PreprintArticleVersion 1This version is not peer-reviewed
Important Aspects of the Design of Experiments and Data Treatment in the Analytical Quality by Design Framework Applied to the Development of Chromatographic Methods
Version 1
: Received: 6 November 2024 / Approved: 7 November 2024 / Online: 7 November 2024 (15:09:17 CET)
How to cite:
Passerine, B. F. G.; Breitkreitz, M. C. Important Aspects of the Design of Experiments and Data Treatment in the Analytical Quality by Design Framework Applied to the Development of Chromatographic Methods. Preprints2024, 2024110548. https://doi.org/10.20944/preprints202411.0548.v1
Passerine, B. F. G.; Breitkreitz, M. C. Important Aspects of the Design of Experiments and Data Treatment in the Analytical Quality by Design Framework Applied to the Development of Chromatographic Methods. Preprints 2024, 2024110548. https://doi.org/10.20944/preprints202411.0548.v1
Passerine, B. F. G.; Breitkreitz, M. C. Important Aspects of the Design of Experiments and Data Treatment in the Analytical Quality by Design Framework Applied to the Development of Chromatographic Methods. Preprints2024, 2024110548. https://doi.org/10.20944/preprints202411.0548.v1
APA Style
Passerine, B. F. G., & Breitkreitz, M. C. (2024). Important Aspects of the Design of Experiments and Data Treatment in the Analytical Quality by Design Framework Applied to the Development of Chromatographic Methods. Preprints. https://doi.org/10.20944/preprints202411.0548.v1
Chicago/Turabian Style
Passerine, B. F. G. and Márcia C. Breitkreitz. 2024 "Important Aspects of the Design of Experiments and Data Treatment in the Analytical Quality by Design Framework Applied to the Development of Chromatographic Methods" Preprints. https://doi.org/10.20944/preprints202411.0548.v1
Abstract
In the AQbD framework, DOE plays a very important role as it provides information about how experimental input variables influence the critical method attributes. Based on the information obtained from the DOE, mathematical models are generated and used to build the MODR a robust region of operability. Data treatment steps are usually carried out in software such as Fusion QbD, Minitab, StaEase 360, among others. Although there are many papers in the literature using DOE, none of them address important aspect of data treatment for optimization and MODR generation and compare different software calculations. The purpose of this study is to contribute to a better understanding of data treatment aspects that are frequently misread or not fully understood, such as model selection, ANOVA results and residual analysis. The discussion will be guided using the separation of curcuminoids by ultra-high performance liquid chromatography and eight quality attribute as responses. The results highlighted the importance of the correct selection and evaluation of the models due to their influence the generation of the MODR and emphasizes the insertion of the uncertainty in the contour plots to proper obtain the MODR regarding the definitions of the USP General Chapter <1220> and ICH Q14 guidelines.
Keywords
Liquid chromatography; Analytical Quality by Design; Experimental design; MODR
Subject
Chemistry and Materials Science, Analytical Chemistry
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
