product. Variability is reduced by product and process understanding which translates into quality improvement, risk reduction and productivity enhancement. The risk management approach further leads to better understanding of the risks, ways to mitigate them and control strategy is proposed commensurate with the level of the risk. Design space in combination with pharmaceutical quality management system provide for flexible regulatory approaches with opportunity for continuous improvement that benefit patient and manufacturer alike. The development of dispersible tablet was proposed in the current study through a QbD paradigm for a better patient compliance and product quality. The quality target product profile of a model biopharmaceutical class II drug was identified. Initial risk analysis led to the identification of the critical quality attributes. Physicochemical characterization and compatibility studies of the drug with commonly used excipients were performed. Experiments were designed with focus on critical material and process attributes. Design space was identified and risk factors for all the possible failure modes were below critical levels after the implementation of control strategy. Compliance to the design space provides an opportunity to release batches in a real time. In conclusion, QbD tools together with risk and quality management tools provided an effective and efficient paradigm to build the quality into dispersible tablet.     

Analytical Procedure Validation and the Quality by Design Paradigm

Since the adoption of the ICH Q8 document concerning the development of pharmaceutical processes following a quality by design (QbD) approach, there have been many discussions on the opportunity for analytical procedure developments to follow a similar approach. While development and optimization of analytical procedure following QbD principles have been largely discussed and described, the place of analytical procedure validation in this framework has not been clarified. This article aims at showing that analytical procedure validation is fully integrated into the QbD paradigm and is an essential step in developing analytical procedures that are effectively fit for purpose. Adequate statistical methodologies have also their role to play: such as design of experiments, statistical modeling, and probabilistic statements. The outcome of analytical procedure validation is also an analytical procedure design space, and from it, control strategy can be set.     

A Quality By Design Approach For Longitudinal Quality Attributes

The concept of quality by design (QbD) as published in ICH-Q8 is currently one of the most recurrent topics in the pharmaceutical literature. This guideline recommends the use of information and prior knowledge gathered during pharmaceutical development studies to provide a scientific rationale for the manufacturing process of a product and provide guarantee of future quality. This poses several challenges from a statistical standpoint and requires a shift in paradigm from traditional statistical practices. First, to provide “assurance of quality” of future lots implies the need to make predictions regarding the quality given past evidence and data. Second, the quality attributes described in the Q8 guidelines are not always a set of unique, independent measurements. In many cases, these criteria are complicated longitudinal data with successive acceptance criteria over a defined period of time. A common example is a dissolution profile for a modified or extended-release solid dosage form that must fall within acceptance limits at several time points. A Bayesian approach for longitudinal data obtained in various conditions of a design of experiment is provided to elegantly address the ICH-Q8 recommendation to provide assurance of quality and derive a scientifically sound design space.     

A Quality by Design Approach to Developing and Manufacturing Polymeric Nanoparticle Drug Products

The translation of nanomedicines from concepts to commercial products has not reached its full potential, in part because of the technical and regulatory challenges associated with chemistry, manufacturing, and controls (CMC) development of such complex products. It is critical to take a quality by design (QbD) approach to developing nanomedicines—using a risk-based approach to identifying and classifying product attributes and process parameters and ultimately developing a deep understanding of the products, processes, and platform. This article exemplifies a QbD approach used by BIND Therapeutics, Inc., to industrialize a polymeric targeted nanoparticle drug delivery platform. The focus of the approach is on CMC affairs but consideration is also given to preclinical, clinical, and regulatory aspects of pharmaceutical development. Processes are described for developing a quality target product profile and designing supporting preclinical studies, defining critical quality attributes and process parameters, building a process knowledge map, and employing QbD to support outsourced manufacturing.     

Application of Quality by Design Principles to Legacy Drug Products

The concept of Quality by Design (QbD) is of paramount importance in designing and developing reproducible and robust drug products, processes and analytical methods, thus enabling regulatory compliance and ensuring manufacturability. Risk assessment, design space, and control strategy constitute the key elements of the QbD framework. In this paper, a data-based approach to developing robust pharmaceutical processes is presented and illustrated with an application to a drug product during a site transfer process. The key objective in applying QbD principles is to ensure that the product is designed and manufactured to consistently meet quality requirements. The approach presented simultaneously considers the variability in raw materials, quality critical process parameters and critical quality attributes. By nature, large historical databases of raw material (active ingredients and excipients) and process data exists for legacy products. Multivariate statistical models were employed to extract knowledge on critical variables. Furthermore, a number of design of experiments (DOE) were performed in the joint space of the raw materials and the manipulated process variables to develop the design space and control strategy with feedback control. The result was a joint space that combines the interaction of all the input variables such as raw materials and process parameters that have been proven to provide high quality. Throughout this paper, the use of multivariate statistical analysis and DOE and how they are applied to define meaningful raw materials specification and design space to achieve QbD are discussed.     

