Concept of Design Space In Quality By Design (QbD)

Concept of Design Space In Quality By Design (QbD): Quality by design (QbD) is a concept first outlined by quality expert Joseph M. Juran, the concept was also mentioned in the ICH Q8 guideline, which states that “quality cannot be tested into products, i.e., quality should be built in by design”. According to ICH Q8 QbD is defined as a systematic approach to development that begins with predefined objectives and emphasizes product and process understanding and process control, based on sound science and quality risk management.

Concept of Design Space In Quality By Design (QbD)

Design space is a multidimensional combination of the raw material properties and process parameters that assures the final product quality. It may be based on the mechanistic, empirical, or hybrid models; and presented as ranges of material inputs and process parameters, graphical representations of mathematical equations. Furthermore, it can be derived from retrospective evaluation of the production data, usually using selected multivariate models.

Design space is an optional feature of the QbD approach, but its unquestionable usefulness makes it almost a default feature of any QbD-based submission. A specific issue related to design space definition is the scale and equipment-dependency of studied factors, which can also be resolved through simulations and mathematical analysis.

Manufacturing of a pharmaceutical product is usually based on several unit operations, which may be executed via batch or continuous mode. The combination of starting materials, processing parameters, and the intermediates of the production process concurrently influence the final product quality.

It would, therefore, be of great importance to appoint an integrated design space spanning multiple-unit operations. If mathematical models are used to simultaneously optimize all CQAs of the product, multiple-unit design space may be appointed as a valuable element of the control strategy. If separate design space models are defined for different CQAs the acceptable parameters and/or ranges could differ and the overlapping range could be rather narrow.

Development of the multiple-unit design space was based on the concept that models derived from the multivariate characterization studies, performed independently on each critical process step, were used to define a set of interconnected acceptable operating ranges for the entire manufacturing process. The idea is that the output quality of one step becomes an input variable for the following step.

Starting from the quality targets of the final product, the design space of the last critical process step can be defined. For each step, the overlap of all CQA models constrained by the quality target for the most restrictive CQAs represents the individual-step design space.

The combination of the individual design spaces of all critical process steps is called the multiple-unit design space. In most cases, the design space boundary definition is restricted by only one or two CQAs. Product CQAs are often dependent on several material attributes and/or process parameters, and, more importantly, on their mutual interactions and combined effects.

MacGregor and Bruwer proposed that the design space of the properties of the raw materials is defined by projecting the possibly highly-dimensional space of raw material property measurements (various physical and chemical properties) down to a low-dimensional subspace of principal components. Garcia-Munoz elaborated upon the idea of the creation of a multivariate specification for an excipient. Multivariate latent variable methods were coupled with optimization techniques to understand the influence of the raw materials, process parameters, control strategy, and scale effects on the quality of the final product.

Some authors introduced the concept of adaptive design space whereby adaptation of critical process parameters is proposed to facilitate the creation of tablets meeting specifications despite variations in raw materials properties. For example, when the drug particle size was modified, only the use of higher compression force (outside of the original design space) at low compression speed generated appropriate tablets. In other words, design space is adapted to compensate for variations in raw materials properties.

An example of the dynamic design space establishment was recently proposed for primary drying during the freeze-drying process. During the freeze-drying process, two process parameters need to be set; the shelf temperature and the chamber pressure, namely; but preferably in a dynamic way. By applying mechanistic modeling of the primary drying step, optimal dynamic values for both parameters were obtained have compared different model-based control techniques for the development and scale-up of the freeze-drying process.

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