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

The effect of cardiac output on the pharmacokinetics and pharmacodynamics of propofol during closed-loop induction of anesthesia

BACKGROUND AND OBJECTIVE

Intraoperative hemodynamic stability is essential to safety and post-operative well-being of patients and should be optimized in closed-loop control of anesthesia. Cardiovascular changes inducing variations in pharmacokinetics may require dose modification. Rigorous investigational tools can strengthen current knowledge of the anesthesiologists and support clinical practice. We quantify the cardiovascular response of high-risk patients to closed-loop anesthesia and propose a new application of physiologically-based pharmacokinetic-pharmacodynamic (PBPK-PD) simulations to examine the effect of hemodynamic changes on the depth of hypnosis (DoH).

METHODS

We evaluate clinical hemodynamic changes in response to anesthesia induction in high-risk patients from a study on closed-loop anesthesia. We develop and validate a PBPK-PD model to simulate the effect of changes in cardiac output (CO) on plasma levels and DoH. The wavelet-based anesthetic value for central nervous system monitoring index (WAV_CNS) is used as clinical end-point of propofol hypnotic effect.

RESULTS

The median (interquartile range, IQR) changes in CO and arterial pressure (AP), 3 min after induction of anesthesia, are 22.43 (14.82-36.0) % and 26.60 (22.39-35.33) % respectively. The decrease in heart rate (HR) is less marked, i.e. 8.82 (4.94-12.68) %. The cardiovascular response is comparable or less enhanced than in manual propofol induction studies. PBPK simulations show that the marked decrease in CO coincides with high predicted plasma levels and deep levels of hypnosis, i.e. WAV_CNS < 40. PD model identification is improved using the PBPK model rather than a standard three-compartment PK model. PD simulations reveal that a 30% drop in CO can cause a 30% change in WAV_CNS.

CONCLUSIONS

Significant CO drops produce increased predicted plasma concentrations corresponding to deeper anesthesia, which is potentially dangerous for elderly patients. PBPK-PD model simulations allow studying and quantifying these effects to improve clinical practice.

Target-controlled-infusion models for remifentanil dosing consistent with approved recommendations

BACKGROUND

Target-controlled infusion (TCI) systems use pharmacokinetic (PK) models to predict the drug infusion rates necessary to achieve a desired target plasma or effect-site concentration. As new PK models are developed and implemented in TCI systems, there can be uncertainty as to which target concentrations are appropriate. Existing dose recommendations can serve as a point of reference to identify target concentrations suitable for clinical applications.

METHODS

Simulations of remifentanil TCI were performed using three PK models (Minto, Eleveld, and Kim). We sought to identify models and target concentrations for remifentanil administration in children, adult, older people, and severely obese individuals, consistent with the remifentanil product label. In a typical adult this is an induction dose of 0.5-1 μg kg^-1 and starting maintenance infusion rate of 0.25 μg kg^-1 min^-1.

RESULTS

For the Minto, Eleveld, and Kim remifentanil models, a plasma target concentration of ∼ 4 ng ml^-1 achieves drug administration consistent with product label recommended initial doses for all groups with minor exceptions. With effect-site targeting in older individuals, a target concentration of ∼2 ng ml^-1 is required for induction and ∼4 ng ml^-1 for starting maintenance to achieve drug dosages close to product label recommendations.

CONCLUSIONS

We identified remifentanil TCI target concentrations that resulted in drug administration similar to product label dosing recommendations. This approach did not necessarily identify target concentrations that achieve desired clinical effect, only those that are consistent with the product label recommended doses. We estimate that plasma target concentrations of 3.1-5.3 ng ml^-1 are suitable for initial dosing.

External Validation of a Pharmacokinetic Model of Propofol for Target-Controlled Infusion in Children under Two Years Old

BACKGROUND

Previously, a linked pharmacokinetic-pharmacodynamic model (the Kim model) of propofol with concurrent infusion of remifentanil was developed for children aged 2-12 years. There are few options for pharmacokinetic-pharmacodynamic model of propofol for children under two years old. We performed an external validation of the Kim model for children under two years old to evaluate whether the model is applicable to this age group.

