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Background: Anesthetic drug interactions traditionally have been characterized using isobolographic analysis or multiple logistic regression. Both approaches have significant limitations. The authors propose a model based on response-surface methodology. This model can characterize the entire dose-response relation between combinations of anesthetic drugs and is mathematically consistent with models of the concentration-response relation of single drugs., Methods: The authors defined a parameter, theta, that describes the concentration ratio of two potentially interacting drugs. The classic sigmoid Emax model was extended by making the model parameters dependent on theta. A computer program was used to estimate response surfaces for the hypnotic interaction between midazolam, propofol, and alfentanil, based on previously published data. The predicted time course of effect was simulated after maximally synergistic bolus dose combinations., Results: The parameters of the response surface were identifiable. With the test data, each of the paired combinations showed significant synergy. Computer simulations based on interactions at the effect site predicted that the maximally synergistic three-drug combination tripled the duration of effect compared with propofol alone., Conclusions: Response surfaces can describe anesthetic interactions, even those between agonists, partial agonists, competitive antagonists, and inverse agonists. Application of response-surface methodology permits characterization of the full concentration-response relation and therefore can be used to develop practical guidelines for optimal drug dosing.

Background: The authors studied the influence of age on the pharmacodynamics of propofol, including characterization of the relation between plasma concentration and the time course of drug effect., Methods: The authors evaluated healthy volunteers aged 25-81 yr. A bolus dose (2 mg/kg or 1 mg/kg in persons older than 65 yr) and an infusion (25, 50, 100, or 200 microg x kg(-1) x min(-1)) of the older or the new (containing EDTA) formulation of propofol were given on each of two different study days. The propofol concentration was determined in frequent arterial samples. The electroencephalogram (EEG) was used to measure drug effect. A statistical technique called semilinear canonical correlation was used to select components of the EEG power spectrum that correlated optimally with the effect-site concentration. The effect-site concentration was related to drug effect with a biphasic pharmacodynamic model. The plasma effect-site equilibration rate constant was estimated parametrically. Estimates of this rate constant were validated by comparing the predicted time of peak effect with the time of peak EEG effect. The probability of being asleep, as a function of age, was determined from steady state concentrations after 60 min of propofol infusion., Results: Twenty-four volunteers completed the study. Three parameters of the biphasic pharmacodynamic model were correlated linearly with age. The plasma effect-site equilibration rate constant was 0.456 min(-1). The predicted time to peak effect after bolus injection ranging was 1.7 min. The time to peak effect assessed visually was 1.6 min (range, 1-2.4 min). The steady state observations showed increasing sensitivity to propofol in elderly patients, with C50 values for loss of consciousness of 2.35, 1.8, and 1.25 microg/ml in volunteers who were 25, 50, and 75 yr old, respectively., Conclusions: Semilinear canonical correlation defined a new measure of propofol effect on the EEG, the canonical univariate parameter for propofol. Using this parameter, propofol plasma effect-site equilibration is faster than previously reported. This fast onset was confirmed by inspection of the EEG data. Elderly patients are more sensitive to the hypnotic and EEG effects of propofol than are younger persons.

Background: Unresolved issues with propofol include whether the pharmacokinetics are linear with dose, are influenced by method of administration (bolus vs. infusion), or are influenced by age. Recently, a new formulation of propofol emulsion, containing disodium edetate (EDTA), was introduced in the United States. Addition of EDTA was found by the manufacturer to significantly reduce bacterial growth. This study investigated the influences of method of administration, infusion rate, patient covariates, and EDTA on the pharmacokinetics of propofol., Methods: Twenty-four healthy volunteers aged 26-81 yr were given a bolus dose of propofol, followed 1 h later by a 60-min infusion. Each volunteer was randomly assigned to an infusion rate of 25, 50, 100, or 200 microg x kg(-1) x min(-1). Each volunteer was studied twice under otherwise identical circumstances: once receiving propofol without EDTA and once receiving propofol with EDTA. The influence of the method of administration and of the volunteer covariates was explored by fitting a three-compartment mamillary model to the data. The influence of EDTA was investigated by direct comparison of the measured concentrations in both sessions., Results: The concentrations of propofol with and without EDTA were not significantly different. The concentration measurements after the bolus dose were significantly underpredicted by the parameters obtained just from the infusion data. The kinetics of propofol were linear within the infusion range of 25-200 microg x kg(-1) x min(-1). Age was a significant covariate for Volume2 and Clearance2, as were weight, height, and lean body mass for the metabolic clearance., Conclusions: These results demonstrate that method of administration (bolus vs. infusion), but not EDTA, influences the pharmacokinetics of propofol. Within the clinically relevant range, the kinetics of propofol during infusions are linear regarding infusion rate.

