Quality by Design for Biotechnology Products—Part 1 - A PhRMA Working Group's advice on applying QbD to biotech. - BioPharm International


Quality by Design for Biotechnology Products—Part 1

Developing the Design Space

Bioprocess manufacturing can be conceptualized as a series of contiguous unit operations such that meeting the drug substance or drug product quality targets is an end result of a single or a combination of multiple unit operations. With such linkages between process steps and unit operations, it is possible to establish the design space for each unit operation. Per ICH Q8(R2), the design space is

the multidimensional combination and interaction of input variables (e.g., material attributes) and process parameters that have been demonstrated to provide assurance of quality. 1

Thus, the design space for a unit operation or process step encompasses the acceptable ranges for the critical process parameters of this step that will deliver product of the desired quality.

Figure 4. Derivative/one branch Ishikawa diagram to identify process parameters in the bioreactor expansion unit operation that may potentially affect the quality attributes. (Figure courtesy of S. Rose, Eli Lilly and Company; unpublished).
A thorough understanding of the factors that could affect the process is required. A risk assessment should be performed to identify the process parameters that should be characterized using small-scale models and tools such as design of experiments (DoE). One approach commonly used to facilitate a cause-and-effect analysis is the "fishbone" or derivative/one branch Ishikawa diagram (Figure 4). Such a diagram provides a graphical representation of the relationship between process operating parameters and unit operation outcomes. For the reactor expansion unit operation, for example, the cell growth, viable cell density, culture viability, and glucose concentration may be affected by the inoculum, medium, bioreactor operation, and harvest. Scientific understanding and prior knowledge can be used together with quality risk management to prioritize which process parameters to study. One tool that is useful for documenting factor risks is failure mode effects analysis (FMEA), which uses the severity, probability, and detectability of each factor to rank risks within a process step, and thereby select factors for subsequent study.2 The accumulated information from similar molecules or experiences with similar technologies may be used to identify variables and define an initial design space for the process step of a new molecular entity.

Whereas operating ranges of a process in early development are primarily based on experience with equipment and platform technologies, design space limits will become available during late development and finally established during process characterization using small-scale models and tools like multivariable DOE. (For a description of process characterization, see PDA Technical Report No. 42). The refinement of the design space is based on the QTPP and the knowledge gained throughout development. As knowledge increases, some of the potentially critical and key process parameters will be identified as noncritical or non-key so that the number of critical and key process parameters may be reduced during late development.

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