METHODS

Twenty-four children were enrolled. After routine anesthetic induction, a continuous infusion of 2% propofol and remifentanil was commenced using the Kim model. The target effect-site concentration of propofol was set as 2, 3, 4, and 5 μg/mL, followed by arterial blood sampling after 10 min of each equilibrium. Population estimates of four parameters-pooled bias, inaccuracy, divergence, and wobble-were used to evaluate the performance of the Kim model.

RESULTS

A total of 95 plasma concentrations were used for evaluation of the Kim model. The population estimate (95% confidence interval) of bias was -0.96% (-8.45%, 6.54%) and that of inaccuracy was 21.0% (15.0%-27.0%) for the plasma concentration of propofol.

CONCLUSION

The pooled bias and inaccuracy of the pharmacokinetic predictions are clinically acceptable. Therefore, our external validation of the Kim model indicated that the model can be applicable to target-controlled infusion of propofol in children younger than 2 years, with the recommended use of actual bispectral index monitoring in clinical settings that remifentanil is present.

TRIAL REGISTRATION

Clinical Research Information Service Identifier: KCT0001752.

Pharmacokinetic and pharmacodynamic considerations of general anesthesia in pediatric subjects

Introduction: The target concentration strategy uses PKPD information for dose determination. Models have also quantified exposure-response relationships, improved understanding of developmental pharmacokinetics, rationalized dose prescription, provided insight into the importance of covariate information, explained drug interactions and driven decision-making and learning during drug development.Areas covered: The prime PKPD consideration is parameter estimation and quantification of variability. The main sources of variability in children are age (maturation) and weight (size). Model use is mostly confined to pharmacokinetics, partly because anesthesia effect models in the young are imprecise. Exploration of PK and PD covariates and their variability hold potential to better individualize treatment.Expert opinion: The ability to model drugs using computer-based technology is hindered because covariate data required to individualize treatment using these programs remain lacking. Target concentration intervention strategies remain incomplete because covariate information that might better predict individualization of dose is absent. Pharmacogenomics appear a valuable area for investigation for pharmacodynamics and pharmacodynamics. Effect measures in the very young are imprecise. Assessment of the analgesic component of anesthesia is crude. While neuromuscular monitoring is satisfactory, depth of anaesthesia EEG interpretation is inadequate. Closed loop anesthesia is possible with better understanding of EEG changes.

Age progression from vicenarians (20-29 year) to nonagenarians (90-99 year) among a population pharmacokinetic/pharmacodynamic (PopPk-PD) covariate analysis of propofol-bispectral index (BIS) electroencephalography

BACKGROUND

Pharmacokinetic/pharmacodynamic (PK/PD) modeling has made an enormous contribution to intravenous anesthesia. Because of their altered physiological, pharmacological and pathological aspects, titrating general anesthesia in the elderly is a challenging task.

METHODS

Eighty patients were consecutively enrolled divided by decades from vicenarians (20-29 year) to nonagenarians (90-99 year) into eight groups. Using target controlled infusion (TCI) and electroencephalographic (EEG)-derived bispectral index (BIS) we set propofol plasma concentration (C_p) to gradually reach 3.5 μg mL^-1 over 3.5-min. In each patient, we constructed a PK/PD model and conducted a population PK/PD (PopPK-PD) covariate analysis.

RESULTS

Age was significant covariate for baseline BIS effect (E₀), inhibitory propofol concentration at 50% BIS decline (IC₅₀) and maximum BIS decline (E_max). First-order rate constant K_e0 of 0.47 min^-1 in vicenarians (20-29 year) gradually increased with age-progression to 1.85 min^-1 in nonagenarians (90-99 year). Simulation modelling showed that clinically recommended C_p of 3.5 μg mL^-1 for 20-29 year BIS 50 should be reduced to 3.0 for 30-49 year, 2.5 for 50-69 year and 2.0 for 80-89 year.