Background: In spinal anesthesia, often a large interindividual variability in analgesic response is observed after administration of a certain fixed dose of anesthetic to a patient population. To improve therapeutic outcome it is important to characterize the variability in response by means of a population model (e.g., mixed-effects models or two-stage approaches). The purpose of this investigation is to derive a population model for spinal anesthesia with plain bupivacaine. Based on the population models, a description of a patient's time course of drug action is obtained, the influence of patient covariates on clinically important endpoints is examined, and the success of Bayesian forecasting of the offset of effect in a specific patient from the data obtained during onset is evaluated., Methods: The level of central neural blockade after intrathecal injection of plain bupivacaine was assessed by testing analgesia to pinprick. A total of 714 measurements in 96 patients (4-10 per subject) were available for analysis. Two pharmacodynamic models, based on the understanding of the physiology of the spread of local anesthetic in the spinal fluid, were evaluated to characterize the time course of analgesia in a specific patient. The first model is a combination of a biexponential pharmacokinetic model, describing the onset and offset of effect and a linear pharmacodynamic model. The second model combines the biexponential pharmacokinetic model with an Emax type pharmacodynamic model. The interindividual variability in model parameters was modeled by an exponential variance model. An additional term characterized the residual error. The population mean parameters, interindividual variance, and residual variance were estimated using the first-order conditional estimate method in the NONMEM software package. Clinically important endpoints such as onset time, time to reach the maximal level, the maximal level, and the duration of analgesia were estimated from the Bayesian fit of each subject's data and correlated with patient-specific covariates. Using Bayesian forecasting, the offset of spinal analgesia was predicted for each patient based on the population model and measurements from the first 30 min and from the first 60 min, respectively., Results: The Emax type pharmacodynamic model was superior based on the improvement in likelihood (P < 0.001) and on visual inspection of the fits. The estimates of the population mean parameters (coefficient of variation) were: (1) maximal effects: T4, which was coded for the purpose of the calculation as 18 (14%); (2) rate of offset of effect: 0.0118 (26%) min-1; (3) rate of onset of effect: 0.061 (45%) min-1. The standard deviation of the residual error was 1.4. Large interindividual differences were observed in the time course of analgesic response and clinically important endpoints. The mean onset time; that is, time to reach T10 (interindividual variability) was 4.2 min (90%), the mean time to maximal level was 35.5 min (29%), the mean duration of effect was 172 min (28%), and the mean maximal achieved level was T6 (12%). Significant correlations between onset time and height and weight, between time to maximal level and age, between maximal level and weight and height, and between duration and height were found. Bayesian regression using the population model and data from the first 30 min and from the first 60 min predicted the offset of effect in each patient reasonably well, with coefficients of determination (R2) of 0.71 and 0.72. This is a significant improvement over the population mean prediction., Conclusion: A population model was derived for the description of the time course of central neural blockade. Based on the population model, a continuous effect profile over time was obtained for each person...

Background: Lidocaine administered intravenously is efficacious in treating neuropathic pain at doses that do not cause sedation or other side effects. Using a computer-controlled infusion pump (CCIP), it is possible to maintain the plasma lidocaine concentration to allow drug equilibration between the plasma and the site of the drug effect. Pharmacokinetic parameters were derived for CCIP administration of lidocaine in patients with chronic pain., Methods: Thirteen patients (mean age 45 yr, mean weight 66 kg) were studied. Eight subjects received a computer-controlled infusion, targeting four increasing lidocaine concentrations (1-7 micrograms.ml-1) for 30 min each, based on published kinetic parameters in which venous samples were obtained infrequently after bolus administration. From the observations in these eight patients, new lidocaine pharmacokinetic parameters were estimated. These were prospectively tested in five additional patients. From the complete data set (13 patients), final structural parameters were estimated using a pooled analysis approach. The interindividual variability was determined with a mixed-effects model, with the structural model parameters fixed at the values obtained from the pooled analysis. Internal cross-validation was used to estimate the residual error in the final pharmacokinetic model., Results: The lidocaine administration based on the published parameters consistently produced higher concentrations than desired, resulting in acute lidocaine toxicity in most of the first eight patients. The highest measured plasma concentration was 15.3 micrograms.ml-1. The pharmacokinetic parameters estimated from these eight patients differed from the initial estimates and included a central volume one-sixth of the initial estimate. In the subsequent prospective test in five subjects, the new parameters resulted in concentrations evenly distributed around the target concentration. None of the second group of subjects had evidence of acute lidocaine toxicity. The final parameters ( +/- population variability expressed as %CV) were estimated as follows: V1 0.101 +/- 53% 1.kg-1, V2 0.452 +/- 33% 1.kg-1, Cl1 0.0215 +/- 25% 1.kg-1.min-1, and Cl2 0.0589 +/- 35% 1.kg-1.min-1. The median error measured by internal cross-validation was +1.9%, and the median absolute error was 14%., Conclusions: Pharmacokinetic parameters for lidocaine were derived and administration was prospectively tested via computer-controlled infusion pumps for patients with chronic neuropathic pain. The estimated parameters performed well when tested prospectively. A second estimation step further refined the parameters and improved performance, as measured using internal cross-validation.

