Looking for a hyper polyhedron within the multidimensional space of Design Space from the results of Designs of Experiments

Diane Manzon, Badih Ghattas, Magalie Claeys-Bruno (), Sophie Declomesnil, Christophe Carité and Michelle Sergent ()
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Diane Manzon: IMBE - Institut méditerranéen de biodiversité et d'écologie marine et continentale - AU - Avignon Université - AMU - Aix Marseille Université - Institut de recherche pour le développement [IRD] : UMR237 - CNRS - Centre National de la Recherche Scientifique, 4D pharma plc
Magalie Claeys-Bruno: IMBE - Institut méditerranéen de biodiversité et d'écologie marine et continentale - AU - Avignon Université - AMU - Aix Marseille Université - Institut de recherche pour le développement [IRD] : UMR237 - CNRS - Centre National de la Recherche Scientifique
Sophie Declomesnil: 4D pharma plc
Christophe Carité: 4D pharma plc
Michelle Sergent: IMBE - Institut méditerranéen de biodiversité et d'écologie marine et continentale - AU - Avignon Université - AMU - Aix Marseille Université - Institut de recherche pour le développement [IRD] : UMR237 - CNRS - Centre National de la Recherche Scientifique

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Abstract: In pharmaceutical studies, the Quality by Design (QbD) approach is increasingly being implemented to improve product development. Product quality is tested at each step of the manufacturing process, allowing a better process understanding and a better risk management, thus avoiding manufacturing defects. A key element of QbD is the construction of a Design Space (DS), i.e., a region in which the specifications on the output parameters should be met. Among the various possible construction methods, Designs of Experiments (DoE), and more precisely Response Surface Methodology, represent a perfectly adapted tool. The DS obtained may have any geometrical shape; consequently, the acceptable variation range of an input may depend on the value of other inputs. However, the experimenters would like to directly know the variation range of each input so that their variation domains are independent. In this context, we developed a method to determine the "Proven Acceptable Independent Range" (PAIR). It consists of looking for all the hyper polyhedra included in the multidimensional DS and selecting a hyper polyhedron according to various strategies. We will illustrate the performance of our method on different DoE cases.

Keywords: Quality by Design (QbD); Design of Experiments (DoE); Response Surface Methodology (RSM); Design Space (DS); Proven Acceptable Independent Range (PAIR) (search for similar items in EconPapers)
Date: 2023-01
New Economics Papers: this item is included in nep-des
Note: View the original document on HAL open archive server: https://amu.hal.science/hal-04021786v1
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Published in Chemometrics and Intelligent Laboratory Systems, 2023, 232, pp.104712. ⟨10.1016/j.chemolab.2022.104712⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04021786

DOI: 10.1016/j.chemolab.2022.104712

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