CONCLUSION

We quantified and graded EEG-BIS age-progression among different age groups divided by decades. We demonstrated deeper BIS values with decades' age progression. Our data has important implications for propofol dosing. The practical information for physicians in their daily clinical practice is using propofol C_p of 3.5 μg mL^-1 might not yield BIS value of 50 in elderly patients. Our simulations showed that the recommended regimen of C_p 3.5 μg mL^-1 for 20-29 year should be gradually decreased to 2.0 μg mL^-1 for 80-89 year.

CLINICAL TRIAL REGISTRY NUMBERS

European Community Clinical Trials Database EudraCT (http://eudract.emea.eu) initial trial registration number: 2011-002847-81, and subsequently registered at www.clinicaltrials.gov; trial registration number: NCT02585284. Xijing Hospital of Fourth Military Medical University ethics committee approval number 20110707-4.

Pharmacodynamics and pharmacokinetics in older adults

PURPOSE OF REVIEW

With the growing of the aging population, increased and new methods of anesthesia and surgery allow for surgery and other interventions in older adults.Pharmacokinetics and pharmacodynamics of drugs in older adults differ from those in younger and middle-aged adults. However, the geriatric population is frequently neglected in the context of clinical trials. The present review focuses on the consequences of multimorbidity and pharmacokinetic and pharmacodynamic alterations and their implications on anesthesia.

RECENT FINDINGS

Physiologically based pharmacokinetic and pharmacodynamic modeling may serve as an option to better understand the influence of age on drugs used for anesthesia. However, difficulties to adequately characterize geriatric patients are described.

SUMMARY

Further research of drug effects in the aging population may include physiologically based pharmacokinetic and pharmacodynamic complex models and randomized controlled trials with thoroughly conducted geriatric assessments.

A physiology-based mathematical model for the selection of appropriate ventilator controls for lung and diaphragm protection

Mechanical ventilation is used to sustain respiratory function in patients with acute respiratory failure. To aid clinicians in consistently selecting lung- and diaphragm-protective ventilation settings, a physiology-based decision support system is needed. To form the foundation of such a system, a comprehensive physiological model which captures the dynamics of ventilation has been developed. The Lung and Diaphragm Protective Ventilation (LDPV) model centers around respiratory drive and incorporates respiratory system mechanics, ventilator mechanics, and blood acid–base balance. The model uses patient-specific parameters as inputs and outputs predictions of a patient’s transpulmonary and esophageal driving pressures (outputs most clinically relevant to lung and diaphragm safety), as well as their blood pH, under various ventilator and sedation conditions. Model simulations and global optimization techniques were used to evaluate and characterize the model. The LDPV model is demonstrated to describe a CO₂ respiratory response that is comparable to what is found in literature. Sensitivity analysis of the model indicate that the ventilator and sedation settings incorporated in the model have a significant impact on the target output parameters. Finally, the model is seen to be able to provide robust predictions of esophageal pressure, transpulmonary pressure and blood pH for patient parameters with realistic variability. The LDPV model is a robust physiological model which produces outputs which directly target and reflect the risk of ventilator-induced lung and diaphragm injury. Ventilation and sedation parameters are seen to modulate the model outputs in accordance with what is currently known in literature.

Influence of propofol-based total intravenous anaesthesia on peri-operative outcome measures: a narrative review

Propofol-based total intravenous anaesthesia is well known for its smooth, clear-headed recovery and anti-emetic properties, but there are also many lesser known beneficial properties that can potentially influence surgical outcome. We will discuss the anti-oxidant, anti-inflammatory and immunomodulatory effects of propofol and their roles in pain, organ protection and immunity. We will also discuss the use of propofol in cancer surgery, neurosurgery and older patients.

Bioelectrical impedance analysis of body composition for the anesthetic induction dose of propofol in older patients

Background

Older people are currently the fastest growing segment of the worldwide population. The present study aimed to estimate propofol dose in older patients based on size descriptors measured by bioelectrical impedance analysis (BIA).

