Abstract
Defining a quantitative and reliable relationship between in vitro drug release and in vivo absorption is highly desired for rational development, optimization, and evaluation of controlled-release dosage forms and manufacturing process. During the development of once daily extended-release (ER) tablet of glipizide, a predictive in vitro drug release method was designed and statistically evaluated using three formulations with varying release rates. In order to establish internally and externally validated level A in vitro-in vivo correlation (IVIVC), a total of three different ER formulations of glipizide were used to evaluate a linear IVIVC model based on the in vitro test method. For internal validation, a single-dose four-way cross over study (n=6) was performed using fast-, moderate-, and slow-releasing ER formulations and an immediate-release (IR) of glipizide as reference. In vitro release rate data were obtained for each formulation using the United States Pharmacopeia (USP) apparatus II, paddle stirrer at 50 and 100 rev. min(-1) in 0.1 M hydrochloric acid (HCl) and pH 6.8 phosphate buffer. The f(2) metric (similarity factor) was used to analyze the dissolution data. The formulations were compared using area under the plasma concentration-time curve, AUC(0-infinity), time to reach peak plasma concentration, T(max), and peak plasma concentration, C(max), while correlation was determined between in vitro release and in vivo absorption. A linear correlation model was developed using percent absorbed data versus percent dissolved from the three formulations. Predicted glipizide concentrations were obtained by convolution of the in vivo absorption rates. Prediction errors were estimated for C(max) and AUC(0-infinity) to determine the validity of the correlation. Apparatus II, pH 6.8 at 100 rev. min(-1) was found to be the most discriminating dissolution method. Linear regression analysis of the mean percentage of dose absorbed versus the mean percentage of in vitro release resulted in a significant correlation (r(2)>or=0.9) for the three formulations.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.