A two-compartment effect site model describes the bispectral index after different rates of propofol infusion

A Deep Learning Framework for Anesthesia Depth Prediction from Drug Infusion History

In the target-controlled infusion (TCI) of propofol and remifentanil intravenous anesthesia, accurate prediction of the depth of anesthesia (DOA) is very challenging. Patients with different physiological characteristics have inconsistent pharmacodynamic responses during different stages of anesthesia. For example, in TCI, older adults transition smoothly from the induction period to the maintenance period, while younger adults are more prone to anesthetic awareness, resulting in different DOA data distributions among patients. To address these problems, a deep learning framework that incorporates domain adaptation and knowledge distillation and uses propofol and remifentanil doses at historical moments to continuously predict the bispectral index (BIS) is proposed in this paper. Specifically, a modified adaptive recurrent neural network (AdaRNN) is adopted to address data distribution differences among patients. Moreover, a knowledge distillation pipeline is developed to train the prediction network by enabling it to learn intermediate feature representations of the teacher network. The experimental results show that our method exhibits better performance than existing approaches during all anesthetic phases in the TCI of propofol and remifentanil intravenous anesthesia. In particular, our method outperforms some state-of-the-art methods in terms of root mean square error and mean absolute error by 1 and 0.8, respectively, in the internal dataset as well as in the publicly available dataset.

The Drug Titration Paradox: Correlation of More Drug With Less Effect in Clinical Data

While analyzing clinical data where an anesthetic was titrated based on an objective measure of drug effect, we observed paradoxically that greater effect was associated with lesser dose. With this study we sought to find a mathematical explanation for this negative correlation between dose and effect, to confirm its existence with additional clinical data, and to explore it further with Monte Carlo simulations. Automatically recorded dosing and effect data from more than 9,000 patients was available for the analysis. The anesthetics propofol and sevoflurane and the catecholamine norepinephrine were titrated to defined effect targets, i.e., the processed electroencephalogram (Bispectral Index, BIS) and the blood pressure. A proportional control titration algorithm was developed for the simulations. We prove by deduction that the average dose–effect relationship during titration to the targeted effect will associate lower doses with greater effects. The finding of negative correlations between propofol and BIS, sevoflurane and BIS, and norepinephrine and mean arterial pressure confirmed the titration paradox. Monte Carlo simulations revealed two additional factors that contribute to the paradox. During stepwise titration toward a target effect, the slope of the dose–effect data for the population will be “reversed,” i.e., the correlation between dose and effect will not be positive, but will be negative, and will be “horizontal” when the titration is “perfect.” The titration paradox must be considered whenever data from clinical titration (flexible dose) studies are interpreted. Such data should not be used naively for the development of dosing guidelines.

The influence of cardiac output on propofol and fentanyl pharmacokinetics and pharmacodynamics in patients undergoing abdominal aortic surgery

Cardiac output (CO) is expected to affect elimination and distribution of highly extracted and perfusion rate-limited drugs. This work was undertaken to quantify the effect of CO measured by the pulse pressure method on pharmacokinetics and pharmacodynamics of propofol and fentanyl administrated during total intravenous anesthesia (TIVA). The data were obtained from 22 ASA III patients undergoing abdominal aortic surgery. Propofol was administered via target-controlled infusion system (Diprifusor) and fentanyl was administered at a dose of 2-3 µg/kg each time analgesia appeared to be inadequate. Hemodynamic measurements as well as bispectral index were monitored and recorded throughout the surgery. Data analysis was performed by using a non-linear mixed-effect population modeling (NONMEM 7.4 software). Three compartment models that incorporated blood flows as parameters were used to describe propofol and fentanyl pharmacokinetics. The delay of the anesthetic effect, with respect to plasma concentrations, was described using a biophase (effect) compartment. The bispectral index was linked to the propofol and fentanyl effect site concentrations through a synergistic Emax model. An empirical linear model was used to describe CO changes observed during the surgery. Cardiac output was identified as an important predictor of propofol and fentanyl pharmacokinetics. Consequently, it affected the depth of anesthesia and the recovery time after propofol-fentanyl TIVA infusion cessation. The model predicted (not observed) CO values correlated best with measured responses. Patients' age was identified as a covariate affecting the rate of CO changes during the anesthesia leading to age-related difference in individual patient's responses to both drugs.

