Pooria Taghavi Moghaddam1, Mohammad Reza Pipelzadeh2, Sholeh Nesioonpour2, Nader Saki3, Saeed Rezaee4. 1. Department of Pharmaceutics, School of Pharmacy, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran. 2. Anesthesia Department, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran. 3. Department of Otolaryngology, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran. 4. Department of Pharmaceutics, School of Pharmacy, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran. ; Nanotechnology Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran. ; Department of Pharmaceutics, School of Pharmacy, Zanjan University of Medical Sciences, Zanjan, Iran. (Current affiliation).
Abstract
PURPOSE: The aim of this study was to select the best calibration model for determination of propofol plasma concentration by high-performance liquid chromatography method. METHODS: Determination of propofol in plasma after deproteinization with acetonitrile containing thymol (as internal standard) was carried out on a C18 column with a mixture of acetonitrile and trifluoroacetic acid 0.1% (60:40) as mobile phase which delivered at the flow rate of 1.2 mL/minute . Fluorescence detection was done at the excitation and emission wavelengths of 276 and 310 nm, respectively. After fitting different equations to the calibration data using weighted regression, the adequacy of models were assessed by lack-of-fit test, significance of all model parameters, adjusted coefficient of determination (R(2) adjusted) and by measuring the predictive performance with median relative prediction error and median absolute relative prediction error of the validation data set. RESULTS: The best model was a linear equation without intercept with median relative prediction error and median absolute relative prediction error of 4.0 and 9.4%, respectively in the range of 10-5000 ng/mL. The method showed good accuracy and precision. CONCLUSION: The presented statistical framework could be used to choose the best model for heteroscedastic calibration data for analytes like propofol with wide range of expected concentration.
PURPOSE: The aim of this study was to select the best calibration model for determination of propofol plasma concentration by high-performance liquid chromatography method. METHODS: Determination of propofol in plasma after deproteinization with acetonitrile containing thymol (as internal standard) was carried out on a C18 column with a mixture of acetonitrile and trifluoroacetic acid 0.1% (60:40) as mobile phase which delivered at the flow rate of 1.2 mL/minute . Fluorescence detection was done at the excitation and emission wavelengths of 276 and 310 nm, respectively. After fitting different equations to the calibration data using weighted regression, the adequacy of models were assessed by lack-of-fit test, significance of all model parameters, adjusted coefficient of determination (R(2) adjusted) and by measuring the predictive performance with median relative prediction error and median absolute relative prediction error of the validation data set. RESULTS: The best model was a linear equation without intercept with median relative prediction error and median absolute relative prediction error of 4.0 and 9.4%, respectively in the range of 10-5000 ng/mL. The method showed good accuracy and precision. CONCLUSION: The presented statistical framework could be used to choose the best model for heteroscedastic calibration data for analytes like propofol with wide range of expected concentration.
Authors: Irena Loryan; Marja Lindqvist; Inger Johansson; Masahiro Hiratsuka; Ilse van der Heiden; Ron H N van Schaik; Jan Jakobsson; Magnus Ingelman-Sundberg Journal: Eur J Clin Pharmacol Date: 2011-10-18 Impact factor: 2.953
Authors: Catherijne A J Knibbe; Gitte Melenhorst-de Jong; Maaike Mestrom; Carin M A Rademaker; Allart F A Reijnvaan; Klaas P Zuideveld; Paul F M Kuks; Hans van Vught; Meindert Danhof Journal: Br J Clin Pharmacol Date: 2002-10 Impact factor: 4.335
Authors: Dimitrije Pavlovic; Ivana Budic; Tatjana Jevtovic Stoimenov; Dragana Stokanovic; Vesna Marjanovic; Marija Stevic; Milan Slavkovic; Dusica Simic Journal: Pharmgenomics Pers Med Date: 2020-01-17