May Almukainzi1, Fakhreddin Jamali1, Ali Aghazadeh-Habashi1, Raimar Löbenberg2. 1. Faculty of Pharmacy & Pharmaceutical Science, University of Alberta, Edmonton, AB, Canada. 2. Faculty of Pharmacy & Pharmaceutical Science, University of Alberta, Edmonton, AB, Canada. Electronic address: raimar.loebenberg@ualberta.ca.
Abstract
PURPOSE: Studies have shown altered pharmacokinetic patterns (PK) in patient suffering from acute pain. Thus, we aimed to simulate pharmacokinetics of meloxicam and ibuprofen in pain and pain-free states using a physiological based software program to identify the underlining mechanistic changes for the observed differences. METHOD: Published in vivo data of meloxicam and ibuprofen were used for the simulations. Two drug formulations were studied: a fast dissolving (FD) and regular release (RR) tablet formulation. The oral bioavailability was compared between these formulations in vagally suppressed rats (gastric dysfunction) and a control group. For ibuprofen additional human data of a control and post dental surgery group were used. All simulations were performed using GastroPlus™. The in vivo drug release and PK of all formulations were estimated for both drugs using the software's immediate release (IR) or gastric release (GR) models. RESULT: For meloxicam, the IR model predicted the in vivo absorption in the control group after administration of the FD and RR formulations. When gastric dysfunction was induced, the IR model did not predict absorption while the GR model did for both formulations, FD and RR. For ibuprofen, the predictions were also very close for both formulations, using the IR model for the control group and the GR model for the vagally suppressed condition in rats and humans. CONCLUSIONS: Gastric control of the drug release in pain/disease state was identified as the major factor causing the observed differences in the pharmacokinetics. Computer simulations of disease states can be employed to optimize drug release from dosage forms to overcome the reported shortfalls in the drug absorption.
PURPOSE: Studies have shown altered pharmacokinetic patterns (PK) in patient suffering from acute pain. Thus, we aimed to simulate pharmacokinetics of meloxicam and ibuprofen in pain and pain-free states using a physiological based software program to identify the underlining mechanistic changes for the observed differences. METHOD: Published in vivo data of meloxicam and ibuprofen were used for the simulations. Two drug formulations were studied: a fast dissolving (FD) and regular release (RR) tablet formulation. The oral bioavailability was compared between these formulations in vagally suppressed rats (gastric dysfunction) and a control group. For ibuprofen additional human data of a control and post dental surgery group were used. All simulations were performed using GastroPlus™. The in vivo drug release and PK of all formulations were estimated for both drugs using the software's immediate release (IR) or gastric release (GR) models. RESULT: For meloxicam, the IR model predicted the in vivo absorption in the control group after administration of the FD and RR formulations. When gastric dysfunction was induced, the IR model did not predict absorption while the GR model did for both formulations, FD and RR. For ibuprofen, the predictions were also very close for both formulations, using the IR model for the control group and the GR model for the vagally suppressed condition in rats and humans. CONCLUSIONS: Gastric control of the drug release in pain/disease state was identified as the major factor causing the observed differences in the pharmacokinetics. Computer simulations of disease states can be employed to optimize drug release from dosage forms to overcome the reported shortfalls in the drug absorption.
Authors: Rohit T Rao; Megerle L Scherholz; Clara Hartmanshenn; Seul-A Bae; Ioannis P Androulakis Journal: Comput Chem Eng Date: 2017-06-03 Impact factor: 3.845
Authors: Marival Bermejo; Paulo Paixão; Bart Hens; Yasuhiro Tsume; Mark J Koenigsknecht; Jason R Baker; William L Hasler; Robert Lionberger; Jianghong Fan; Joseph Dickens; Kerby Shedden; Bo Wen; Jeffrey Wysocki; Raimar Löbenberg; Allen Lee; Ann Frances; Gregory E Amidon; Alex Yu; Niloufar Salehi; Arjang Talattof; Gail Benninghoff; Duxin Sun; Gislaine Kuminek; Katie L Cavanagh; Naír Rodríguez-Hornedo; Gordon L Amidon Journal: Mol Pharm Date: 2018-11-12 Impact factor: 4.939