Design of experiments (DoE) is a systematic approach aiming to maximize information content from an experimental study, while keeping the number of experiments low. During formulation development, DoE is used to develop an experimental matrix that probes a limited number of input factor combinations simultaneously and then uses statistical analysis to allow scientists to choose the optimal formulation conditions.
Design of experiments (DoE) aims to maximize information content from an experimental study, while keeping the number of experiments low.
Although DoE does not replace scientific know-how and experience, the careful use of DoE allows large parameter spaces to be explored in a highly efficient way.
DoE can also be a vital part of a Quality by Design (QbD) concept.
The steps of DoE during formulation development often follow a general pattern.
First, influencing variables (input factors) must be defined and the related responses (product or process results) need to be identified.
Second, the number of experimental settings must be selected, and the experimental design needs to be generated using software algorithms.
Third, an experimental work plan is drafted and reviewed. DoE is supported by dedicated software solutions, such as Design-Expert or MODDE, especially when it comes to the statistical analysis of the experimental results.