Clinical Relevance of Dissolution Testing in Quality by Design

Quality by design (QbD) has recently been introduced in pharmaceutical product development in a regulatory context and the process of implementing such concepts in the drug approval process is presently on-going. This has the potential to allow for a more flexible regulatory approach based on understanding and optimisation of how design of a product and its manufacturing process may affect product quality. Thus, adding restrictions to manufacturing beyond what can be motivated by clinical quality brings no benefits but only additional costs. This leads to a challenge for biopharmaceutical scientists to link clinical product performance to critical manufacturing attributes. In vitro dissolution testing is clearly a key tool for this purpose and the present bioequivalence guidelines and biopharmaceutical classification system (BCS) provides a platform for regulatory applications of in vitro dissolution as a marker for consistency in clinical outcomes. However, the application of these concepts might need to be further developed in the context of QbD to take advantage of the higher level of understanding that is implied and displayed in regulatory documentation utilising QbD concepts. Aspects that should be considered include identification of rate limiting steps in the absorption process that can be linked to pharmacokinetic variables and used for prediction of bioavailability variables, in vivo relevance of in vitro dissolution test conditions and performance/interpretation of specific bioavailability studies on critical formulation/process variables. This article will give some examples and suggestions how clinical relevance of dissolution testing can be achieved in the context of QbD derived from a specific case study for a BCS II compound.     

Minimisation of the capping tendency by tableting process optimisation with the application of artificial neural networks and fuzzy models

The pharmaceutical industry is increasingly aware of the advantages of implementing a quality-by-design (QbD) principle, including process analytical technology, in drug development and manufacturing. Although the implementation of QbD into product development and manufacturing inevitably requires larger resources, both human and financial, large-scale production can be established in a more cost-effective manner and with improved efficiency and product quality. The objective of the present work was to study the influence of particle size (and indirectly, the influence of dry granulation process) and the settings of the tableting parameters on the tablet capping tendency. Artificial neural network and fuzzy models were used for modelling the effect of the particle size and the tableting machine settings on the capping coefficient. The suitability of routinely measured quantities for the prediction of tablet quality was tested. Results showed that model-based expert systems based on the contemporary routinely measured quantities can significantly improve the trial-and-error procedures; however, they cannot completely replace them. The modelling results also suggest that in cases where it is not possible to obtain sufficient number of measurements to uniquely identify the model, it is beneficial to use several modelling techniques to identify the quality of model prediction.     

Meeting Report: Applied Biopharmaceutics and Quality by Design for Dissolution/Release Specification Setting: Product Quality for Patient Benefit

A biopharmaceutics and Quality by Design (QbD) conference was held on June 10–12, 2009 in Rockville, Maryland, USA to provide a forum and identify approaches for enhancing product quality for patient benefit. Presentations concerned the current biopharmaceutical toolbox (i.e., in vitro, in silico, pre-clinical, in vivo, and statistical approaches), as well as case studies, and reflections on new paradigms. Plenary and breakout session discussions evaluated the current state and envisioned a future state that more effectively integrates QbD and biopharmaceutics. Breakout groups discussed the following four topics: Integrating Biopharmaceutical Assessment into the QbD Paradigm, Predictive Statistical Tools, Predictive Mechanistic Tools, and Predictive Analytical Tools. Nine priority areas, further described in this report, were identified for advancing integration of biopharmaceutics and support a more fundamentally based, integrated approach to setting product dissolution/release acceptance criteria. Collaboration among a broad range of disciplines and fostering a knowledge sharing environment that places the patient''s needs as the focus of drug development, consistent with science- and risk-based spirit of QbD, were identified as key components of the path forward.

Electronic supplementary material

The online version of this article (doi:10.1208/s12248-010-9206-0) contains supplementary material, which is available to authorized users.KEY WORDS: biopharmaceutics, dissolution, product performance, quality by design, quality target product profile