Mechanism-based PK/PD Modeling of the Respiratory Depressant Effect of Buprenorphine and Fentanyl in Healthy Volunteers

Abstract

The objective of this study was to characterize the pharmacokinetic/pharmacodynamic (PK/PD) relationship of buprenorphine and fentanyl for the respiratory depressant effect in healthy volunteers. Data on the time course of the ventilatory response at a fixed P(ET)CO(2) of 50 mm Hg and P(ET)O(2) of 110 mm Hg following intravenous administration of buprenorphine and fentanyl were obtained from two phase I studies (50 volunteers received buprenorphine: 0.05-0.6 mg/70 kg and 24 volunteers received fentanyl: 0.075-0.5 mg/70 kg). The PK/PD correlations were analyzed using nonlinear mixed effects modeling. A two- and three-compartment pharmacokinetic model characterized the time course of fentanyl and buprenorphine concentration, respectively. Three structurally different PK/PD models were evaluated for their appropriateness to describe the time course of respiratory depression: (1) a biophase distribution model with a fractional sigmoid E(max) pharmacodynamic model, (2) a receptor association/dissociation model with a linear transduction function, and (3) a combined biophase distribution-receptor association/dissociation model with a linear transduction function. The results show that for fentanyl hysteresis is entirely determined by the biophase distribution kinetics, whereas for buprenorphine hysteresis is caused by a combination of biophase distribution kinetics and receptor association/dissociation kinetics. The half-time values of biophase equilibration (t(1/2, k(eo))) were 16.4 and 75.3 min for fentanyl and buprenorphine, respectively. In addition, for buprenorphine, the value of k(on) was 0.246 ml/ng/min and the value of k(off) was 0.0102 min(-1). The concentration-effect relationship of buprenorphine was characterized by a ceiling effect at higher concentrations (intrinsic activity alpha=0.56, 95% confidence interval (CI): 0.50-0.62), whereas fentanyl displayed full respiratory depressant effect (alpha=0.91, 95% CI: 0.19-1.62).

Understanding the time course of pharmacological effect: a PKPD approach

“…Effect compartment models are intuitively appealing and, because of their simplicity, have been widely applied (e.g. fentanyl [28], d-tubocurarine [16], sotalol [29] and digoxin [30], see Table 1). …”

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

“…While this study demonstrates the influence of target concentrations on the target occupancy in different tissues, the influence of target concentrations on the occupancyresponse relationship has previously been described as the driving factor for tissue selectivity of partial agonists (61)(62)(63). Also, the influence of target expression and target accesibility on target saturation and its duration has been described in quantitative terms before (64).…”

Effects of Anesthetics, Sedatives, and Opioids on Ventilatory Control

“…In addition to measurement limitations, pharmacokinetics and pharmacodynamics seem to differ significantly between species for both intravenous anesthetics and opioids and seem subject to allometry (378). As a result, rodents (rats and mice) and other small mammals (rabbits) require much larger single doses (mg/kg) and infusion rates (mg/kg/h) of intravenous agents (61,482,491) and opioids (microgram/kg) (25,117,314,359,361,436,772,774) on a weight basis than larger mammals (dogs) and primates (humans). Finally, it is important to realize that only the free plasma concentrations in the aqueous phase of intravenous anesthetics or opioids seem to be relevant for the clinical effect, not the total plasma concentration.…”

“…In these in vitro preparations various bath concentrations of μ-opioid agonists have been used, ranging from 100 nM to more than 1 μM. Most of these opioid agonist concentrations are above the clinically relevant range of low nanomolar plasma concentrations that cause respiratory depression in humans (774) and rats (772) in vivo, and thus the results may not be directly applicable to the in vivo clinical scenario (see also Section "Opioid effects on respiratory neurons in vivo").…”

“…Theoretical diffusion-based modeling suggests that neuronal opioid receptors will be typically exposed to opioid agonist concentrations in the micromolar range (788). Such concentrations are several orders of magnitude higher than the nanomolar concentrations in plasma and brain, which are measured after clinically relevant systemic opioid doses, that are associated with clinical analgesia and respiratory depression (60,210,314,393,395,436,440,493,574,684,703,774).…”