Literature DB >> 10411581

Mechanism-based pharmacokinetic-pharmacodynamic modeling of antilipolytic effects of adenosine A(1) receptor agonists in rats: prediction of tissue-dependent efficacy in vivo.

P H Van der Graaf1, E A Van Schaick, S A Visser, H J De Greef, A P Ijzerman, M Danhof.   

Abstract

In this study, we analyzed the antilipolytic effects of six N(6)-cyclopentyladenosine analogs in rats and developed a mechanistic pharmacokinetic-pharmacodynamic model to quantify and predict the tissue-selective action of adenosine A(1) receptor agonists in vivo. Freely moving rats received an i.v. infusion of vehicle or compound over 15 min. Arterial blood samples were taken at regular time intervals for the determination of concentrations of drugs using HPLC analysis and of nonesterified fatty acids (NEFAs). All N(6)-cyclopentyladenosine analogs that were investigated produced a significant decrease in the NEFA plasma concentration after i.v. infusion. The pharmacokinetic behavior of each ligand was described by a standard two-compartment model. The pharmacokinetic parameter estimates then were used to simultaneously fit the individual (n = 6-8) time-NEFA concentration profiles for each agonist to a physiological indirect response model in combination with the Hill equation to obtain estimates of the NEFA elimination rate constant (k(e)) and upper asymptote (fractional inhibition), midpoint location, and midpoint slope parameter (alpha, pEC(50), and n(H), respectively) of the concentration-effect relationship. Subsequently, the data were analyzed with the operational model of agonism to obtain estimates of in vivo affinity and efficacy. It was estimated that the in vivo density and/or coupling of adenosine A(1) receptors mediating antilipolytic effects is approximately 38 times higher compared with the receptors mediating bradycardia. The model predicts that it is possible to design ligands that produce significant inhibition of lipolysis and are completely devoid of cardiovascular effects in vivo.

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Year:  1999        PMID: 10411581

Source DB:  PubMed          Journal:  J Pharmacol Exp Ther        ISSN: 0022-3565            Impact factor:   4.030


  21 in total

1.  Mechanism-based pharmacokinetic-pharmacodynamic modeling-a new classification of biomarkers.

Authors:  Meindert Danhof; Gunnar Alvan; Svein G Dahl; Jochen Kuhlmann; Gilles Paintaud
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2.  A receptor theory-based semimechanistic PD model for the CCR5 noncompetitive antagonist maraviroc.

Authors:  Philippe Jacqmin; Lynn McFadyen; Janet R Wade
Journal:  Br J Clin Pharmacol       Date:  2008-04       Impact factor: 4.335

3.  PKPD modelling of the interrelationship between mean arterial BP, cardiac output and total peripheral resistance in conscious rats.

Authors:  N Snelder; B A Ploeger; O Luttringer; D F Rigel; R L Webb; D Feldman; F Fu; M Beil; L Jin; D R Stanski; M Danhof
Journal:  Br J Pharmacol       Date:  2013-08       Impact factor: 8.739

4.  Pharmacokinetic-pharmacodynamic modelling of the analgesic effects of lumiracoxib, a selective inhibitor of cyclooxygenase-2, in rats.

Authors:  D A Vásquez-Bahena; U E Salazar-Morales; M I Ortiz; G Castañeda-Hernández; Iñaki F Trocóniz
Journal:  Br J Pharmacol       Date:  2009-12-02       Impact factor: 8.739

5.  Unexpected relationship between plasma protein binding and the pharmacodynamics of 2-NAP, a CCK1-receptor antagonist.

Authors:  V P Gerskowitch; J Hodge; R A D Hull; N P Shankley; S B Kalindjian; J McEwen; J W Black
Journal:  Br J Clin Pharmacol       Date:  2006-10-17       Impact factor: 4.335

6.  Target and Tissue Selectivity Prediction by Integrated Mechanistic Pharmacokinetic-Target Binding and Quantitative Structure Activity Modeling.

Authors:  Anna H C Vlot; Wilhelmus E A de Witte; Meindert Danhof; Piet H van der Graaf; Gerard J P van Westen; Elizabeth C M de Lange
Journal:  AAPS J       Date:  2017-12-04       Impact factor: 4.009

7.  Pharmacokinetic-pharmacodynamic analysis of the EEG effect of alfentanil in rats following beta-funaltrexamine-induced mu-opioid receptor "knockdown" in vivo.

Authors:  M Garrido; J Gubbens-Stibbe; E Tukker; E Cox; J von Frijtag; D Künzel; A IJzerman; M Danhof; P H van der Graaf
Journal:  Pharm Res       Date:  2000-06       Impact factor: 4.200

Review 8.  Toward the prediction of CNS drug-effect profiles in physiological and pathological conditions using microdialysis and mechanism-based pharmacokinetic-pharmacodynamic modeling.

Authors:  Elizabeth C M de Lange; Paulien G M Ravenstijn; Dorien Groenendaal; Tamara J van Steeg
Journal:  AAPS J       Date:  2005-10-07       Impact factor: 4.009

Review 9.  Pharmacokinetic/pharmacodynamic modelling in diabetes mellitus.

Authors:  Cornelia B Landersdorfer; William J Jusko
Journal:  Clin Pharmacokinet       Date:  2008       Impact factor: 6.447

10.  Pharmacokinetic-pharmacodynamic modeling of the effectiveness and safety of buprenorphine and fentanyl in rats.

Authors:  Ashraf Yassen; Erik Olofsen; Jingmin Kan; Albert Dahan; Meindert Danhof
Journal:  Pharm Res       Date:  2007-10-04       Impact factor: 4.200

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