Methods

A cross sectional study in adult and older patients with body mass index equal to or lower than 35 kg/m² was carried out. BIA and Clinical Frail Scale scoring were performed during pre-operative evaluation. Propofol infusion was started at 2000 mg/h until loss of consciousness (LOC) which was defined by “loss of eye-lash reflex” and “loss of response to name calling”. Total dose of propofol at LOC was recorded. Propofol plasma concentration was measured using gas chromatography/ion trap-mass spectrometry.

Results

Forty patients were enrolled in the study. Total propofol dose required to LOC was lower in Age ≥ 65 group and a higher plasma propofol concentration was measured in this group. 60% of old patients were classified as “apparently vulnerable” or “frail” and narrow phase angle values were associated with increasing vulnerability scores. In the Age ≥ 65 group, the correlation analysis showed that the relationship between propofol dose and total body weight (TBW) scaled by the corresponding phase angle value is stronger than the correlation between propofol dose and TBW or fat free mass (FFM).

Conclusions

This study demonstrates that weight-based reduction of propofol is suitable in older patients; however FFM was not seen to be more effective than TBW to predict the propofol induction dose in these patients. Guiding propofol induction dose according to baseline frailty score should also be considered to estimate individualized dosage profiles. Determination of phase angle value appears to be an easy and reliable tool to assess frailty in older patients.

Trial registration

ClinicalTrials.gov Identifier: NCT02713698. Registered on 23 February 2016.

A manual propofol infusion regimen for neonates and infants

AIMS

Manual propofol infusion regimens for neonates and infants have been determined from clinical observations in children under the age of 3 years undergoing anesthesia. We assessed the performance of these regimens using reported age-specific pharmacokinetic parameters for propofol. Where performance was poor, we propose alternative dosing regimens.

METHODS

Simulations using a reported general purpose pharmacokinetic propofol model were used to predict propofol blood plasma concentrations during manual infusion regimens recommended for children 0-3 years. Simulated steady state concentrations were 6-8 µg.mL^-1 in the first 30 minutes that were not sustained during 100 minutes infusions. Pooled clinical data (n = 161, 1902 plasma concentrations) were used to determine an alternative pharmacokinetic parameter set for propofol using nonlinear mixed effects models. A new manual infusion regimen for propofol that achieves a steady-state concentration of 3 µg.mL^-1 was determined using a heuristic approach.

RESULTS

A manual dosing regimen predicted to achieve steady-state plasma concentration of 3 µg.mL^-1 comprised a loading dose of 2 mg.kg^-1 followed by an infusion rate of 9 mg.kg^-1 .h^-1 for the first 15 minutes, 7 mg.kg^-1 .h^-1 from 15 to 30 minutes, 6 mg.kg^-1 .h^-1 from 30 to 60 minutes, 5 mg.kg^-1 .h^-1 from 1 to 2 hours in neonates (38-44 weeks postmenstrual age). Dose increased with age in those aged 1-2 years with a loading dose of 2.5 mg.kg^-1 followed by an infusion rate of 13 mg.kg^-1 .h^-1 for the first 15 minutes, 12 mg.kg^-1 .h^-1 from 15 to 30 minutes, 11 mg.kg^-1 .h^-1 from 30 to 60 minutes, and 10 mg.kg^-1 .h^-1 from 1 to 2 hours.

CONCLUSION

Propofol clearance increases throughout infancy to reach 92% that reported in adults (1.93 L.min.70 kg^-1 ) by 6 months postnatal age and infusion regimens should reflect clearance maturation and be cognizant of adverse effects from concentrations greater than the target plasma concentration. Predicted concentrations using a published general purpose pharmacokinetic propofol model were similar to those determined using a new parameter set using richer neonatal and infant data.

Practicalities of Total Intravenous Anesthesia and Target-controlled Infusion in Children

Propofol administered in conjunction with an opioid such as remifentanil is used to provide total intravenous anesthesia for children. Drugs can be given as infusion controlled manually by the physician or as automated target-controlled infusion that targets plasma or effect site. Smart pumps programmed with pharmacokinetic parameter estimates administer drugs to a preset plasma concentration. A linking rate constant parameter (keo) allows estimation of effect site concentration. There are two parameter sets, named after the first author describing them, that are commonly used in pediatric target-controlled infusion for propofol (Absalom and Kataria) and one for remifentanil (Minto). Propofol validation studies suggest that these parameter estimates are satisfactory for the majority of children. Recommended target concentrations for both propofol and remifentanil depend on the type of surgery, the degree of surgical stimulation, the use of local anesthetic blocks, and the ventilatory status of the patient. The use of processed electroencephalographic monitoring is helpful in pediatric total intravenous anesthesia and target-controlled infusion anesthesia, particularly in the presence of neuromuscular blockade.

