Mechanism-based pharmacokinetic-pharmacodynamic (PK-PD) modeling in translational drug research

Danhof, Meindert; Lange, Elizabeth C. M. de; Pasqua, Oscar Della; Ploeger, Bart; Voskuyl, Rob A.

doi:10.1016/j.tips.2008.01.007

Cited by 259 publications

(167 citation statements)

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“…These quantitative PD markers should reflect features of drug exposure and drug response with respect to modulation of the molecular target, the cognate biochemical pathways and/or downstream biological effects. 10,11 The availability of these quantitative PD markers may provide a rational basis for decision making during, for example, treatment optimization. A relatively easy to measure PD marker currently described for TNF-blocking therapy is serum C-reactive protein levels.…”

Section: Discussionmentioning

confidence: 99%

Pharmacogenomics of infliximab treatment using peripheral blood cells of patients with rheumatoid arthritis

et al. 2010

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Section: Discussionmentioning

confidence: 99%

Pharmacogenomics of infliximab treatment using peripheral blood cells of patients with rheumatoid arthritis

et al. 2010

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“…Applications of the developed model, using the identified set of system parameters, are limited to SHR and WKY rats. However, as a mechanism-based modelling approach was applied, it is foreseen that accurate extrapolation between different rat strains and from one species to another is possible (Danhof et al, 2008;Ploeger et al, 2009). This requires the differences in the values of the system-specific parameters between the different species to be known.…”

Section: Hr and Map Measurements Only And System Propertiesmentioning

confidence: 99%

Drug effects on the CVS in conscious rats: separating cardiac output into heart rate and stroke volume using PKPD modelling

Snelder

Ploeger

Luttringer

et al. 2014

British J Pharmacology

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BACKGROUND AND PURPOSEPreviously, a systems pharmacology model was developed characterizing drug effects on the interrelationship between mean arterial pressure (MAP), cardiac output (CO) and total peripheral resistance (TPR). The present investigation aims to (i) extend the previously developed model by parsing CO into heart rate (HR) and stroke volume (SV) and (ii) evaluate if the mechanism of action (MoA) of new compounds can be elucidated using only HR and MAP measurements. EXPERIMENTAL APPROACHCardiovascular effects of eight drugs with diverse MoAs (amiloride, amlodipine, atropine, enalapril, fasudil, hydrochlorothiazide, prazosin and propranolol) were characterized in spontaneously hypertensive rats (SHR) and normotensive Wistar-Kyoto (WKY) rats following single administrations of a range of doses. Rats were instrumented with ascending aortic flow probes and aortic catheters/radiotransmitters for continuous recording of MAP, HR and CO throughout the experiments. Data were analysed in conjunction with independent information on the time course of the drug concentration following a mechanism-based pharmacokinetic-pharmacodynamic modelling approach. KEY RESULTSThe extended model, which quantified changes in TPR, HR and SV with negative feedback through MAP, adequately described the cardiovascular effects of the drugs while accounting for circadian variations and handling effects. CONCLUSIONS AND IMPLICATIONSA systems pharmacology model characterizing the interrelationship between MAP, CO, HR, SV and TPR was obtained in hypertensive and normotensive rats. This extended model can quantify dynamic changes in the CVS and elucidate the MoA for novel compounds, with one site of action, using only HR and MAP measurements. Whether the model can be applied for compounds with a more complex MoA remains to be established. Abbreviations amp, amplitude; BSL_CO, baseline value of cardiac output; BSL_HR, baseline value of heart rate; BSL_MAP, baseline value of mean arterial pressure; BSL_SV, baseline value of stroke volume; BSL_TPR, baseline value of total peripheral resistance; C, drug concentration in plasma; CO, cardiac output; Emax, maximum effect; FB, negative feedback of mean arterial pressure; FB0, feedback of a typical subject; FB0_MAP, exponent of the power relationship between FB and the individual BSL_MAP; HCTZ, hydrochlorothiazide; hor, horizontal displacement; HR, heart rate; Kin_HR, zero-order production rate constant of HR; Kin_SV, zero-order production rate constant of stroke volume; Kin_TPR, zero-order production rate constant of total peripheral resistance; kout_HR, first-order dissipation rate constant of HR; kout_SV, first-order dissipation rate constant of stroke volume; kout_TPR, first-order dissipation rate constant of total peripheral resistance; LVFT, left ventricular filling time; MAP, mean arterial pressure; MoA, mechanisms of action; MVOF, minimum value of the objective function;

