The present communication describes a systematic methodology for the quantification of the Design Space characteristics of batch pharmaceutical process. The methodology is applicable to processes which are not known in great detail for a mathematical model to be available. The approach designs a set of experiments utilizing a newly developed methodology for the Design of Dynamic Experiments (DoDE) and the traditional response surface modeling methodology. The use of these input output-models enables the quantitative address the following issues related to the Quality by Design approach:
1) For processes in which no feedback control strategy is exercised:
1a. For a given variability in the raw materials and/or the processing conditions, what is the expected variability in the quality of the product produced?
1b. Given the maximal acceptable variability in the product and the current operating conditions, what is the maximum variability in the raw material that can be utilized without impacting the quality of the product?
2) For processes with a feedback control strategy on the expected product quality:
2a. What is the maximum variability in the raw materials or other uncontrolled disturbances which can be compensated by a given control strategy so the product quality is kept within acceptable limits?
2b. What is the impact of different fee-forward or/and feedback control strategies on question 2a?
Processes for which we have a model describing the cause and effect relationships among the pertinent variables can be also handled in a similar, if not easier, manner by substituting the design of dynamic experiments (DoDE) with an equivalent design of (selective) dynamic calculations (DoDC).&'
The Use of the Design of Dynamic Experiments Methodology to Quantify the Design Space in QbD Tasks
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