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Zolpidem is a nonbenzodiazepine GABA(A) receptor modulator that binds in vitro with high affinity to GABA(A) receptors expressing alpha(1) subunits but with relatively low affinity to receptors expressing alpha(2), alpha(3), and alpha(5) subunits. In the present study, it was investigated whether this subtype selectivity could be detected and quantified in vivo. Three doses (1.25, 5, and 25 mg) of zolpidem were administered to rats in an intravenous infusion over 5 min. The time course of the plasma concentrations was determined in conjunction with the change in the beta-frequency range of the EEG as pharmacodynamic endpoint. The concentration-effect relationship of the three doses showed a dose-dependent maximum effect and a dose-dependent potency. The data were analyzed for one- or two-site binding using two pharmacodynamic models based on 1) the descriptive model and 2) a novel mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) model for GABA(A) receptor modulators that aims to separates drug- and system-specific properties, thereby allowing the estimation of in vivo affinity and efficacy. The application of two-site models significantly improved the fits compared with one-site models. Furthermore, in contrast to the descriptive model, the mechanism-based PK/PD model yielded dose-independent estimates for affinity (97 +/- 40 and 33,100 +/- 14,800 ng x ml(-1)). In conclusion, the mechanism-based PK/PD model is able to describe and explain the observed dose-dependent EEG effects of zolpidem and suggests the subtype selectivity of zolpidem in vivo.

A mechanism-based pharmacokinetic-pharmacodynamic (PK/PD) model for neuroactive steroids, comprising a separate characterization of 1) the receptor activation process and 2) the stimulus-response relationship, was applied to various nonsteroidal GABAA receptor modulators. The EEG effects of nine prototypical GABAA receptor modulators (six benzodiazepines, one imidazopyridine, one cyclopyrrolone, and one beta-carboline) were determined in rats in conjunction with plasma concentrations. Population PK/PD modeling revealed monophasic concentration-EEG effect relationships with large differences in potency (EC50) and intrinsic activity between the compounds. The data were analyzed on the basis of the mechanism-based PK/PD model for (synthetic) neuroactive steroids on the assumption of a single and unique stimulus-response relationship. The model converged yielding estimates of both the apparent in vivo receptor affinity (KPD) and the in vivo intrinsic efficacy (ePD). The values of KPD ranged from 0.41 +/- 0 ng.ml(-1) for bretazenil to 436 +/- 72 ng.ml(-1) for clobazam and the values for e(PD) from -0.27 +/- 0 for methyl 6,7-dimethoxy-4-ethyl-beta-carboline-3-carboxylate to 0.54 +/- 0.02 for diazepam. Significant linear correlations were observed between KPD for unbound concentrations and the affinity in an in vitro receptor bioassay (r = 0.93) and between e(PD) and the GABA-shift in vitro (r = 0.95). The findings of this investigation show that the in vivo effects of nonsteroidal GABAA receptor modulators and (synthetic) neuroactive steroids can be described on the basis of a single unique transducer function. In this paradigm, the nonsteroidal GABAA receptor modulators behave as partial agonists relative to neuroactive steroids.

The objective of the present investigation was to characterize the in vivo EEG effects of (synthetic) neuroactive steroids on the basis of a recently proposed mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) model. After intravenous administration, the time course of the EEG effect of pregnanolone, 2beta-3alpha-5alpha-3-hydroxy-2-(2,2-dimethylmorpholin-4-yl)-pregnan-11,20-dione (ORG 21465), 2beta-3alpha-5alpha-21-chloro-3-hydroxy-2-(4-morpholinyl)-pregnan-20-one (ORG 20599), and alphaxalone was determined in conjunction with plasma concentrations in rats. For each neuroactive steroid the PK/PD correlation was described on the basis of a two-compartment pharmacokinetic model with an effect compartment to account for hysteresis. The observed concentration EEG effect relationships were biphasic and characterized with a mechanism-based pharmacodynamic model, which is based on a separation between the receptor activation process and the stimulus-response relationship. A single unique biphasic stimulus-response relationship could be identified for all neuroactive steroids, which was successfully described by a parabolic function. The receptor activation process was described by a hyperbolic function. Estimates for the maximum activation (e(PD)) were similar for the different neuroactive steroids but values of the potency estimate (K(PD)) ranged from 157 +/- 16 ng. ml(-1) for pregnanolone, 221 +/- 83 ng. ml(-1) for ORG 20599, and 483 +/- 42 ng. ml(-1) for alphaxalone to 1619 +/- 208 ng. ml(-1) for ORG 21465. A statistically significant correlation was observed between the in vivo potency and the IC(50) in an in vitro [(35)S]t-butylbicyclophosphorothionate binding assay (r = 0.91). It is concluded that the new PK/PD model constitutes a new mechanism-based approach to the quantification of the effects of (synthetic) neuroactive steroids in vivo effects. The results show that the neuroactive steroids differ in potency but not in intrinsic efficacy at the GABA(A) receptor in vivo.

