Propofol infusions using a human target controlled infusion (TCI) pump in chimpanzees (Pan troglodytes).

Chimpanzees are genetically and physiologically similar to humans. Several pharmacokinetic models of propofol are available and target controlled infusion (TCI) of propofol is established in humans, but not in chimpanzees. The purpose of this study was to investigate if human pharmacokinetic models can accurately predict propofol plasma concentration (Cp) in chimpanzees and if it is feasible to perform TCI in chimpanzees. Ten chimpanzees were anaesthetized for regular veterinary examinations. Propofol was used as an induction or maintenance agent. Blood samples were collected from a catheter in a cephalic vein at 3-7 time points between 1 and 100 min following the propofol bolus and/or infusion in five chimpanzees, or TCI in six chimpanzees. Cp was measured using high-performance liquid chromatography. The Marsh, Schnider and Eleveld human pharmacokinetic models were used to predict Cp for each case and we examined the predictive performances of these models using the Varvel criteria Median PE and Median APE. Median PE and Median APE for Marsh, Schnider and Eleveld models were within or close to the acceptable range. A human TCI pump was successfully maintained propofol Cp during general anesthesia in six chimpanzees. Human propofol pharmacokinetic models and TCI pumps can be applied in chimpanzees.

Pharmacokinetic-pharmacodynamic model for propofol for broad application in anaesthesia and sedation.

BACKGROUND: Pharmacokinetic (PK) and pharmacodynamic (PD) models are used in target-controlled-infusion (TCI) systems to determine the optimal drug administration to achieve a desired target concentration in a central or effect-site compartment. Our aim was to develop a PK-PD model for propofol that can predict the bispectral index (BIS) for a broad population, suitable for TCI applications. METHODS: Propofol PK data were obtained from 30 previously published studies, five of which also contained BIS observations. A PK-PD model was developed using NONMEM. Weight, age, post-menstrual age (PMA), height, sex, BMI, and presence/absence of concomitant anaesthetic drugs were explored as covariates. The predictive performance was measured across young children, children, adults, elderly, and high-BMI individuals, and in simulated TCI applications. RESULTS: Overall, 15 433 propofol concentration and 28 639 BIS observations from 1033 individuals (672 males and 361 females) were analysed. The age range was from 27 weeks PMA to 88 yr, and the weight range was 0.68-160 kg. The final model uses age, PMA, weight, height, sex, and presence/absence of concomitant anaesthetic drugs as covariates. A 35-yr-old, 170 cm, 70 kg male (without concomitant anaesthetic drugs) has a V1, V2, V3, CL, Q2, Q3, and ke0 of 6.28, 25.5, 273 litres, 1.79, 1.75, 1.11 litres min-1, and 0.146 min-1, respectively. The propofol TCI administration using the model matches well with recommendations for all age groups considered for both anaesthesia and sedation. CONCLUSIONS: We developed a PK-PD model to predict the propofol concentrations and BIS for broad, diverse population. This should be useful for TCI in anaesthesia and sedation.

Influence of Bayesian optimization on the performance of propofol target-controlled infusion.

BACKGROUND: Target controlled infusion (TCI) systems use population-based pharmacokinetic (PK) models that do not take into account inter-individual residual variation. This study compares the bias and inaccuracy of a population-based vs a personalized TCI propofol titration using Bayesian adaptation. Haemodynamic and hypnotic stability, and the prediction probability of alternative PK models, was studied. METHODS: A double-blinded, prospective randomized controlled trial of 120 subjects undergoing cardiac surgery was conducted. Blood samples were obtained at 10, 35, 50, 65, 75 and 120 min and analysed using a point-of-care propofol blood analyser. Bayesian adaptation of the PK model was applied at 60 min in the intervention group. Median (Absolute) Performance Error (Md(A)PE) was used to evaluate the difference between bias and inaccuracy of the models. Haemodynamic (mean arterial pressure [MAP], heart rate) and hypnotic (bispectral index [BIS]) stability was studied. The predictive performance of four alternative propofol PK models was studied. RESULTS: MdPE and MdAPE did not differ between groups during the pre-adjustment period (control group: 6.3% and 16%; intervention group: 5.4% and 18%). MdPE differed in the post-adjustment period (12% vs. -0.3%), but MdAPE did not (18% vs. 15%). No difference in heart rate, MAP or BIS was found. Compared with the other models, the Eleveld propofol PK model (patients) showed the best prediction performance. CONCLUSIONS: When an accurate population-based PK model was used for propofol TCI, Bayesian adaption of the model improved bias but not precision. CLINICAL TRIAL REGISTRATION: Dutch Trial Registry NTR4518.

