Literature DB >> 22451016

A physiologically based pharmacokinetic model of mitoxantrone in mice and scale-up to humans: a semi-mechanistic model incorporating DNA and protein binding.

Guohua An1, Marilyn E Morris.   

Abstract

We conducted a pharmacokinetic (PK) study of mitoxantrone (Novantrone®), a clinically well-established anticancer agent, in mice and developed a mechanism-based PBPK (physiologically based pharmacokinetic) model to describe its disposition. Mitoxantrone concentrations in plasma and six organs (lung, heart, liver, kidney, spleen, and brain) were determined after a 5 mg/kg i.v. dose. We evaluated three different PBPK models in order to characterize our experimental data: model 1 containing Kp values, model 2 incorporating a deep binding compartment, and model 3 incorporating binding of mitoxantrone to DNA and protein. Among the three models, only model 3 with DNA and protein binding captured all the experimental data well. The estimated binding affinity for DNA (K (DNA)) and protein (K (macro)) were 0.0013 and 1.44 μM, respectively. Predicted plasma and tissue AUC values differed from observed values by <19 %, except for heart (60 %). Model 3 was further used to simulate plasma mitoxantrone concentrations in humans for a 12-mg/m(2) dose, using human physiological parameters. The simulated results generally agreed with the observed time course of mitoxantrone plasma concentrations in patients after a standard dose of 12 mg/m(2). In summary, we reported for the first time a mechanism-based PBPK model of mitoxantrone incorporating macromolecule binding which may have clinical applicability in optimizing clinical therapy. Since mitoxantrone is a substrate of the efflux transporters ABCG2 and ABCB1, the incorporation of efflux transporters may also be necessary to characterize the data obtained in low-dose studies.

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Year:  2012        PMID: 22451016      PMCID: PMC3326165          DOI: 10.1208/s12248-012-9344-7

Source DB:  PubMed          Journal:  AAPS J        ISSN: 1550-7416            Impact factor:   4.009


  40 in total

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2.  Methotrexate tissue distribution: prediction by a mathematical model.

Authors:  D S Zaharko; R L Dedrick; K B Bischoff; J A Longstreth; V T Oliverio
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Journal:  Biochim Biophys Acta       Date:  1967-02-14

Review 5.  Mitoxantrone: a review of its use in multiple sclerosis.

Authors:  Lesley J Scott; David P Figgitt
Journal:  CNS Drugs       Date:  2004       Impact factor: 5.749

6.  Flavonoids are inhibitors of breast cancer resistance protein (ABCG2)-mediated transport.

Authors:  Shuzhong Zhang; Xinning Yang; Marilyn E Morris
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7.  Evidence of a specific complex between adriamycin and negatively-charged phospholipids.

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8.  Flow cytometric analysis of breast cancer resistance protein expression and function.

Authors:  Hans Minderman; Attaya Suvannasankha; Kieran L O'Loughlin; George L Scheffer; Rik J Scheper; Robert W Robey; Maria R Baer
Journal:  Cytometry       Date:  2002-06-01

9.  Doxorubicin pharmacokinetics: Macromolecule binding, metabolism, and excretion in the context of a physiologic model.

Authors:  Daniel L Gustafson; Jeffrey C Rastatter; Tina Colombo; Michael E Long
Journal:  J Pharm Sci       Date:  2002-06       Impact factor: 3.534

10.  DNA-binding specificity and RNA polymerase inhibitory activity of bis(aminoalkyl)anthraquinones and bis(methylthio)vinylquinolinium iodides.

Authors:  W O Foye; O Vajragupta; S K Sengupta
Journal:  J Pharm Sci       Date:  1982-02       Impact factor: 3.534

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Review 2.  Dose selection based on physiologically based pharmacokinetic (PBPK) approaches.

Authors:  Hannah M Jones; Kapil Mayawala; Patrick Poulin
Journal:  AAPS J       Date:  2012-12-27       Impact factor: 4.009

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4.  Characterization and Interspecies Scaling of rhTNF-α Pharmacokinetics with Minimal Physiologically Based Pharmacokinetic Models.

Authors:  Xi Chen; Debra C DuBois; Richard R Almon; William J Jusko
Journal:  Drug Metab Dispos       Date:  2017-04-14       Impact factor: 3.922

5.  Inherited variation in OATP1B1 is associated with treatment outcome in acute myeloid leukemia.

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Journal:  Clin Pharmacol Ther       Date:  2016-02-20       Impact factor: 6.875

6.  A Whole-Body Physiologically Based Pharmacokinetic Model of Gefitinib in Mice and Scale-Up to Humans.

Authors:  Youwei Bi; Jiexin Deng; Daryl J Murry; Guohua An
Journal:  AAPS J       Date:  2015-11-11       Impact factor: 4.009

7.  Dose-Independent ADME Properties and Tentative Identification of Metabolites of α-Mangostin from Garcinia mangostana in Mice by Automated Microsampling and UPLC-MS/MS Methods.

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Journal:  PLoS One       Date:  2015-07-15       Impact factor: 3.240

8.  Dynamical Boolean Modeling of Immunogenic Cell Death.

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  8 in total

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