Population pharmacokinetic-pharmacodynamic model of propofol in adolescents undergoing scoliosis surgery with intraoperative wake-up test: a study using Bispectral index and composite auditory evoked potentials as pharmacodynamic endpoints

BACKGROUND

In adolescents limited data are available on the pharmacokinetics (PK) and pharmacodynamics (PD) of propofol. In this study we derived a PK-PD model for propofol in adolescents undergoing idiopathic scoliosis surgery with an intraoperative wake-up test with reinduction of anesthesia using both Bispectral Index (BIS) and composite A-line ARX index (cAAI) as endpoints.

METHODS

Fourteen adolescents (9.8-20.1 years) were evaluated during standardized propofol-remifentanil anesthesia for idiopathic scoliosis surgery with an intraoperative wake-up test with reinduction of anesthesia. BIS and cAAI were continuously measured and blood samples collected. A propofol PKPD model was developed using NONMEM.

RESULTS

The time courses of propofol concentrations, BIS and cAAI values during anesthesia, intra-operative wakeup and reduction of anesthesia were best described by a two-compartment PK model linked to an inhibitory sigmoidal Emax PD model. For the sigmoidal Emax model, the propofol concentration at half maximum effect (EC₅₀) was 3.51 and 2.14 mg/L and Hill coefficient 1.43 and 6.85 for BIS and cAAI, respectively. The delay in PD effect in relation to plasma concentration was best described by a two compartment effect-site model with a ke_o of 0.102 min^- 1, ke₁₂ of 0.121 min^- 1 and ke₂₁ of 0.172 min^- 1.

CONCLUSIONS

A population PKPD model for propofol in adolescents was developed that successfully described the time course of propofol concentration, BIS and cAAI in individuals upon undergoing scoliosis surgery with intraoperative wake-up test and reinduction of anesthesia. Large differences were demonstrated between both monitors. This may imply that BIS and cAAI measure fundamentally different endpoints in the brain.

Pharmacokinetics and pharmacodynamics of dexmedetomidine-induced vasoconstriction in healthy volunteers

AIMS

Alpha-2 agonists are direct peripheral vasoconstrictors, which achieve these effects by activating vascular smooth muscle alpha-2 adrenoceptors. The impact of this response during dexmedetomidine infusion remains poorly quantified. Our goal was to investigate the pharmacokinetic (PK) and pharmacodynamic (PD, vasoconstriction) effects of a computer-controlled dexmedetomidine infusion in healthy volunteers.

METHODS

After local ethics committee approval, we studied 10 healthy volunteers. To study the peripheral vasoconstrictive effect of dexmedetomidine without concurrent sympatholytic effects, sympathetic fibres were blocked with a brachial plexus block. Volunteers received a dexmedetomidine target-controlled infusion for 15 min, to a target concentration of 0.3 ng ml-1 . Arterial blood samples were collected during and for 60 min after dexmedetomidine infusion for PK analysis. Peripheral vasoconstriction (PD) was assessed using finger photoelectric plethysmography. PK/PD analysis was carried out using nonlinear mixed-effect models.

RESULTS

We found that the computer-controlled infusion pump delivered mean concentrations greater than 0.3 ng ml-1 over the 15-min infusion duration. The peripheral vasoconstrictive effect correlated with dexmedetomidine plasma concentrations during and after the infusion. A three-compartment model provided a better fit to the data than a two-compartment model.

CONCLUSIONS

We found that dexmedetomidine-induced vasoconstriction is concentration dependent over time. Dexmedetomidine PK were best estimated by a three-compartment model with allometric scaling. Our results may contribute to future modelling of dexmedetomidine-induced haemodynamic effects.

Pharmacokinetic/Pharmacodynamic Model of CW002, an Investigational Intermediate Neuromuscular Blocking Agent, in Healthy Volunteers

BACKGROUND

CW002 is an investigational nondepolarizing, neuromuscular blocking agent with a rapid onset and intermediate duration of action in animals. This is a single ascending dose, healthy subject study exploring tolerability, pharmacokinetics, and potency.