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.

The purpose of our investigation was to characterize the relationships between the pharmacodynamics of synthetic opioids in vivo and the interaction at the mu-opioid receptor. The pharmacokinetics and pharmacodynamics were determined in vivo after a single i.v. infusion of 3.14 mg/kg alfentanil (A), 0.15 mg/kg fentanyl (F) or 0.030 mg/kg sufentanil (S) in rats. Amplitudes in the 0.5 to 4.5 Hz frequency band of the electroencephalogram (EEG) was used as pharmacodynamic endpoint. The EEG effect intensity was related to the (free) concentration in blood (A) or in a hypothetical effect compartment (F, S) on basis of the sigmoidal Emax pharmacodynamic model. The interaction at the mu-opioid receptor was determined in vitro on basis of the displacement of [3H]-naloxone binding in washed rat brain membranes. The value of the sodium shift was used as a measure of in vitro intrinsic efficacy. For the EEG effect the in vivo potencies based on free drug concentrations (EC50,u) were 4.62 +/- 0.66 ng/ml (A), 0.69 +/- 0.05 ng/ml (F) and 0.29 +/- 0.06 ng/ml (S). In the receptor binding studies the affinities at the mu-opioid receptor (Kl) were 47.4 +/- 6.6 nM (A), 8.6 +/- 4.1 nM (F) and 2.8 +/- 0.2 nM (S). For each opioid the ratio between EC50,u and Kl was the same with a value of 0.23-0.25, indicating the existence of receptor reserve for the EEG effect. The intrinsic activity (Emax) of the three opioids in vivo was similar with values of 111 +/- 10 microV (A), 89 +/- 11 microV (F) and 104 +/- 4 microV (S). However, the values of the sodium shift varied between 2.8 (S) and 19.1 (A). Further analysis of the in vivo pharmacodynamic data on basis of an operational model of agonism provided evidence for a large receptor reserve, which explains why compounds with different values of the sodium shift all behave as full agonists in vivo.

We have developed a pharmacokinetic-pharmacodynamic strategy based on the operational model of agonism to obtain estimates of apparent affinity and efficacy of N6-cyclopentyladenosine (CPA) analogs for the adenosine A1 receptor-mediated in vivo effect on heart rate in the rat. All analogs investigated produced a significant decrease of the heart rate after intravenous infusion. Individual concentration-effect curves were fitted to the operational model of agonism with the values of Emax and n constrained to the intrinsic activity (273 bpm) and Hill slope (1.18), respectively, obtained with the agonist that displayed the highest intrinsic activity, 5'-deoxy-CPA. In all cases, the model converged and estimates of apparent affinity and efficacy were obtained for each agonist. Affinity estimates correlated well with pKi values for the adenosine A1 receptor in rat brain homogenates. In addition, a highly significant correlation was found between the estimates of the in vivo efficacy parameter and the GTP shift (the ratio between Ki in the presence and absence of GTP). In conclusion, the operational model of agonism can provide meaningful measures of agonist affinity and efficacy at adenosine A1 receptors in vivo. The model should be of use in the development of partial adenosine A1 receptor agonists.