A pharmacokinetic model optimized by covariates for propofol target-controlled infusion in dogs

OBJECTIVE

To develop a population pharmacokinetic model for propofol target-controlled infusion (TCI) in dogs and to evaluate its performance for use in the clinical setting.

STUDY DESIGN

Prospective clinical study.

ANIMALS

A group of 40 client-owned dogs undergoing general anaesthesia for magnetic resonance imaging.

METHODS

Propofol was administered to 26 premedicated dogs and arterial blood samples were collected during the infusion and over 240 minutes after terminating the infusion. Propofol concentrations were measured by high-performance liquid chromatography. A population pharmacokinetic analysis was performed using a nonlinear mixed-effects modelling approach, allowing inter- and intra-individual variability estimation and quantitative evaluation of the influence of the following covariates: weight, body condition score, age, size-related age (Age_size), sex, premedication type, size and contrast agent administration. A final model was obtained using a stepwise approach in which individual covariate effects on each pharmacokinetic variable were incorporated. The performance of the developed TCI model was subsequently evaluated while inducing and maintaining anaesthesia in 14 premedicated dogs and assessed by comparing predicted and measured concentrations at specific time points.

RESULTS

Propofol pharmacokinetics was best described by a three-compartment model. Weight, Age_size, premedication and sex showed significant pharmacokinetic effects. Addition of the significant covariate/variable associations to the final model resulted in a reduction of the objective function value from 285.53 to -22.34. The median values of prediction error and absolute performance error were 3.1% and 28.4%, respectively. Induction targets between 4.0 and 6.5 μg mL^-1 allowed intubation within 5.0 ± 0.9 minutes. Anaesthesia was achieved with targets between 3.0 and 6.5 μg mL^-1. Mean time to extubation was 9.7 ± 2.6 minutes. All dogs recovered smoothly and without complications.

CONCLUSIONS AND CLINICAL RELEVANCE

Overall predictive performance of the pharmacokinetic model-driven infusion developed was clinically acceptable for administering propofol to dogs in routine anaesthesia.

Predictive performance of a new pharmacokinetic model for propofol in underweight patients during target-controlled infusion

BACKGROUND

In a previous study, the modified Marsh and Schnider models respectively showed negatively- and positively-biased predictions in underweight patients. To overcome this drawback, we developed a new pharmacokinetic propofol model-the Choi model-for use in underweight patients. In the present study, we evaluated the predictive performance of the Choi model.

METHODS

Twenty underweight patients undergoing elective surgery received propofol via TCI using the Choi model. The target effect-site concentrations (Ces) of propofol were 2.5, 3, 3.5, 4, 4.5, and 2 μg/mL. Arterial blood samples were obtained at least 10 minutes after achieving pseudo-steady-state. Predicted propofol concentrations with the modified Marsh, Schnider, and Eleveld pharmacokinetic models were obtained by simulation (Asan pump, version 2.1.3; Bionet Co. Ltd., Seoul, Korea). The predictive performance of each model was assessed by calculation of four parameters: inaccuracy, divergence, bias, and wobble.

RESULTS

A total of 119 plasma samples were used to determine the predictive performance of the Choi model. Our evaluation showed that the pooled median (95% CI) bias and inaccuracy were 4.0 (-4.2 to 12.2) and 23.9 (17.6-30.3), respectively. The pooled biases and inaccuracies of the modified Marsh, Schnider, and Eleveld models were clinically acceptable. However, the modified Marsh and Eleveld models consistently produced negatively biased predictions in underweight patients. In particular, the Schnider model showed greater inaccuracy at a target Ce ≥ 3 µg/mL.