METHODS

Population pharmacokinetic and pharmacokinetic/pharmacodynamic models were developed using plasma drug concentration data from a previously published dose-response study in 28 healthy subjects receiving single doses of CW002 during sevoflurane anesthesia. Subjects included in the models were from five different dose cohorts (cohorts 3, 4, 5, 6, and 8 receiving 0.04, 0.06, 0.08, 0.10, and 0.14 mg/kg, respectively). Serial arterial plasma concentrations and muscle twitch heights were monitored.

RESULTS

A four-compartment model was fit to the concentration-time data, whereas a transit compartment with a sigmoid Emax model was fit to the pharmacokinetic/pharmacodynamic data. The population pharmacokinetics of CW002 was linear with very low interindividual variability in clearance (10.8%). Simulations were conducted to predict the onset and offset of effect at 2×, 3×, and 4× ED95. The time to 80% block was predicted to be 1.5, 0.8, and 0.7 min for 2×, 3×, and 4× ED95 doses, respectively. The simulated 25 to 75% recovery index was independent of dose.

CONCLUSIONS

CW002 has predictable pharmacokinetics and is likely to have a rapid onset with an intermediate duration of action at 3× ED95. This model provides information to inform critical decisions (e.g., dose, study design) for continued development of CW002.

Prediction of Bispectral Index during Target-controlled Infusion of Propofol and Remifentanil

Background

The discrepancy between predicted effect-site concentration and measured bispectral index is problematic during intravenous anesthesia with target-controlled infusion of propofol and remifentanil. We hypothesized that bispectral index during total intravenous anesthesia would be more accurately predicted by a deep learning approach.

Methods

Long short-term memory and the feed-forward neural network were sequenced to simulate the pharmacokinetic and pharmacodynamic parts of an empirical model, respectively, to predict intraoperative bispectral index during combined use of propofol and remifentanil. Inputs of long short-term memory were infusion histories of propofol and remifentanil, which were retrieved from target-controlled infusion pumps for 1,800 s at 10-s intervals. Inputs of the feed-forward network were the outputs of long short-term memory and demographic data such as age, sex, weight, and height. The final output of the feed-forward network was the bispectral index. The performance of bispectral index prediction was compared between the deep learning model and previously reported response surface model.

Results

The model hyperparameters comprised 8 memory cells in the long short-term memory layer and 16 nodes in the hidden layer of the feed-forward network. The model training and testing were performed with separate data sets of 131 and 100 cases. The concordance correlation coefficient (95% CI) were 0.561 (0.560 to 0.562) in the deep learning model, which was significantly larger than that in the response surface model (0.265 [0.263 to 0.266], P < 0.001).

Conclusions

The deep learning model–predicted bispectral index during target-controlled infusion of propofol and remifentanil more accurately compared to the traditional model. The deep learning approach in anesthetic pharmacology seems promising because of its excellent performance and extensibility.

Propofol Breath Monitoring as a Potential Tool to Improve the Prediction of Intraoperative Plasma Concentrations

INTRODUCTION

Monitoring of drug concentrations in breathing gas is routinely being used to individualize drug dosing for the inhalation anesthetics. For intravenous anesthetics however, no decisive evidence in favor of breath concentration monitoring has been presented up until now. At the same time, questions remain with respect to the performance of currently used plasma pharmacokinetic models implemented in target-controlled infusion systems. In this study, we investigate whether breath monitoring of propofol could improve the predictive performance of currently applied, target-controlled infusion models.

METHODS

Based on data from a healthy volunteer study, we developed an addition to the current state-of-the-art pharmacokinetic model for propofol, to accommodate breath concentration measurements. The potential of using this pharmacokinetic (PK) model in a Bayesian forecasting setting was studied using a simulation study. Finally, by introducing bispectral index monitor (BIS) measurements and the accompanying BIS models into our PK model, we investigated the relationship between BIS and predicted breath concentrations.

RESULTS AND DISCUSSION

We show that the current state-of-the-art pharmacokinetic model is easily extended to reliably describe propofol kinetics in exhaled breath. Furthermore, we show that the predictive performance of the a priori model is improved by Bayesian adaptation based on the measured breath concentrations, thereby allowing further treatment individualization and a more stringent control on the targeted plasma concentrations during general anesthesia. Finally, we demonstrated concordance between currently advocated BIS models, relying on predicted effect-site concentrations, and our new approach in which BIS measurements are derived from predicted breath concentrations.

