Pierre O. Maitre

Population pharmacokinetics of alfentanil: the average dose-plasma concentration relationship and interindividual variability in patients

The population pharmacokinetic parameters describing the plasma concentration versus time profile of alfentanil in patients undergoing general anesthesia were determined from 614 plasma concentration measurements collected in four previously reported studies with a total of 45 patients. A nonlinear regression analysis evaluating the effect of six concomitant variables revealed a significant influence of body weight on the volume of the central compartment (Vc), and a decrease with age of total body clearance (CL) and of redistribution rate from the deep compartment (k31). A small but significant effect of sex on the Vc was also observed. The duration of anesthesia and the concomitant administration of inhalational anesthetics had no effect on alfentanil pharmacokinetic parameters. The mean CL and Vc for alfentanil in a 70-kg male, aged less than 40 yr, were estimated as 0.356 l/min and 7.77 l, respectively. After correction for age, body weight, and sex, the remaining interindividual variability of alfentanil kinetics (expressed as coefficient of variation) was 48% for CL and 33% for Vc. These population pharmacokinetic parameter estimates should increase the accuracy of predicting concentration-time profiles for intravenous alfentanil infusions. A computer program is presented that allows prediction of the alfentanil plasma concentration and the 68% interval limits of the prediction from the study data analysis.

A three-step approach combining bayesian regression and NONMEM population analysis: Application to midazolam

NONMEM, the only available supported program for population pharmacokinetic analysis, does not provide the analyst with individual subject parameter estimates. As a result, the relationship between pharmacokinetic parameters and demographic factors such as age, gender, and body weight cannot be sought by plotting demographic factors vs. kinetic parameters. To overcome this problem, we devised a three-step approach. In step 1, an initial NONMEM analysis provides the population pharmacokinetic parameters without taking into account the demographic factors. Step 2 consists of individual bayesian regressions using the measured drug concentrations for each subject and the population pharmacokinetic parameters obtained in step 1. The bayesian parameter estimates of the individual subject can be plotted against the demographic factors of interest. From the scatter plots, it can be seen which are the demographic factors that appear to affect the pharmacokinetic parameters. In step 3, the NONMEM analysis is resumed, and the demographic factors found in step 2 are entered into the NONMEM regression model in a stepwise manner. This method was used to analyze the pharmacokinetics of midazolam in 64 subjects from 714 plasma concentrations and 11 demographic factors. CL (elimination clearance) and V1were found to be a function of body weight. Age and liver disease were found to decrease CL. Of the 11 demographic factors recorded for each patient, none was found to influence Vssor intercompartmental clearance.

Population pharmacokinetics and pharmacodynamics of thiopental: the effect of age revisited

The authors have previously attributed the mechanism for the 50-67% decrease in the required dose of thiopental for induction of anesthesia in aged human patients to a decrease in the initial distribution volume for thiopental. Using a larger group of patients and volunteers studied in the laboratory, the authors have re-examined thiopental pharmacokinetics and EEG pharmacodynamics relative to age. A population data analysis approach (NONMEM), using a three-compartment model, was used to analyze bolus and rapid iv infusion thiopental serum concentration versus time data from 64 subjects. A one-compartment model was also used on the first 10 min of serum concentration data to focus only on the initial distribution phase. The population pharmacokinetic analysis demonstrated that when thiopental is administered via an iv bolus injection, traditional pharmacokinetic models limit the accurate characterization of thiopental distribution phenomena. Using the rapid iv infusion data, the pharmacokinetic mechanism for the decreased thiopental dose requirement in the elderly was a decreased rapid intercompartment clearance. Thiopental distribution from the central compartment of the three-compartment model to the rapidly equilibrating compartment (rapid intercompartment clearance) decreased 27% between the ages of 35-80 yr and decreased 34% in the one-compartment analysis. EEG spectral edge versus time data from 37 subjects was analyzed with a semiparametric modelling approach to remove the disequilibrium between thiopental serum concentration and the spectral edge. A population data analysis (NONMEM) was performed with several pharmacodynamic models. There was no age-related change in brain responsiveness or pharmacodynamics when the spectral edge is used as a measure of drug effect.