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“…PK and PD have long been considered to be separate disciplines, and the time course of the pharmacological effect of a drug has essentially been considered in terms of the temporal fluctuation of its free concentration [2]. In accordance with this principle, the frequently observed time lag between the concentration of a drug in the systemic circulation and its effect was initially attributed to slow equilibration between the plasma and a hypothetical target-surrounding 'effect compartment' [3]. By contrast, preclinical screening studies traditionally aim to optimize drug candidates in terms of only their efficacy and potency (i.e.…”

Section: Introductionmentioning

confidence: 99%

Cell membranes… and how long drugs may exert beneficial pharmacological activity in vivo

Vauquelin

2016

Brit J Clinical Pharma

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The time course of the beneficial pharmacological effect of a drug has long been considered to depend merely on the temporal fluctuation of its free concentration. Only in the last decade has it become widely accepted that target-binding kinetics can also affect in vivo pharmacological activity. Although current reviews still essentially focus on genuine dissociation rates, evidence is accumulating that additional micro-pharmacokinetic (PK) and -pharmacodynamic (PD) mechanisms, in which the cell membrane plays a central role, may also increase the residence time of a drug on its target. The present review provides a compilation of otherwise widely dispersed information on this topic. The cell membrane can intervene in drug binding via the following three major mechanisms: (i) by acting as a sink/repository for the drug; (ii) by modulating the conformation of the drug and even by participating in the binding process; and (iii) by facilitating the approach (and rebinding) of the drug to the target. To highlight these mechanisms, we focus on drugs that are currently used in clinical therapy, such as the antihypertensive angiotensin II type 1 receptor antagonist candesartan, the atypical antipsychotic agent clozapine and the bronchodilator salmeterol. Although the role of cell membranes in PK-PD modelling is gaining increasing interest, many issues remain unresolved. It is likely that novel biophysical and computational approaches will provide improved insights in the near future. IntroductionThe pharmacokinetic (PK) and pharmacodynamic (PD) properties of a drug are determinants of its efficacy and the duration of its clinical action [1]. PK and PD have long been considered to be separate disciplines, and the time course of the pharmacological effect of a drug has essentially been considered in terms of the temporal fluctuation of its free concentration [2]. In accordance with this principle, the frequently observed time lag between the concentration of a drug in the systemic circulation and its effect was initially attributed to slow equilibration between the plasma and a hypothetical target-surrounding 'effect compartment' [3]. By contrast, preclinical screening studies traditionally aim to optimize drug candidates in terms of only their efficacy and potency (i.e. PD properties). Inherent to this practice is the proposal that drug-target interactions are adequately described by equilibrium equations and, hence, that association and dissociation rates play only subordinate roles. In addition to a few noteworthy exceptions [4,5], it is only in the last decade that it has become fashionable to include binding kinetics as an additional criterion for clinical efficacy. This insight was largely sparked by the seminal articles by Swinney [6] and Copeland et al. [7]. The numerous review articles that have been published subsequently have focused mainly on long residence times. This property is now recognized to play a key role with respect to the clinical British Journal of Clinical Pharmacology Br J Clin Pharmacol (2016...

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Mechanism-based pharmacokinetic-pharmacodynamic (PK-PD) modeling in translational drug research

Cited by 259 publications

References 24 publications

Pharmacogenomics of infliximab treatment using peripheral blood cells of patients with rheumatoid arthritis

Pharmacogenomics of infliximab treatment using peripheral blood cells of patients with rheumatoid arthritis

Drug effects on the CVS in conscious rats: separating cardiac output into heart rate and stroke volume using PKPD modelling

Cell membranes… and how long drugs may exert beneficial pharmacological activity in vivo

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