Adaptive pharmacokinetic and pharmacodynamic modelling to predict propofol effect using BIS-guided anesthesia

BACKGROUND AND OBJECTIVE

Propofol is widely used for hypnosis induction and maintenance of general anesthesia. Its effect can be assessed using the bispectral index (BIS). Many automatic infusion systems are based in pharmacokinetics (PK) and pharmacodynamics (PD) models to predict the response of the patient to the drug. However, all these models do not take into account intra and inter-patient variability. An adjusted intraoperative drug administration allows faster recovery and provides post-operative side-effect mitigation

METHODS

BIS evolution and surgery-recorded propofol infusion data of a group of 60 adult patients (30 males/30 females) with ASA I/II physical status were used to test a real time PK/PD compartmental model. This new algorithm tunes three model parameters (ce50, γ and ke0), minimizing a performance function online.

RESULTS

The error in the BIS signal predicted by the real time PK/PD model was smaller than the error measured with fixed parameter equations. This model shows that ce50, γ and ke0 change with time and patients, given a mean (95% confidence interval) of 3.89 (3.52-4.26)mg/l, 4.63 (4.13-5.13) and 0.36 (0.31-0.4)min(-1), respectively.

CONCLUSIONS

The real time PK/PD model proposed provides a closer description of the patient real state at each sample time. This allows for greater control of the drug infusion, and thus the quantity of drug administered can be titrated to achieve the desired effect for the desired duration, and reduce unnecessary waste or post-operative effects.

Evidence of Different Propofol Pharmacokinetics under Short and Prolonged Infusion Times in Rabbits

Propofol is an anaesthetic widely used in both human beings and animals. However, the characterization of propofol pharmacokinetics (PK) is not well understood when long-term infusions are used. The main objective of this study was to explore the PK behaviour of propofol in a rabbit model during short and prolonged propofol infusions and to develop an internally validated PK model, for propofol dose individualization in the rabbit for future use. Population 1 (P1) was constituted by seven New Zealand rabbits and was used to characterize the PK profile of propofol at short infusions. Animals were anaesthetized with a bolus of 20 mg/kg, followed by an infusion rate of 50 mg/kg/hr of propofol at 1%, which was then maintained for 30 min. A second rabbit population (P2, n = 7) was sedated according to reflexes responses and Index of Consciousness values, for 20 consecutive hours using propofol 2% aiming at characterizing propofol behaviour at long-term infusions. Clinical data and blood samples were collected at specific time-points in both populations. Propofol plasma concentrations were determined by gas chromatography/ion trap mass spectrometry. The NONMEM VII software was used to evaluate the relationships between dose and plasma concentrations. A linear two-compartment model with different central compartment volume and plasma clearance (separately modelled in the two populations) was the one that best described propofol concentrations. The time course of propofol plasma concentrations was well characterized by the PK model developed, which simultaneously accounts for propofol short- and long-term infusions and can be used to optimize future PK studies in rabbits.

Pharmacokinetic-pharmacodynamic modelling in anaesthesia

Anaesthesiologists adjust drug dosing, administration system and kind of drug to the characteristics of the patient. They then observe the expected response and adjust dosing to the specific requirements according to the difference between observed response, expected response and the context of the surgery and the patient. The approach above can be achieved because on one hand quantification technology has made significant advances allowing the anaesthesiologist to measure almost any effect by using noninvasive, continuous measuring systems. On the other the knowledge on the relations between dosing, concentration, biophase dynamics and effect as well as detection of variability sources has been achieved as being the benchmark specialty for pharmacokinetic-pharmacodynamic (PKPD) modelling. The aim of the review is to revisit the most common PKPD models applied in the field of anaesthesia (i.e. effect compartmental, turnover, drug-receptor binding and drug interaction models) through representative examples. The effect compartmental model has been widely used in this field and there are multiple applications and examples. The use of turnover models has been limited mainly to describe respiratory effects. Similarly, cases in which the dissociation process of the drug-receptor complex is slow compared with other processes relevant to the time course of the anaesthetic effect are not frequent in anaesthesia, where in addition to a rapid onset, a fast offset of the response is required. With respect to the characterization of PD drug interactions different response surface models are discussed. Relevant applications that have changed the way modern anaesthesia is practiced are also provided.