Electroencephalographic effects of benzodiazepines. II. Pharmacodynamic modeling of the electroencephalographic effects of midazolam and diazepam

The comparative pharmacodynamics of midazolam and diazepam were examined by use of the electroencephalogram as a measure of drug effect on the central nervous system. Intravenous doses of 7.5, 15, and 25 mg midazolam and 15, 30, and 50 mg diazepam were given on repeated occasions to three volunteers. Arterial plasma concentration and electroencephalogram voltage were related with nonparameteric and parametric pharmacodynamic models. The peak increases in voltage (maximal effect) and the slopes of the plasma concentration versus effect curve were similar for both drugs. The half‐time of blood:brain equilibration was significantly longer for midazolam than diazepam (4.8 minutes versus 1.6 minutes). Midazolam was found to have an intrinsic steady‐state potency that was approximately five times greater than that of diazepam (152 ng/ml versus 958 ng/ml).

Thiopental Pharmacodynamics I. Defining the Pseudo–Steady-state Serum Concentration–EEG Effect Relationship

To assess depth of anesthesia for intravenous anesthetics using clinical stimuli and observed responses, it is necessary to achieve constant serum concentrations of drug that result in constant biophase or central nervous system concentrations. The goal of this investigation was to use a computer-controlled infusion pump (CCIP) to obtain constant serum thiopental concentrations and use the electroencephalogram (EEG) as a measure of thiopentals central nervous system drug effect. The number of waves per second obtained from aperiodic waveform analysis was used as the EEG measure. A CCIP was used in six male volunteers to attain rapidly and then maintain for 6-min time periods the following pseudo-steady-state constant serum thiopental target concentrations: 10, 20, 30, and 40 micrograms/ml. The median performance error (bias) of the CCIP using 149 measurements of thiopental serum concentrations in six subjects was +5%, and the median absolute performance error (accuracy) was 16%. Following the step change in serum thiopental concentration, the EEG number of waves per second stabilized within 2-3 min and the remained constant until the target serum thiopental concentration was changed. When the constant serum thiopental concentration was plotted against the number of waves per second for each subject, a biphasic serum concentration versus EEG effect relationship was seen. This biphasic concentration:response relationship was characterized with a nonparametric pharmacodynamic model. The awake, baseline EEG was 10.6 waves/s; at peak activation the EEG was 19.1 waves/s and occurred at a serum thiopental concentration of 13.3 micrograms/ml. At a serum thiopental concentration of 31.2 micrograms/ml the EEG had slowed to 10.6 waves/s (back to baseline) and at 41.2 micrograms/ml was 50% below the baseline, awake value. Zero waves per second occurred at serum thiopental concentrations greater than 50 micrograms/ml. Using a CCIP it is possible to establish constant serum thiopental concentration rapidly and characterize the concentration versus EEG drug effect relationship.

Dexmedetomidine Decreases Thiopental Dose Requirement and Alters Distribution Pharmacokinetics

Backgroundα2-Adrenergic agonists such as dexmedetomidine can be used to reduce the dose requirement of intravenous and volatile anesthetics. Whereas dexmedetomidine and volatile anesthetics interact pharmacodynamically (reduction of MAC), the mechanism of interaction between dexmedetomidine and intravenous anesthetics is not known. MethodsFourteen male ASA physical status 1 patients were randomly assigned to serve as control subjects (n = 7) or to be treated with dexmedetomidine (n = 7; 100, 30, and 6 ng. kg−1. min−1 for 10 min, 15 min, and thereafter, respectively). After 35 min, in all patients, thiopental (100 mg/min) was infused until burst suppression appeared in the raw tracing of the electroencephalogram. By using concentrations of thiopental in plasma and the electroencephalogram as a continuous pharmacologic effect measure, the apparent effect site concentrations for thiopental were estimated in both groups. Three-compartment pharmacokinetics were calculated for thiopental. ResultsDexmedetomidine reduced the thiopental dose requirement for electroencephalographic burst suppression by 30%. There was no difference in estimated thiopental effect site concentrations between dexmedetomidine and control patients, suggesting the absence of a major pharmacodynamic interaction. Dexmedetomidine significantly decreased distribution volumes (V2, V3, and Vdss) and distribution clearances (Cl1Z and Cl13) of thiopental. ConclusionsThe thiopental dose-sparing effect of dexmedetomidine on the electroencephalogram is not the result of a pharmacodynamic interaction but rather can be explained by a dexmedetomidlne-lnduced decrease in thiopental distribution volume and distribution clearances. Dexmedetomidine reduces thiopental distribution, most probably by decreasing cardiac output and regional blood flow.

Electroencephalographic effects of benzodiazepines. I. Choosing an electroencephalographic parameter to measure the effect of midazolam on the central nervous system.

