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The data set contained 14 input variables (both formulation and process variables) and one output variable (pellet aspect ratio).
A predictive model to prepare stable solid spray dried amorphous ABT-102 nanoparticles, incorporating both formulation and process parameters, was successfully developed using multiple linear regression analysis.
In a quality by design paradigm, there is a need to establish both formulation and process design space, which can get expensive if such experiments are to be conducted at a large scale.
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These models have a sound mechanistic basis and can be used for both formulation design and process scaling.
It was concluded that an in-line tool such as Raman spectroscopy is a simple and sensitive technique able to assist in both formulation optimization and process development.
Conversely, emulsion stability resulted simultaneously from formulation and process factors.
Effect of formulation and process variants was assessed on uniformity and fineness of fibrous scaffolds.
The dissolution and assay were independent of formulation and process parameters studied.
The formulation and process, as input variables, were analyzed using a response surface methodology (RS M.
The formulation and process variables were optimized using a central-composite design.
CQAs provide the link between critical formulation and process parameters with clinical product performance.
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