Population pharmacokinetic-pharmacodynamic modeling and dosing simulation of propofol maintenance anesthesia in severely obese adolescents

BACKGROUND

Optimal dosing of propofol to maintain appropriate anesthetic depth is challenging in severely obese (SO) adolescents. We previously reported that total body weight (TBW) is predictive of propofol clearance. This study was aimed at characterizing pharmacokinetics (PK) and pharmacodynamics (PD) of propofol in SO adolescents, using bispectral index (BIS), and toward developing PK/PD model-based dosing guidelines.

METHODS

A prospective PK/PD study was conducted in 26 SO children and adolescents aged 9-18 years (body mass index 31-69 kg·m(-2)), undergoing surgery with intravenous propofol anesthesia clinically titrated by providers blinded to BIS. BIS data and propofol infusion schemes were recorded. Venous blood samples collected during and after propofol infusion were assayed for propofol concentrations. A propofol PK/PD model was developed using NONMEM and model-based simulations were performed to determine propofol dosing regimens targeting BIS of 50 ± 10.

RESULTS

A three-compartment PK model linked to a sigmoidal inhibitory Emax PD model by a first-order rate constant, adequately described the propofol concentration (n = 375) and BIS (n = 3334) data. TBW was the most predictive covariate for propofol clearance [CL (l·min(-1) ) = 1.65 × (TBW/70)(0.75)]. An effect-site propofol concentration of 3.19 μg·ml(-1) was estimated for half-maximal effect, with no identifiable predictive covariates. The proposed maintenance dosing regimen targeted to a BIS of 50 ± 10, based on our PK/PD model, was able to predict desired propofol concentrations and BIS in a representative obese teen when used in conjunction with accepted PK/PD models for children/obese adults (PK:Eleveld/PD: Cortinez), further supporting evidence for the dosing based on TBW.

CONCLUSION

This is the first study to describe the PK/PD of propofol in SO adolescents. The proposed maintenance dosing regimen for propofol uses TBW in an allometric function as a dosing scalar, with an exponent of 0.75. Our results suggest no relevant effect of obesity on the propofol concentration-BIS relationship.

Propofol: a review of its role in pediatric anesthesia and sedation

Propofol is an intravenous agent used commonly for the induction and maintenance of anesthesia, procedural, and critical care sedation in children. The mechanisms of action on the central nervous system involve interactions at various neurotransmitter receptors, especially the gamma-aminobutyric acid A receptor. Approved for use in the USA by the Food and Drug Administration in 1989, its use for induction of anesthesia in children less than 3 years of age still remains off-label. Despite its wide use in pediatric anesthesia, there is conflicting literature about its safety and serious adverse effects in particular subsets of children. Particularly as children are not "little adults", in this review, we emphasize the maturational aspects of propofol pharmacokinetics. Despite the myriad of propofol pharmacokinetic-pharmacodynamic studies and the ability to use allometrical scaling to smooth out differences due to size and age, there is no optimal model that can be used in target controlled infusion pumps for providing closed loop total intravenous anesthesia in children. As the commercial formulation of propofol is a nutrient-rich emulsion, the risk for bacterial contamination exists despite the Food and Drug Administration mandating addition of antimicrobial preservative, calling for manufacturers' directions to discard open vials after 6 h. While propofol has advantages over inhalation anesthesia such as less postoperative nausea and emergence delirium in children, pain on injection remains a problem even with newer formulations. Propofol is known to depress mitochondrial function by its action as an uncoupling agent in oxidative phosphorylation. This has implications for children with mitochondrial diseases and the occurrence of propofol-related infusion syndrome, a rare but seriously life-threatening complication of propofol. At the time of this review, there is no direct evidence in humans for propofol-induced neurotoxicity to the infant brain; however, current concerns of neuroapoptosis in developing brains induced by propofol persist and continue to be a focus of research.