Dexmedetomidine pharmacokinetic-pharmacodynamic modelling in healthy volunteers: 1. Influence of arousal on bispectral index and sedation.

BACKGROUND: Dexmedetomidine, a selective α 2 -adrenoreceptor agonist, has unique characteristics, such as maintained respiratory drive and production of arousable sedation. We describe development of a pharmacokinetic-pharmacodynamic model of the sedative properties of dexmedetomidine, taking into account the effect of stimulation on its sedative properties. METHODS: In a two-period, randomized study in 18 healthy volunteers, dexmedetomidine was delivered in a step-up fashion by means of target-controlled infusion using the Dyck model. Volunteers were randomized to a session without background noise and a session with pre-recorded looped operating room background noise. Exploratory pharmacokinetic-pharmacodynamic modelling and covariate analysis were conducted in NONMEM using bispectral index (BIS) monitoring of processed EEG. RESULTS: We found that both stimulation at the time of Modified Observer's Assessment of Alertness/Sedation (MOAA/S) scale scoring and the presence or absence of ambient noise had an effect on the sedative properties of dexmedetomidine. The stimuli associated with MOAA/S scoring increased the BIS of sedated volunteers because of a transient 170% increase in the effect-site concentration necessary to reach half of the maximal effect. In contrast, volunteers deprived of ambient noise were more resistant to dexmedetomidine and required, on average, 32% higher effect-site concentrations for the same effect as subjects who were exposed to background operating room noise. CONCLUSIONS: The new pharmacokinetic-pharmacodynamic models might be used for effect-site rather than plasma concentration target-controlled infusion for dexmedetomidine in clinical practice, thereby allowing tighter control over the desired level of sedation. CLINICAL TRIAL REGISTRATION: NCT01879865.

Dexmedetomidine pharmacodynamics in healthy volunteers: 2. Haemodynamic profile.

BACKGROUND: Dexmedetomidine, a selective α 2 -adrenoreceptor agonist, has unique characteristics, with little respiratory depression and rousability during sedations. We characterized the haemodynamic properties of dexmedetomidine by developing a pharmacokinetic-pharmacodynamic (PKPD) model with a focus on changes in mean arterial blood pressure (MAP) and heart rate. METHODS: Dexmedetomidine was delivered i.v. to 18 healthy volunteers in a step-up fashion by target-controlled infusion using the Dyck model. Exploratory PKPD modelling and covariate analysis were conducted in NONMEM. RESULTS: Our model adequately describes dexmedetomidine-induced hypotension, hypertension, and bradycardia, with a greater effective concentration for the hypertensive effect. Changes in MAP were best described by a double-sigmoidal E max model with hysteresis. Covariate analysis revealed no significant covariates apart from age on the baseline MAP in the population pharmacokinetic model used to develop this PKPD model. Simulations revealed good general agreement with published descriptive studies of haemodynamics after dexmedetomedine infusion. CONCLUSIONS: The present integrated PKPD model should allow tighter control over the desired level of sedation, while limiting potential haemodynamic side-effects. CLINICAL TRIAL REGISTRATION: NCT01879865.

Pharmacokinetics and pharmacodynamics of propofol: changes in patients with frontal brain tumours.