Background: Remifentanil is an esterase-metabolized opioid with a rapid clearance. The aim of this study was to contrast the pharmacokinetics and pharmacodynamics of remifentanil and alfentanil in healthy, adult male volunteers., Methods: Ten volunteers received infusions of remifentanil and alfentanil on separate study sessions using a randomized, open-label crossover design. Arterial blood samples were analyzed to determine drug blood concentrations. The electroencephalogram was employed as the measure of drug effect. The pharmacokinetics were characterized using a moment analysis, a nonlinear mixed effects model (NONMEM) population analysis, and context-sensitive half-time computer simulations. After processing the raw electroencephalogram to obtain the spectral edge parameter, the pharmacodynamics were characterized using an effect compartment, inhibitory maximum effect model., Results: Pharmacokinetically, the two drugs are similar in terms of steady-state distribution volume (VD(SS)), but remifentanil's central clearance (CLc)) is substantially greater. The NONMEM analysis population pharmacokinetic parameters for remifentanil include a CLc of 2.9 l x min(-1), a VDss of 21.81, and a terminal half-life of 35.1 min. Corresponding NONMEM parameters for alfentanil are 0.36 l x min(-1), 34.11, and 94.5 min. Pharmacodynamically, the drugs are similar in terms of the time required for equilibration between blood and the effect-site concentrations, as evidenced by a T(12)k(e0) for remifentanil of 0.75 min [corrected] and 0.96 min for alfentanil. However, remifentanil is 19 times more potent than alfentanil, with an effective concentration for 50% maximal effect of 19.9 ng x ml(-1) versus 375.9 ng x ml(-1) for alfentanil., Conclusions: Compared to alfentanil, the high clearance of remifentanil, combined with its small steady-state distribution volume, results in a rapid decline in blood concentration after termination of an infusion. With the exception of remifentanil's nearly 20-times greater potency (30-times if alfentanil partitioning between whole blood and plasma is considered), the drugs are pharmacodynamically similar.

Background: The electroencephalographic (EEG) effect of benzodiazepines, and midazolam in particular, has been described using simple measures such as total power in the beta band, waves.s(-1) in the beta band and total power from aperiodic analysis. All these parameters failed to consistently describe the EEG effect of midazolam in a study in which large doses of midazolam were infused, and the effect subsequently reversed with flumazenil. Using a technique called semilinear correlation it is possible to extract a parameter from the EEG that is statistically optimally correlated with the apparent concentration of the benzodiazepine in the effect site. This method has been used to develop new univariate measures of the effects of opioids on the EEG but has not previously been applied to the EEG effects of benzodiazepines., Methods: Data from ten subjects who received an infusion of midazolam were analyzed. The data were divided into "learning" and "test" sets. The learning set consisted of ten studies in which the volunteers received an infusion of 2.5 mg.min(-1) midazolam. Semilinear canonical correlation was used to extract an univariate descriptor of the EEG effect by weighting the different frequency bands of the EEG power spectrum. The test set comprised the same subjects on subsequent visits, in which the subjects received a continuous infusion of midazolam to maintain 20% or 80% of the peak drug effect for 3h. Twenty minutes after start of the midazolam infusion, the patient received an infusion of flumazenil to acutely reverse the benzodiazepine drug effect. The weights obtained from the learning set were tested prospectively in the test set, based on the coefficient of multiple determination, R(2), obtained by fitting the EEG effect to a sigmoid Emax model., Results: The canonical univariate parameter of benzodiazepine drug effect on the EEG, when applied to the test set receiving the midazolam infusion with flumazenil reversal, yielded a median R(2) of 0.78. The median R(2) of six commonly used empirical EEG measures of drug effect ranged from 0.18 to 0.55., Conclusions: The canonical univariate parameter for benzodiazepine drug effect on the EEG correlates more accurately and consistently with the predicted EEG effects of midazolam and its reversal than previously reported EEG measures of benzodiazepine effect.