Pharmacokinetics and pharmacodynamics of propofol in cancer patients undergoing major lung surgery

Despite the growing number of cancer cases and cancer surgeries around the world, the pharmacokinetics (PK) and pharmacodynamics (PD) of anesthetics used in this population are poorly understood. Patients operated due to cancer are usually in severe state and often require chemotherapy. It might affect the PK/PD of drugs used in this population. Therefore, in this study we explored the PK/PD of propofol in cancer patients having a major lung surgery. 23 patients that underwent a propofol-fentanyl total intravenous anesthesia were included in the analysis. A large set of demographic, biochemical and hemodynamic parameters was collected for the purpose of covariate analysis. Nonlinear mixed effect modeling in NONMEM was used to analyze the collected data. A three-compartment model was sufficient to describe PK of propofol. The anesthetic effect (AAI index) was linked to the propofol effect site concentrations through a sigmoidal E max model. A slightly higher value of clearance, a lower value of distribution clearance, and a decreased volume of peripheral compartment were observed in our patients, as compared with the literature values reported for healthy volunteers by Schnider et al. and by Eleveld et al. Despite these differences, both models led to a clinically insignificant bias of -8 and -1 % in concentration predictions, as reflected by the median performance error. The C e50 and propofol biophase concentration at the time of postoperative orientation were low and equaled 1.40 and 1.13 mg/L. The population PK/PD model was proposed for cancer patients undergoing a major lung surgery. The large body of studied covariates did not affect PK/PD of propofol significantly. The modification of propofol dosage in the group of patients under study is not necessary when TCI-guided administration of propofol by means of the Schnider model is used.

Insights from neuroenergetics into the interpretation of functional neuroimaging: an alternative empirical model for studying the brain's support of behavior

Functional neuroimaging measures quantitative changes in neurophysiological parameters coupled to neuronal activity during observable behavior. These results have usually been interpreted by assuming that mental causation of behavior arises from the simultaneous actions of distinct psychological mechanisms or modules. However, reproducible localization of these modules in the brain using functional magnetic resonance imaging (MRI) and positron emission tomography (PET) imaging has been elusive other than for sensory systems. In this paper, we show that neuroenergetic studies using PET, calibrated functional magnetic resonance imaging (fMRI), (13)C magnetic resonance spectroscopy, and electrical recordings do not support the standard approach, which identifies the location of mental modules from changes in brain activity. Of importance in reaching this conclusion is that changes in neuronal activities underlying the fMRI signal are many times smaller than the high ubiquitous, baseline neuronal activity, or energy in resting, awake humans. Furthermore, the incremental signal depends on the baseline activity contradicting theoretical assumptions about linearity and insertion of mental modules. To avoid these problems, while making use of these valuable results, we propose that neuroimaging should be used to identify observable brain activities that are necessary for a person's observable behavior rather than being used to seek hypothesized mental processes.

Evaluation of the aepEX™ monitor of hypnotic depth in pediatric patients receiving propofol-remifentanil anesthesia

BACKGROUND

The aepEX Plus monitor (aepEX) utilizes a mid-latency auditory evoked potential-derived index of depth of hypnosis (DoH).

OBJECTIVE

This observational study evaluates the performance of the aepEX as a DoH monitor for pediatric patients receiving propofol-remifentanil anesthesia.

METHODS

aepEX and BIS values were recorded simultaneously during surgery in three groups of 25 children (aged 1-3, 3-6 and 6-16 years). Propofol was administered by target-controlled infusion. The University of Michigan Sedation Scale (UMSS) was used to clinically assess the DoH during emergence. Prediction probability (P(k)) and receiver operating characteristics (ROC) analyses were performed to assess the accuracy of both DoH monitors. Nonlinear regression analysis was used to describe the dose-response relationships for the aepEX, the BIS, and propofol plasma concentrations (Cp).

RESULTS

The P(k) for the aepEX and BIS was 0.36 and 0.21, respectively (P = 0.010). ROC analysis showed an area under the curve of 0.77 and 0.88 for the aepEX and BIS, respectively (P = 0.644). At half-maximal effect (EC(50)), C(p) of 3.13 μg·ml(-1) and 3.06 μg·ml(-1) were observed for the aepEX and BIS, respectively. The r(2) for the aepEX and BIS was 0.53 and 0.82, respectively.

