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Case studies on the manufacture of a bluk powder and the development of a tablet show the application of QbD principles.
The changing development paradigm resulting from FDA’s quality-by-design (QbD) initiative and International Conference on Harmonization (ICH) guidelines requires increased process understanding of the drug substance and drug product throughout development and manufacturing. A lack of information can result in delays in regulatory approval and higher costs. Applying QbD principles leads to greater process understanding, facilitates regulatory approval, and streamlines postapproval changes. Case studies on the manufacture of a bulk powder and the development of a tablet show the application of QbD principles, including defining critical quality attributes, implementing risk assessment, optimizing process development, developing a design space, and performing a criticality analysis.
Quality by design (QbD) is often misquoted, misused, and misunderstood. Pharmaceutical QbD is a systematic scientific risk-based approach to pharmaceutical development that begins with predefined objectives that address product and process understanding and process control (1). Many articles focus on what is required with respect to product quality, safety, and efficacy but successful approaches are not commonly shared. Successful product development relies on consistent application of a proven methodology. The key steps are the same, irrespective of the product or formulation being developed. A proven methodology is described in this article, with the framework shown in Figure 1. These main steps are further described as outlined below.
Main steps of a QbD processCritical quality attributes (CQAs). CQAs are defined based on the target drug profile. These are quality characteristics of the drug that must be kept within appropriate limits to ensure the desired product quality (e.g., purity, crystalline form, and particle size).
Risk assessment during the development phase. For each CQA, an analysis of the potential critical process parameters (pCPPs) and potential critical material attributes (pCMAs) is conducted. The aim is to evaluate in each process step, operating parameters or raw materials that have the potential to affect a CQA within the known ranges, and therefore, should be monitored or controlled to ensure the desired quality. Because the number of parameters is usually high, a risk assessment based on prior knowledge of the product or process is used to rank the parameters in terms of perceived criticality. The ultimate goal is to keep the development process as lean as possible by focusing the studies on those parameters with a higher likelihood of having a critical impact.
Process development. The output of the risk assessment is a qualitative match between CQAs and pCPPs/pCMAs. To confirm the dependences and quantify the effects, a process-development stage is conducted. Usually a statistical approach is followed, through a sequence of design of experiments with different objectives--screening, optimization, and robustness studies. This development stage constitutes the core of the QbD methodology since most of the process knowledge is generated during this stage. Although not mandatory, a model, either statistical and/or mechanistic, is a usual outcome of this stage. Process analytical tools can also be considered at this stage based on the need to improve the CQA monitoring as the process is scaled up.
Design space and normal operating ranges (NOR). Once the impacts of the pCPPs/pCMAs are quantified on the CQAs, a feasible operating space can be defined. This space, known as the design space, will consider all the interactions between operating parameters and material attributes and will often be multidimensional. The NOR is established within the design space, and can be thought of as the ranges where the process typically operates.
Risk assessment during manufacturing. After defining the design space and NOR, an exhaustive analysis of the process is conducted at the manufacturing scale. In this study, a failure mode effect analysis (FMEA) of all manufacturing aspects are reviewed, challenging the equipment operating ranges and procedures against the process knowledge gathered in the previous steps. The purpose of this study is to understand and quantify the risk of batch or process failure and to define actions to minimize failures.
Criticality analysis. By knowing the feasible operating regions and after evaluating the equipment/procedures at the manufacturing scale and the practical NOR, a final criticality analysis will take place to identify parameters and/or material attributes that will require tight monitoring or control. For example, all parameters for which the corresponding NORs are close to the boundaries of the design space.
Process-control strategy. Once the criticality around a process parameter and/or raw material attribute is confirmed, adequate control strategies will be set in place. The ultimate goal is to assure that the operation is always taking place within the design space, therefore, assuring the quality of the final product. For this purpose, and considering the dependence of a control strategy on a given monitoring capability, the final implementation of process analytical technology tools is carried out at this stage. The subsequent steps are mainly focused on the documentation aspects associated with the filing process and will not be addressed in this article.
Bulk powder development case studyCQA definition. This case study examines the preparation of bulk powder that is subsequently formulated as a tablet. The preparation of the powder was broken down into three stages: synthesis, excipient addition, and spray drying. The spray-drying stage was identified as being potentially crucial for all CQAs, and will be examined in more detail (see Figure 2). CQAs for the bulk powder were determined to be purity, residual solvent level, particle size distribution, and bulk density among others, but will not be addressed in this article.
Risk assessment. A risk assessment was completed to prioritize and reduce the number of parameters to be investigated in the study. This process is subjective and relies on the experience of the team members involved in the assessment. Having four or more inputs will help reduce bias and enable the top pCPPs to become evident in general (see Figure 3). It is important to recognize that at this point, all process parameters are only potentially critical; confirmation of criticality is only conducted later in the methodology.
Although identified as being a pCPP, certain parameters may need to be fixed because they impact other aspects of the process such as yield and throughput. In this study, the concentration of the feed solution was fixed and the outlet temperature (T_out), the feed pressure (P_feed), and the spraying nozzle diameter (D_noz) were varied.
A series of experiments were run as a screening study. Using a statistically valid design of experiments (DOE), eleven runs were made. These trials considered a 24-1 half-factorial design with the centre point run in triplicates (see Figure 4). Once complete, the ranges of a DOE become the knowledge space for your product. Subsequent studies enlarge the knowledge space.