Pharmacokinetic modelling of microencapsulated metronidazole.
- Author:
Mahmood AHMAD
1
;
Khalid PERVAIZ
;
Ghulam MURTAZA
;
Munaza RAMZAN
Author Information
1. Department of Pharmacy, Faculty of Pharmacy and Alternative Medicines, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan. ma786_786@yahoo.com
- Publication Type:Journal Article
- MeSH:
Chemistry, Pharmaceutical;
Drug Compounding;
Drug Design;
Humans;
Male;
Metronidazole;
administration & dosage;
pharmacokinetics;
Young Adult
- From:
Acta Pharmaceutica Sinica
2009;44(6):674-679
- CountryChina
- Language:English
-
Abstract:
The aim of present study is to develop a pharmacokinetic model for microencapsulated metronidazole to predict drug absorption pattern in healthy human and validate this model internally. Metronidazole was microencapsulated into ethylcellulose shells followed by the conversion of these microcapsules into tablets. Dissolution study of tablets was conducted in 450 mL double distilled water, 0.1 mol L(-1) HCl and phosphate buffer (pH 6.8) maintained at (37+/-0.5) degrees C using USP apparatus II at 50, 100 and 150 r min(-1). Three metronidazole tablets (T1: fast release, T2: moderate release, T3: slow release and reference) were administered to twenty four healthy human volunteers and serial blood samples were collected for 12 hours followed by their analysis using RP-HPLC. Drug release data were analyzed by various model dependent and independent approaches. Drug absorbed (%) was determined by Wagner-Nelson method from plasma concentration profile. Internal predictability was checked from Cmax and AUC. Optimum dissolution profile was observed in double distilled water and 50 r min(-1). A good level A correlation was observed between drug dissolution and absorption profiles (correlation coefficient, R2 = 0.9009, 0.9426, 0.9015 and 0.932 for T1, T2, T3 and reference, respectively). Internal predictability was found less than 10%. Good correlation coefficients and low prediction errors elaborate the validity of this mathematical in-vitro in-vivo correlation model as a predictive tool for the determination of pharmacokinetics from dissolution data.