CONCLUSION

The aepEX performs comparable to the BIS in differentiating between consciousness and unconsciousness, while performing inferior to the BIS in terms of distinguishing different levels of sedation and does not correlate well with the C(p) in children receiving propofol-remifentanil anesthesia.

Modeling the Influence of the A118G Polymorphism in the OPRM1 Gene and of Noxious Stimulation on the Synergistic Relation between Propofol and Remifentanil

Background:

The presence of the A118G single nucleotide polymorphism in the OPRM1 gene as well as noxious stimulation might affect the requirements of remifentanil for patients undergoing ultrasonographic endoscopy under sedation-analgesia with propofol and remifentanil. Bispectral index (BIS) was used as a surrogate measure of effect.

Methods:

A total of 207 patients were screened for A118G and randomly received different combinations of propofol and remifentanil, changed depending on the nausea response to endoscopy tube introduction. Nonlinear mixed effects modelling was used to establish the relation between propofol and remifentanil with respect to BIS and to investigate the influence of A118G or noxious stimulation. The value of ke0 for propofol and remifentanil was estimated to avoid the hysteresis between predicted effect site concentration (Ce) and BIS.

Results:

Data from 176 patients were analysed. Eleven were recessive homozygous for A118G (OPRM = 1). A total of 165 patients were either dominant homozygous or heterozygous and considered normal (OPRM = 0). The estimated values of ke0 for propofol and remifentanil were 0.122 and 0.148min−1. Propofol and remifentanil were synergistic with respect to the BIS (α = 1.85). EC50 estimate for propofol was 3.86 µg/ml and for remifentanil 19.6 ng/ml in normal patients and 326ng/ml in OPRM = 1 patients. BIS increases around 4% for the same effect site concentrations with noxious stimulation.

Conclusions:

Predicted effect site concentration of remifentanil ranging 1–5ng/ml synergistically potentiates the effects of propofol on the BIS but has no effect in A118G patients. Noxious stimulation increases BIS values by 4% at the same concentrations of propofol and remifentanil.

Bispectral index dynamics during propofol hypnosis is similar in red-haired and dark-haired subjects

BACKGROUND

We have previously shown that red hair is associated with increased desflurane requirement for immobility, compared with dark hair. The effect of red hair on IV anesthetic requirement remains unknown. We tested the hypothesis that the propofol concentration in the effect site associated with half maximal electroencephalogram response, Ce50, is at least 50% higher in subjects with red hair.

METHODS

We modeled the propofol concentration versus electroencephalogram response relationship using a 2-step approach in 29 healthy dark- and red-haired volunteers receiving a propofol infusion to produce loss of consciousness. Bispectral Index (BIS) was the measure of drug effect. The parameters of a 3-compartment pharmacokinetic model were fit to measured arterial propofol concentrations. The relationship between effect-site propofol concentration (Ce) and BIS was characterized using a sigmoid Emax model. Model performance and accuracy of the estimated parameters were evaluated using accepted metrics and bootstrap resampling. The effect of hair color on the Ce50 for BIS response in the final model was assessed using a threshold of 6.63 (P<0.01) in reduction of -2 log likelihood. The influence of body weight on the model was also assessed.

RESULTS

The inclusion of hair color as a model covariate did not improve either the pharmacokinetic or the pharmacodynamic model. A separate analysis for the dark- and red-haired subjects estimated a median (95% confidence interval) Ce50 BIS of 2.71 μg/mL (2.28-3.36 μg/mL) and 2.57 μg/mL (1.68-3.60 μg/mL), respectively. Body weight was a significant covariate for the CL1 and V1.

CONCLUSIONS

Red hair phenotype does not affect the pharmacokinetics or pharmacodynamics of propofol.