BACKGROUND: Models of propofol pharmacokinetics and pharmacodynamics developed in patients without brain pathology are widely used for target-controlled infusion (TCI) during brain tumour excision operations. The goal of this study was to determine if the presence of a frontal brain tumour influences propofol pharmacokinetics and pharmacodynamics and existing PK-PD model performance. METHODS: Twenty patients with a frontal brain tumour and 20 control patients received a propofol infusion to achieve an induction-emergence-induction anaesthetic sequence. Propofol plasma concentration was measured every 4 min and at each transition of the conscious state. Bispectral index (BIS) values were continuously recorded. We used non-linear mixed-effects modelling to analyse the effects of the presence of a brain tumour on the pharmacokinetics and pharmacodynamics of propofol. Subsequently we calculated the predictive performance of Marsh, Schnider, and Eleveld models in terms of median prediction error (MdPE) and median absolute prediction error (MdAPE). RESULTS: Patients with brain tumours showed 40% higher propofol clearance than control patients. Performance of the Schnider model (MdPEpk -20.0%, MdAPEpk 23.4%) and Eleveld volunteer model (MdPEpk -8.58%, MdAPEpk 21.6%) were good. The Marsh model performed less well (MdPEpk -14.3%, MdAPEpk 41.4%), as did the Eleveld patient model (MdPEpk -30.8%, MdAPEpk 32.1%). CONCLUSIONS: Brain tumours might alter the pharmacokinetics of propofol. Caution should be exerted when using propofol TCI in patients with frontal brain tumours due to higher clearance. TRIAL REGISTRY NUMBER: NCT01060631.

Predictive performance of eleven pharmacokinetic models for propofol infusion in children for long-duration anaesthesia.

Background: Predictive performance of eleven published propofol pharmacokinetic models was evaluated for long-duration propofol infusion in children. Methods: Twenty-one aged three-11 yr ASA I-II patients were included. Anaesthesia was induced with propofol or sevoflurane, and maintained with propofol, remifentanil, and fentanyl. Propofol was continuously infused at rates of 4-14 mg kg - 1 h - 1 after an initial bolus of 1.5-2.0 mg kg - 1 . Venous blood samples were obtained every 30-60 min for five h and then every 60-120 min after five h from the start of propofol administration, and immediately after the end of propofol administration. Model performance was assessed with prediction error (PE) derivatives including divergence PE, median PE (MDPE), and median absolute PE (MDAPE) as time-related PE shift, measures for bias, and inaccuracy, respectively. Results: We collected 85 samples over 270 (130) (88-545), mean (SD) (range), min. The Short model for children, and the Schüttler general-purpose model had acceptable performance (-20%≤MDPE ≤ 20%, MDAPE ≤ 30%, -4% h - 1 ≤ divergence PE ≤ 4% h - 1 ). The Short model showed the best performance with the maximum predictive performance metric. Two models developed only using bolus dosing (Shangguan and Saint-Maurice models) and the Paedfusor of the remaining nine models had significant negative divergence PE (≤-6.1% h - 1 ). Conclusions: The Short model performed well during continuous infusion up to 545 min. This model might be preferable for target-controlled infusion for long-duration anaesthesia in children.

Pharmacokinetic and pharmacodynamic interactions in anaesthesia. A review of current knowledge and how it can be used to optimize anaesthetic drug administration.

This review describes the basics of pharmacokinetic and pharmacodynamic drug interactions and methodological points of particular interest when designing drug interaction studies. It also provides an overview of the available literature concerning interactions, with emphasis on graphic representation of interactions using isoboles and response surface models. It gives examples on how to transform this knowledge into clinically and educationally applicable (bedside) tools.

Probability to tolerate laryngoscopy and noxious stimulation response index as general indicators of the anaesthetic potency of sevoflurane, propofol, and remifentanil.

