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      Guiding dose adjustment of amlodipine after co-administration with ritonavir containing regimens using a physiologically-based pharmacokinetic/pharmacodynamic model

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          Abstract

          Amlodipine, a commonly prescribed anti-hypertensive drug, shows increased systemic exposure with cytochrome P450 (CYP) 3A inhibitors. Ritonavir (RTV) is a potent mechanism-based and reversible CYP3A inhibitor and moderate inducer that is used as a pharmacokinetic enhancer in several antiviral treatment regimens. Drug–drug interaction (DDI) between RTV and amlodipine is due to mixed inhibition and induction of CYP3A4, which is challenging to predict without a mechanistic model that accounts for the complexity of both mechanisms occurring simultaneously. A novel physiologically-based pharmacokinetic (PBPK) model was developed for amlodipine, and the model was verified using published clinical PK and DDI data. The verified amlodipine PBPK model was linked to a pharmacodynamics model that describes changes in systolic blood pressure (SBP) during and after co-administration with RTV. The magnitude and time course of RTV effects on amlodipine plasma exposures and SBP were evaluated, to provide guidance on dose adjustment of amlodipine during and after co-administration with RTV-containing regimens. Model simulations suggested that the increase in amlodipine’s plasma exposure by RTV diminishes by approximately 80% within 5 days after the last dose of RTV. PBPK simulations suggested that resuming a full dose of amlodipine [5 mg once daily (QD)] immediately after RTV’s last dose would decrease daily average SBP by a maximum of 3.3 mmHg, while continuing with the reduced dose (2.5 mg QD) for 5 days after the last dose of RTV would increase daily average SBP by a maximum of 5.8 mmHg. Based on these results, either approach of resuming amlodipine’s full dose could be appropriate when combined with appropriate clinical monitoring.

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          Simulation and prediction of in vivo drug metabolism in human populations from in vitro data.

          The perceived failure of new drug development has been blamed on deficiencies in in vivo studies of drug efficacy and safety. Prior simulation of the potential exposure of different individuals to a given dose might help to improve the design of such studies. This should also help researchers to focus on the characteristics of individuals who present with extreme reactions to therapy. An effort to build virtual populations using extensive demographic, physiological, genomic and in vitro biochemical data to simulate and predict drug disposition from routinely collected in vitro data is outlined.
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            Volume of distribution at steady state for a linear pharmacokinetic system with peripheral elimination.

            The problem of finding the steady-state volume of distribution V(ss) for a linear pharmacokinetic system with peripheral drug elimination is considered. A commonly used equation V(ss) = (D/AUC)*MRT is applicable only for the systems with central (plasma) drug elimination. The following equation, V(ss) = (D/AUC)*MRT(int), was obtained, where AUC is the commonly calculated area under the time curve of the total drug concentration in plasma after intravenous (iv) administration of bolus drug dose, D, and MRT(int) is the intrinsic mean residence time, which is the average time the drug spends in the body (system) after entering the systemic circulation (plasma). The value of MRT(int) cannot be found from a drug plasma concentration profile after an iv bolus drug input if a peripheral drug exit occurs. The obtained equation does not contain the assumption of an immediate equilibrium of protein and tissue binding in plasma and organs, and thus incorporates the rates of all possible reactions. If drug exits the system only through central compartment (plasma) and there is an instant equilibrium between bound and unbound drug fractions in plasma, then MRT(int) becomes equal to MRT = AUMC/AUC, which is calculated using the time course of the total drug concentration in plasma after an iv bolus injection. Thus, the obtained equation coincides with the traditional one, V(ss) = (D/AUC)*MRT, if the assumptions for validity of this equation are met. Experimental methods for determining the steady-state volume of distribution and MRT(int), as well as the problem of determining whether peripheral drug elimination occurs, are considered. The equation for calculation of the tissue-plasma partition coefficient with the account of peripheral elimination is obtained. The difference between traditionally calculated V(ss) = (D/AUC)*MRT and the true value given by (D/AUC)*MRT(int) is discussed. Copyright 2004 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 93:1628-1640, 2004
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              A framework for assessing inter-individual variability in pharmacokinetics using virtual human populations and integrating general knowledge of physical chemistry, biology, anatomy, physiology and genetics: A tale of 'bottom-up' vs 'top-down' recognition of covariates.

              An increasing number of failures in clinical stages of drug development have been related to the effects of candidate drugs in a sub-group of patients rather than the 'average' person. Expectation of extreme effects or lack of therapeutic effects in some subgroups following administration of similar doses requires a full understanding of the issue of variability and the importance of identifying covariates that determine the exposure to the drug candidates in each individual. In any drug development program the earlier these covariates are known the better. An important component of the drive to decrease this failure rate in drug development involves attempts to use physiologically-based pharmacokinetics 'bottom-up' modeling and simulation to optimize molecular features with respect to the absorption, distribution, metabolism and elimination (ADME) processes. The key element of this approach is the separation of information on the system (i.e. human body) from that of the drug (e.g. physicochemical characteristics determining permeability through membranes, partitioning to tissues, binding to plasma proteins or affinities toward certain enzymes and transporter proteins) and the study design (e.g. dose, route and frequency of administration, concomitant drugs and food). In this review, the classical 'top-down' approach in covariate recognition is compared with the 'bottom-up' paradigm. The determinants and sources of inter-individual variability in different stages of drug absorption, distribution, metabolism and excretion are discussed in detail. Further, the commonly known tools for simulating ADME properties are introduced.
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                Author and article information

                Contributors
                +1 (847) 938-3662 , Mohamad.shebley@abbvie.com
                Journal
                J Pharmacokinet Pharmacodyn
                J Pharmacokinet Pharmacodyn
                Journal of Pharmacokinetics and Pharmacodynamics
                Springer US (New York )
                1567-567X
                1573-8744
                9 February 2018
                9 February 2018
                2018
                : 45
                : 3
                : 443-456
                Affiliations
                ISNI 0000 0004 0572 4227, GRID grid.431072.3, Clinical Pharmacology and Pharmacometrics, , AbbVie Inc., ; 1 North Waukegan Road, Dept. R4PK, Bldg. AP31-3, North Chicago, IL 60064 USA
                Article
                9574
                10.1007/s10928-018-9574-0
                5953987
                29427135
                73028eeb-964e-40ee-add9-b787e9c9e33c
                © The Author(s) 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                : 11 October 2017
                : 23 January 2018
                Categories
                Original Paper
                Custom metadata
                © Springer Science+Business Media, LLC, part of Springer Nature 2018

                Pharmacology & Pharmaceutical medicine
                pbpk,amlodipine,systolic blood pressure,cyp3a4,dose adjustment,ritonavir

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