Pharmacokinetics and pharmacodynamics of propofol in patients undergoing abdominal aortic surgery

Available propofol pharmacokinetic protocols for target-controlled infusion (TCI) were obtained from healthy individuals. However, the disposition as well as the response to a given drug may be altered in clinical conditions. The aim of the study was to examine population pharmacokinetics (PK) and pharmacodynamics (PD) of propofol during total intravenous anesthesia (propofol/fentanyl) monitored by bispectral index (BIS) in patients scheduled for abdominal aortic surgery. Population nonlinear mixed-effect modeling was done with Nonmem. Data were obtained from ten male patients. The TCI system (Diprifusor) was used to administer propofol. The BIS index served to monitor the depth of anesthesia. The propofol dosing was adjusted to keep BIS level between 40 and 60. A two-compartment model was used to describe propofol PK. The typical values of the central and peripheral volume of distribution, and the metabolic and inter-compartmental clearance were V(C) = 24.7 l, V(T) = 112 l, Cl = 2.64 l/min and Q = 0.989 l/min. Delay of the anesthetic effect, with respect to plasma concentrations, was described by the effect compartment with the rate constant for the distribution to the effector compartment equal to 0.240 min(-1). The BIS index was linked to the effect site concentrations through a sigmoidal E(max) model with EC(50) = 2.19 mg/l. The body weight, age, blood pressure and gender were not identified as statistically significant covariates for all PK/PD parameters. The population PK/PD model was successfully developed to describe the time course and variability of propofol concentration and BIS index in patients undergoing surgery.

Population pharmacokinetics and pharmacodynamics of propofol in morbidly obese patients

BACKGROUND AND OBJECTIVES

In view of the increasing prevalence of morbidly obese patients, the influence of excessive total bodyweight (TBW) on the pharmacokinetics and pharmacodynamics of propofol was characterized in this study using bispectral index (BIS) values as a pharmacodynamic endpoint.

METHODS

A population pharmacokinetic and pharmacodynamic model was developed with the nonlinear mixed-effects modelling software NONMEM VI, on the basis of 491 blood samples from 20 morbidly obese patients (TBW range 98-167 kg) and 725 blood samples from 44 lean patients (TBW range 55-98 kg) from previously published studies. In addition, 2246 BIS values from the 20 morbidly obese patients were available for pharmacodynamic analysis.

RESULTS

In a three-compartment pharmacokinetic model, TBW proved to be the most predictive covariate for clearance from the central compartment (CL) in the 20 morbidly obese patients (CL 2.33 L/min × [TBW/70]^[0.72]). Similar results were obtained when the morbidly obese patients and the 44 lean patients were analysed together (CL 2.22 L/min × [TBW/70]^[0.67]). No covariates were identified for other pharmacokinetic parameters. The depth of anaesthesia in the morbidly obese patients was adequately described by a two-compartment biophase-distribution model with a sigmoid maximum possible effect (E(max)) pharmacodynamic model (concentration at half-maximum effect [EC(50)] 2.12 mg/L) without covariates.

CONCLUSION

We developed a pharmacokinetic and pharmacodynamic model of propofol in morbidly obese patients, in which TBW proved to be the major determinant of clearance, using an allometric function with an exponent of 0.72. For the other pharmacokinetic and pharmacodynamic parameters, no covariates could be identified. Trial registration number (clinicaltrials.gov): NCT00395681.

Mechanism-based pharmacokinetic-pharmacodynamic modeling of the estrogen-like effect of ginsenoside Rb1 on neural 5-HT in ovariectomized mice

We sought to develop a mechanism-based pharmacokinetic-pharmacodynamic (PK-PD) model to characterize the effects of ginsenoside Rb1 (Rb1) and estradiol (E(2)) on neural 5-hydroxytryptamine (5-HT) concentration in ovariectomized mice. PK data of Rb1 and E(2) were obtained in plasma and brain. Brain levels of 5-HT, tryptophan (TRP), 5-hydroxytryptophan (5-HTP), and 5-hydroxyindoleacetic acid (5-HIAA) were determined after a single intravenous injection of Rb1 (20mg/kg) and E(2) (0.2mg/kg) in ovariectomized mice. The activities of tryptophan hydroxylase (TPH), aromatic amino acid decarboxylase (AAAD), and monoamine oxidase (MAO) were also evaluated. Rb1 and E(2) elevated neural 5-HT levels via TPH activation and MAO inhibition, respectively. Effects were well described by the mechanism-based PK-PD model. The net effect of increased 5-HT induced by MAO inhibition is greater than TPH activation. The increased brain levels of 5-HT induced by Rb1 and E(2) were well described by the present PK-PD model, suggesting the use and further development of this mechanism-based model for the effects of ginsenoside on brain 5-HT levels.