BACKGROUND: The probability to tolerate laryngoscopy (PTOL) and its derivative, the noxious stimulation response index (NSRI), have been proposed as measures of potency of a propofol-remifentanil drug combination. This study aims at developing a triple drug interaction model to estimate the combined potency of sevoflurane, propofol, and remifentanil in terms of PTOL. We compare the predictive performance of PTOL and the NSRI with various anaesthetic depth monitors. METHODS: Data from three previous studies (n=120) were pooled and reanalysed. Movement response after laryngoscopy was observed with different combinations of propofol-remifentanil, sevoflurane-propofol, and sevoflurane-remifentanil. A triple interaction model to estimate PTOL was developed. The NSRI was derived from PTOL. The ability of PTOL and the NSRI to predict observed tolerance of laryngoscopy (TOL) was compared with the following other measures: (i) effect-site concentrations of sevoflurane, propofol, and remifentanil (CeSEVO, CePROP, and CeREMI); (ii) bispectral index; (iii) two measures of spectral entropy; (iv) composite variability index; and (v) surgical pleth index. RESULTS: Sevoflurane and propofol interact additively, whereas remifentanil interacts in a strongly synergistic manner. The effect-site concentrations of sevoflurane and propofol at a PTOL of 50% (Ce50; se) were 2.59 (0.13) vol % and 7.58 (0.49) µg ml(-1). A CeREMI of 1.36 (0.15) ng ml(-1) reduced the Ce50 of sevoflurane and propofol by 50%. The common slope factor was 5.22 (0.52). The PTOL and NSRI predict the movement response to laryngoscopy best. CONCLUSIONS: The triple interaction model estimates the potency of any combination of sevoflurane, propofol, and remifentanil expressed as either PTOL or NSRI.

Model to describe the degree of twitch potentiation during neuromuscular monitoring.

BACKGROUND: Neuromuscular block is estimated by comparing the evoked peak twitch with a control value measured in the absence of neuromuscular block. In practice, this control value is often difficult to determine because repeated motor nerve stimulation enhances the evoked mechanical response of the corresponding muscle, resulting in an increased twitch response. This is known as twitch potentiation or the staircase phenomenon. It is probably the result of myosin light chain phosphorylation creating an increased twitch force for a given amount of Ca(2+) released at each action potential. Modelling of potentiation may improve studies of neuromuscular blocking agents using mechanomyography or accelerometry. METHODS: We used one- and two-exponential models to describe the degree of myosin light chain phosphorylation and associated twitch potentiation. These models were fitted to accelerographic twitch force measurements for various stimulation patterns and frequencies used in neuromuscular monitoring. RESULTS: Fitting a two-exponential model to twitch data for various stimulation rates and patterns provides better prediction than a one-exponential model. A one-exponential model performs poorly when the stimulation rate varies during measurement. CONCLUSIONS: We conclude that a two-exponential model can predict the degree of twitch potentiation for the stimulation patterns and frequencies tested more accurately than a one-exponential model. However, if only one stimulation frequency is used, a one-exponential model can provide good accuracy. We illustrate that such a potentiation model can improve the ability of pharmacodynamic-pharmacokinetic neuromuscular block models to predict twitch response in the presence of a neuromuscular blocking agent.

The relationship between rate of administration of an intubating dose of rocuronium and time to 50% and 90% block at the adductor pollicis muscle.

OBJECTIVE: To determine the relationship between the rate of rocuronium injection and the onset time of neuromuscular block. METHODS: After intravenous induction, 60 female patients (ASA I-II) were assigned randomly into 3 groups for rocuronium administration within 1-15, 15-30 or 30-60 seconds. Acceleromyography of the thumb was performed using train-of-four (TOF) stimulation. Times to 50% and 90% twitch depression of the first twitch of the TOF stimulation (T1) were recorded. RESULTS: Injection time significantly influences time to 50% relaxation, but not time to 90% relaxation. Body mass index is negatively correlated with time to 50% and 90% relaxation. CONCLUSIONS: We conclude that rate of injection influences only the initial phase of development of the block and that slower injection times do not significantly affect time to 90% relaxation at the adductor pollicis muscle.