The goal of this investigation was to determine a numerical electroencephalographic parameter that best indicated the degree of the effect of midazolam, administered in hypnotic doses, on the central nervous system. This electroencephalographic parameter could then be used to relate midazolam plasma concentrations and electroencephalographic drug effect (pharmacodynamic modeling). Intravenous doses of midazolam (3.75 to 25 mg) were given to five men at an infusion rate of 5 mg/min. A cortical electroencephalogram was continuously recorded. Two waveform analysis approaches were examined: fast Fourier transformation and aperiodic analysis. From fast Fourier transformation and aperiodic analysis a set of parameters were examined as measures of drug effect. We conclude that the voltage per second from aperiodic analysis provided the electroencephalographic parameter that optimally measured the effect of midazolam on the central nervous system.

Bayesian Forecasting Improves the Prediction of Intraoperative Plasma Concentrations of Alfentanil

To achieve therapeutic plasma concentrations of the opioid alfentanil, one must administer the drug as a variable rate continuous infusion. For most patients, using population pharmacokinctic parameters of alfentanil for dosing regimen allows accurate prediction of the plasma concentration of the drug over time. However, for some patients, using such parameters results in systematic over- or underprediction of the concentration. Retrospectively studying a data set (dosage history and measured concentrations) for 34 patients, the authors examined how Bayesian forecasting could improve the precision of prediction. For each patient, a Bayesian regression was performed to estimate “individualized” pharmacokinetic parameters, using population pharmacokinetic values for alfentanil and the measurement of alfentanil in one or more plasma samples from each patient. These individualized parameters were then used to predict the subsequent plasma concentrations of alfentanil over time. By comparing the value of each measured point with its corresponding predicted value, the authors calculated the prediction error as a percentage of the measured value. The precision of the prediction was assessed by the percent mean absolute prediction error. After Bayesian forecasting using a single point sampled at 80 min after start of anesthesia, the average precision of the prediction was 13.8 ± 6.1% (SD). Using no Bayesian forecasting and only population values of the pharmacokinetic parameters for the prediction of the concentration, the precision was 24.3 ± 16.9%. The improvement in precision brought by Bayesian forecasting was especially noticeable for those patients whose prediction of alfentanil was poor using population pharmacokinetic values (i.e., “outlier” patients). These results suggest that Bayesian forecasting may facilitate optimal administration of alfentanil during long procedures and that a rapid assay should be developed to measure plasma concentrations of alfentanil intraoperatively.

Chronic alcohol intake does not change thiopental anesthetic requirement, pharmacokinetics, or pharmacodynamics.

The anesthetic requirements of chronic alcoholics for induction of anesthesia with thiopental were investigated using an electroencephalographic (EEG) measure of thiopentals CNS drug effect and pharmacodynamic modeling to relate thiopental serum concentrations to drug effect. Eleven patients with a history of excessive alcohol intake were studied from an inpatient alcohol rehabilitation program and compared with nine control patients or volunteers who were social drinkers. The alcoholic population had consumed ethanol 9-17 days prior to the study. They had no evidence of acute intoxication or acute withdrawal at the time of the study. Five of the 11 alcoholic patients were restudied after 1 month of abstinence from alcohol consumption. Each study consisted of a thiopental infusion until EEG burst suppression (1-3 s of isoelectric signal) was achieved. Timed arterial and then venous blood samples were obtained for measurement of thiopental serum concentrations for up to 36 h. Pharmacokinetic differences between groups were analyzed using a three-compartment model. Power spectral analysis of the EEG allowed determination of spectral edge frequency. An inhibitory sigmoid Emax pharmacodynamic model combined with an effect compartment was used to analyze concentration-response relationships and to provide an estimate of brain sensitivity to thiopental in the study populations. The thiopental anesthetic dose requirement using the EEG was not different between alcoholics and nonalcoholics. The mean dose requirement (+/- SD) of alcoholics was 823 +/- 246 mg and the mean dose requirement of nonalcoholics was 733 +/- 218 mg. There were no differences in thiopental pharmacokinetic and pharmacodynamic parameters between alcoholics and nonalcoholics.(ABSTRACT TRUNCATED AT 250 WORDS)

A Simple Pocket Calculator Approach to Predict Anesthetic Drug Concentrations from Pharmacokinetic Data

Use of pharmacokinetic concepts to predict anesthetic drug concentrations has not had extensive use in clinical anesthetic practice to date. The multiple exponent equations needed to describe iv drug disposition have required computer capability not practical for the operating room. An algorithm is presented that allows the clinician to use information from the pharmacokinetic literature to improve accuracy of drug dosing in the operating room. Implemented on a pocket calculator, this approach does not involve complex mathematics or lengthy computations and allows the clinician to obtain a continuous prediction of the plasma anesthetic concentration during the course of the anesthetic from iv bolus or continuous infusion of anesthetic drugs.