CONCLUSION

The new propofol pharmacokinetic model (the Choi model) developed for underweight patient showed adequate performance for clinical use.

Future of paediatric sedation: towards a unified goal of improving practice

This review offers a perspective on the future of paediatric sedation. This future will require continued evaluation of adverse events, their risk factors, and predictors. As the introduction of new sedatives with paediatric applications will remain limited, the potential role of mainstay sedatives administered by new routes, for new indications, and with new delivery techniques, should be considered. The role of non-pharmacological strategies for anxiolysis, along with the application of non-mainstay physiologic monitoring, may aid in the improvement of targeted sedation delivery. Understanding the mechanism and location of action of the different sedatives will remain an important focus. Important developments in paediatric sedation will require that large scale studies with global data contribution be conducted in order to support changes in sedation practice, improve the patient experience, and make sedation safer.

Clinical Pharmacokinetics and Pharmacodynamics of Propofol

Propofol is an intravenous hypnotic drug that is used for induction and maintenance of sedation and general anaesthesia. It exerts its effects through potentiation of the inhibitory neurotransmitter γ-aminobutyric acid (GABA) at the GABAA receptor, and has gained widespread use due to its favourable drug effect profile. The main adverse effects are disturbances in cardiopulmonary physiology. Due to its narrow therapeutic margin, propofol should only be administered by practitioners trained and experienced in providing general anaesthesia. Many pharmacokinetic (PK) and pharmacodynamic (PD) models for propofol exist. Some are used to inform drug dosing guidelines, and some are also implemented in so-called target-controlled infusion devices, to calculate the infusion rates required for user-defined target plasma or effect-site concentrations. Most of the models were designed for use in a specific and well-defined patient category. However, models applicable in a more general population have recently been developed and published. The most recent example is the general purpose propofol model developed by Eleveld and colleagues. Retrospective predictive performance evaluations show that this model performs as well as, or even better than, PK models developed for specific populations, such as adults, children or the obese; however, prospective evaluation of the model is still required. Propofol undergoes extensive PK and PD interactions with both other hypnotic drugs and opioids. PD interactions are the most clinically significant, and, with other hypnotics, tend to be additive, whereas interactions with opioids tend to be highly synergistic. Response surface modelling provides a tool to gain understanding and explore these complex interactions. Visual displays illustrating the effect of these interactions in real time can aid clinicians in optimal drug dosing while minimizing adverse effects. In this review, we provide an overview of the PK and PD of propofol in order to refresh readers' knowledge of its clinical applications, while discussing the main avenues of research where significant recent advances have been made.

Modeling the pharmacokinetics and pharmacodynamics of sevoflurane using compartment models in children and adults

BACKGROUND

Sevoflurane pharmacokinetics have been traditionally described using physiological models, while pharmacodynamics employed the use of minimal alveolar concentration.

AIMS

The integrated pharmacokinetic-pharmacodynamic relationship of sevoflurane in both adults and children was reviewed using compartment models. We wished to delineate age-related changes in both pharmacokinetics and pharmacodynamics.

METHODS

The bispectral index and sevoflurane endtidal concentration were continuously measured in 50 patients, aged 3-71 years, scheduled for minor surgery. During maintenance of anesthesia and after stable bispectral index values of 60-65 were obtained, the inspired concentration of sevoflurane was increased to 5 vol % for 5 minutes or until BIS 40 and then decreased. Data were analyzed using mammillary compartments with nonlinear mixed effects population modeling. The covariate effects of age and size were investigated.

RESULTS

A three-compartment PK model adequately described sevoflurane pharmacokinetics. Size standardization using allometry explained clearance and volume changes with age. The equilibration half-time (1.48 minutes) increased with age, but could be predicted using allometry in those under 40 years. The effect site concentration eliciting half the maximum response at age 40 years was 1.3% (95%CI 1.22, 1.42) decreased with age from 1.6% at 3 years to 1.1% at 70 years.

CONCLUSION

Pharmacokinetic compartment models offer an alternative method to describe inhalation anesthetic drug disposition and effects.