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Title: Improvement of a mixture experiment model relating the component proportions to the size of nanonized itraconazole particles in extemporary suspensions

A paper by Foglio Bonda et al. published previously in this journal (2016, Vol. 83, pp. 175–183) discussed the use of mixture experiment design and modeling methods to study how the proportions of three components in an extemporaneous oral suspension affected the mean diameter of drug particles (Z ave). The three components were itraconazole (ITZ), Tween 20 (TW20), and Methocel® E5 (E5). This commentary addresses some errors and other issues in the previous paper, and also discusses an improved model relating proportions of ITZ, TW20, and E5 to Z ave. The improved model contains six of the 10 terms in the full-cubic mixture model, which were selected using a different cross-validation procedure than used in the previous paper. In conclusion, compared to the four-term model presented in the previous paper, the improved model fit the data better, had excellent cross-validation performance, and the predicted Z ave of a validation point was within model uncertainty of the measured value.
Authors:
ORCiD logo [1] ;  [2] ;  [1]
  1. Univ. degli Studi del Piemonte Orientale "A. Avogadro," Novara (Italy). Dipartimento di Scienze del Farmaco
  2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Publication Date:
Report Number(s):
PNNL-SA-123916
Journal ID: ISSN 0928-0987; PII: S0928098718301209
Grant/Contract Number:
AC05-76RL01830
Type:
Accepted Manuscript
Journal Name:
European Journal of Pharmaceutical Sciences
Additional Journal Information:
Journal Volume: 117; Journal ID: ISSN 0928-0987
Publisher:
Elsevier
Research Org:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
77 NANOSCIENCE AND NANOTECHNOLOGY; Drug nanosuspension; Drug particle size; Mixture experiment design; Mixture experiment model; Cross-validated regression analysis
OSTI Identifier:
1425500

Pattarino, Franco, Piepel, Greg, and Rinaldi, Maurizio. Improvement of a mixture experiment model relating the component proportions to the size of nanonized itraconazole particles in extemporary suspensions. United States: N. p., Web. doi:10.1016/J.EJPS.2018.03.005.
Pattarino, Franco, Piepel, Greg, & Rinaldi, Maurizio. Improvement of a mixture experiment model relating the component proportions to the size of nanonized itraconazole particles in extemporary suspensions. United States. doi:10.1016/J.EJPS.2018.03.005.
Pattarino, Franco, Piepel, Greg, and Rinaldi, Maurizio. 2018. "Improvement of a mixture experiment model relating the component proportions to the size of nanonized itraconazole particles in extemporary suspensions". United States. doi:10.1016/J.EJPS.2018.03.005.
@article{osti_1425500,
title = {Improvement of a mixture experiment model relating the component proportions to the size of nanonized itraconazole particles in extemporary suspensions},
author = {Pattarino, Franco and Piepel, Greg and Rinaldi, Maurizio},
abstractNote = {A paper by Foglio Bonda et al. published previously in this journal (2016, Vol. 83, pp. 175–183) discussed the use of mixture experiment design and modeling methods to study how the proportions of three components in an extemporaneous oral suspension affected the mean diameter of drug particles (Zave). The three components were itraconazole (ITZ), Tween 20 (TW20), and Methocel® E5 (E5). This commentary addresses some errors and other issues in the previous paper, and also discusses an improved model relating proportions of ITZ, TW20, and E5 to Zave. The improved model contains six of the 10 terms in the full-cubic mixture model, which were selected using a different cross-validation procedure than used in the previous paper. In conclusion, compared to the four-term model presented in the previous paper, the improved model fit the data better, had excellent cross-validation performance, and the predicted Zave of a validation point was within model uncertainty of the measured value.},
doi = {10.1016/J.EJPS.2018.03.005},
journal = {European Journal of Pharmaceutical Sciences},
number = ,
volume = 117,
place = {United States},
year = {2018},
month = {3}
}