Roberta Bartolucci, Nicola Melillo, Paolo Magni
Laboratory of Bioinformatics, Mathematical Modelling and Synthetic Biology, Department of Electrical, Computer and Biomedical Engineering, University of Pavia, via Ferrata 5, Pavia, I-27100, Italy
Objectives: The aim of this work was to develop a mechanistic model for the description of the pharmacokinetics of the drug Azathioprine in rats, in order to predict the plasma concentration-time curve in humans. Azathioprine (AZA) is an immunosuppressive, antimetabolite prodrug used for the treatment of Acute Lymphoblastic Leukaemia in childhood and autoimmune disorders [1]. After absorption, it is rapidly converted into 6-mercaptopurine (6MP) which in turn is subject to a fast and extensive metabolism, distributed in several different tissues [1]. Despite AZA is a drug already on the market, it is still very studied for the Drug-Drug Interaction (DDI), as many drugs act on the same enzymes involved in its metabolism. A good description of AZA pharmacokinetics is therefore essential to better understand the DDI mechanism and to avoid toxic effects.
Methods: Physiologically-based pharmacokinetic (PBPK) models were chosen to describe the plasma concentration vs time profiles of AZA and 6MP in rats and humans, as they allow to consider inter-species differences in terms of physiological and anatomical characteristics [2]. Two coupled PBPK models have been developed in MATLAB, each one describing the kinetics of one molecule within the whole organism. The model structure was divided into 17 homogeneous (well-stirred) compartments: Lungs, Heart, Brain, Adipose tissue, Muscles, Spleen, Liver, Stomach, Intestinal lumen, Enterocytes, Gut tissue, Kidneys, Arterial Plasma, Venous Plasma, Arterial Red Blood Cells (RBC), Venous RBC and Rest of Body (representing all tissues not directly modelled). An ACAT model of 8 compartments was then implemented to better describe the absorption and the metabolism in the intestinal mucosa. Partition coefficients of each compartment, except RBC’s, were estimated using Poulin-Thiel equations with a correction factor K that considers active transports. Drug exchange between plasma and RBC compartments has been modelled through the PSBC parameter, which takes into account the permeability and the membrane surface area. The conversion of AZA into 6MP was represented with a first order clearance in Liver and Enterocytes, whereas the metabolism of 6MP was described by Michaelis-Menten equations in Liver, Enterocytes, RBCs and Kidney.
Results: Three scenarios (Intravenous administration of 6MP, oral administration of 6MP and oral administration of AZA) were simulated in rats using pre-clinical experimental data [3]-[4], in order to estimate 7 PK parameters that have not been found in literature. After a proper parameter scaling between rat and human, the complete model thus obtained was used to simulate an oral administration of AZA in humans, and the predicted plasma concentration-time profile of 6MP was compared with literature data [5]. The estimated values of the unknown parameters allowed to obtain a simulated PK profile similar to the experimental data in rats and a good prediction in humans, with a plasma concentration curve of 6MP within the range of a standard deviation from the mean values. Cmax, Tmax and AUC were also comparable to literature values in every scenario.
Conclusions: The transition from the pre-clinical to the clinical phase, critical in drug development, it is generally addressed using empirical methods such as allometric scaling, which considers only the proportion with respect to the body weight [2]. In this work instead, a PBPK model was used to considers the anatomical and physiological differences between rats and humans. Furthermore, the mechanistic description of AZA and 6MP metabolism in rats allowed to obtain a good prediction of the plasma concentration in humans. For this reason, the model will could be useful for further DDI investigations.
References:
[1] L. Lennard, “The clinical pharmacology of 6-mercaptopurine”, European Journal of Clinical Pharmacology, vol. 43, pp. 329-339, 1992.
[2] P. Espié, D. Tytgat, M. Sargentini Maier, I. Poggesi and J. Watelet, “Physiologically based pharmacokinetics (PBPK)”, Drug Metabolism Reviews, vol. 41, no. 3, pp. 391-407, 2009. DOI:10.1080/10837450902891360.
[3] M. Umrethia, P.K. Ghosh, R. Majithya and R.S.R. Murthy, “6-Mercaptopurine (6-MP) Entrapped Stealth Liposomes for Improvement of Leukemic Treatment without Hepatotoxicity and Nephrotoxicity”, Cancer Investigation, vol. 25, pp. 117-123,2007. DOI: 10.1080/07357900701224862
[4] N.K. Burton and G.W. Aherne, “The effect of cotrimoxazole on the absorption of orally administered 6-mercaptopurine in the rat”, Cancer Chemotherapy and Pharmacology, vol. 16, pp. 83-84, 1986.
[5] B.J. Zins, W.J. Sandborn, J.A. McKinney, D.C. Mays, E.C. Van Os, W.J. Tremaine, D.W. Mahoney, A.R. Zinsmeister and J.J. Lipsky, “A Dose-Ranging Study of Azathioprine Pharmacokinetics After Single-Dose Administration of a Delayed-Release Oral Formulation”, Journal of Clinical Pharmacology, vol. 37, pp. 38-46, 1997.
Reference: PAGE 27 (2018) Abstr 8547 [www.page-meeting.org/?abstract=8547]
Poster: Drug/Disease Modelling - Absorption & PBPK