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The application of computer simulation to investigate drug absorption and bioavailability in disease states Open Access


Other title
MATE, OCT transporter
Top down approche ,bottom up approache
Meloxicam, Ibuprofen
Gastroplus, Drug modelling,computer simulation, Drug bioavailability, Disease
Type of item
Degree grantor
University of Alberta
Author or creator
Almukainzi, May Khalifah
Supervisor and department
Raimar Löbenberg
Examining committee member and department
Carlos Velazquez (Pharmacy)
Sharon Marsh (Pharmacy)
Fakhreddin Jamali (Pharmacy)
Hadi Valizadeh (Pharmacy)
Jack Tuszynski (Physics/ Oncology)
Faculty of Pharmacy and Pharmaceutical Sciences
Pharmaceutical Sciences
Date accepted
Graduation date
Doctor of Philosophy
Degree level
Oral drug absorption relies mainly on the physicochemical drug properties and the interaction with the physiological environment of the body. These factors could be altered significantly under abnormal conditions and disease states. Identifying these changes can optimize drug therapy under these conditions. Pain, obesity surgery and kidney failure are examples that can influence drug absorption through various mechanisms. Mechanistic tools can assist researchers to gain a better understanding of such effects. Computer simulations have promising applications in the recognition of alterations in drug absorption under disease conditions. The objectives of this thesis were to evaluate the utility of computer simulations to improve the understanding of such effects. This was done by investigating drug absorption and bioavailability in pain, gastric bypass surgery and renal impairments. The drug absorption of meloxicam, ibuprofen, and metformin were used as model drugs using advanced compartmental absorption and transit (ACAT) and physiologically based pharmacokinetics (PBPK) models in GastroplusTM (Simulations Plus, Inc.). In the pain model, published in vivo data of meloxicam and ibuprofen were used for the simulations using two formulations: a fast dissolving (FD) and regular release (RR). The oral bioavailability was compared between these formulations in vagally suppressed rats (gastric dysfunction) and a control group. Additionally, human data under pain induced by dental surgery was used. The in vivo drug release of all formulations was estimated for both drugs using the software’s immediate or gastric release models. In gastric bypass surgery and renal failure models, we investigated the mechanistic background of the absorption of metformin using patient data with post gastric bypass surgery and moderate chronic renal failure. Assumptions to explain the causes in the changes in drug absorption in these patients from their observed data were tested using the software. Using these models, I was able to explain the observed alteration in the drugs absorption that was induced by physiological changes in pain, gastric bypass, and renal failure. For meloxicam and ibuprofen, the software’s built in immediate release (IR) model predicted the in vivo absorption in the control groups administered FD and IR. When gastric dysfunction was induced, the model did not predict absorption, while the gastric release model did so for both FD and IR formulations. Simulation of gastric bypass surgery on the absorption of metformin showed that the increase in the pore size and porosity of the last part of the small intestine successfully predicted the observed PK parameters. This indicates that the gut must have undergone an adaption process to compensate for the loss of parts of the small intestine. The renal model showed that the down regulations of the kidney and liver transporters, particularly, the multidrug and toxin extrusion (MATE1), can explain the observed data. This down regulation might be induced by the increased in uremic toxins. Creatinin, is one of the uremic toxins that are highly increased in renal dysfunction, our anticipation that creatinin, which is a substrate for the same transporters, can compete with metformin and inhibit the drug elimination. However, using in vitro cell line derived from human embryonic kidney (HEK293) showed that the presence of a high concentration of creatinine level has no effect on metformin elimination. The insights gained by these studies can be applied to other drugs that have similar physiochemical properties. In silico methods can be a potential tool to predict the influence of physiological changes induced by disease conditions. Using such software in disease conditions can help to understand the mechanism of drug absorption, predicting the pharmacokinetics (PK) of administered drugs. This tool can be used in precision medicine in order to individualize patients’ dose or treatment regimen and optimize dosage forms. This is a very important practice to maximize drug benefits and reduce possible side effects for these patents. This also can help the pharmaceutical industry in speeding up drug development cycles, reducing clinical testing, and reducing cost.
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
Citation for previous publication
Almukainzi M, L. V., Löbenberg R (2014). "Modelling the Absorption of Metformin with Patients Post Gastric Bypass Surgery." Diabetes Metab 5: 353.

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