General Purpose Pharmacokinetic-Pharmacodynamic Models for Target-Controlled Infusion of Anaesthetic Drugs: A Narrative Review.

Target controlled infusion (TCI) is a clinically-available and widely-used computer-controlled method of drug administration, adjusting the drug titration towards user selected plasma- or effect-site concentrations, calculated according to pharmacokinetic-pharmacodynamic (PKPD) models. Although this technology is clinically available for several anaesthetic drugs, the contemporary commercialised PKPD models suffer from multiple limitations. First, PKPD models for anaesthetic drugs are developed using deliberately selected patient populations, often excluding the more challenging populations, such as children, obese or elderly patients, of whom the body composition or elimination mechanisms may be structurally different compared to the lean adult patient population. Separate PKPD models have been developed for some of these subcategories, but the availability of multiple PKPD models for a single drug increases the risk for invalid model selection by the user. Second, some models are restricted to the prediction of plasma-concentration without enabling effect-site controlled TCI or they identify the effect-site equilibration rate constant using methods other than PKPD modelling. Advances in computing and the emergence of globally collected databases has allowed the development of new "general purpose" PKPD models. These take on the challenging task of identifying the relationships between patient covariates (age, weight, sex, etc) and the volumes and clearances of multi-compartmental pharmacokinetic models applicable across broad populations from neonates to the elderly, from the underweight to the obese. These models address the issues of allometric scaling of body weight and size, body composition, sex differences, changes with advanced age, and for young children, changes with maturation and growth. General purpose models for propofol, remifentanil and dexmedetomidine have appeared and these greatly reduce the risk of invalid model selection. In this narrative review, we discuss the development, characteristics and validation of several described general purpose PKPD models for anaesthetic drugs.

Utility of the SmartPilot® View advisory screen to improve anaesthetic drug titration and postoperative outcomes in clinical practice: a two-centre prospective observational trial.

BACKGROUND: The advisory system SmartPilot® View (Drägerwerk AG, Lübeck, Germany) provides real-time, demographically adjusted pharmacodynamic information throughout anaesthesia, including time course of effect-site concentrations of administered drugs and a measure of potency of the combined drug effect termed the "'Noxious Stimulation Response Index' (NSRI). This dual-centre, prospective, observational study assesses whether the availability of SmartPilot® View alters the behaviour of anaesthetic drug titration of anaesthetists and improves the Anaesthesia Quality Score (AQS; percentage of time spent with MAP 60-80 mm Hg and Bispectral Index [BIS] 40-60 [blinded]). METHODS: We recruited 493 patients scheduled for elective surgery in two university centres. A control group (CONTROL; n=170) was enrolled to observe drug titration in current practice. Thereafter, an intervention group was enrolled, for which SmartPilot® View was made available to optimise drug titration (SPV; n=188). The AQS, haemodynamic and hypnotic effects, recovery times, pain scores, and other parameters were compared between groups. RESULTS: There were 358 patients eligible for analysis. Anaesthesia quality score was similar between CONTROL and SPV (median AQS [Q1-Q3]) 25.3% [7.4-41.5%] and 22.2% [8.0-44.4%], respectively; P=0.898). Compared with CONTROL, SPV patients had less severe hypotension and hypertension, less BIS <40, faster tracheal extubation, and lower early postoperative pain scores. CONCLUSIONS: Adding SmartPilot® View information did not affect average drug titration behaviour. However, small improvements in control of MAP and BIS and early recovery suggest improved titration for some patients without increasing the risk of overdosing or underdosing. CLINICAL TRIAL REGISTRATION: NCT01467167.

Dexmedetomidine Clearance Decreases with Increasing Drug Exposure: Implications for Current Dosing Regimens and Target-controlled Infusion Models Assuming Linear Pharmacokinetics.

BACKGROUND: Numerous pharmacokinetic models have been published aiming at more accurate and safer dosing of dexmedetomidine. The vast majority of the developed models underpredict the measured plasma concentrations with respect to the target concentration, especially at plasma concentrations higher than those used in the original studies. The aim of this article was to develop a dexmedetomidine pharmacokinetic model in healthy adults emphasizing linear versus nonlinear kinetics. METHODS: The data of two previously published clinical trials with stepwise increasing dexmedetomidine target-controlled infusion were pooled to build a pharmacokinetic model using the NONMEM software package (ICON Development Solutions, USA). Data from 48 healthy subjects, included in a stratified manner, were utilized to build the model. RESULTS: A three-compartment mamillary model with nonlinear elimination from the central compartment was superior to a model assuming linear pharmacokinetics. Covariates included in the final model were age, sex, and total body weight. Cardiac output did not explain between-subject or within-subject variability in dexmedetomidine clearance. The results of a simulation study based on the final model showed that at concentrations up to 2 ng · ml-1, the predicted dexmedetomidine plasma concentrations were similar between the currently available Hannivoort model assuming linear pharmacokinetics and the nonlinear model developed in this study. At higher simulated plasma concentrations, exposure increased nonlinearly with target concentration due to the decreasing dexmedetomidine clearance with increasing plasma concentrations. Simulations also show that currently approved dosing regimens in the intensive care unit may potentially lead to higher-than-expected dexmedetomidine plasma concentrations. CONCLUSIONS: This study developed a nonlinear three-compartment pharmacokinetic model that accurately described dexmedetomidine plasma concentrations. Dexmedetomidine may be safely administered up to target-controlled infusion targets under 2 ng · ml-1 using the Hannivoort model, which assumed linear pharmacokinetics. Consideration should be taken during long-term administration and during an initial loading dose when following the dosing strategies of the current guidelines.

Comment on Morse et al. A Universal Pharmacokinetic Model for Dexmedetomidine in Children and Adults. J. Clin. Med. 2020, 9, 3480.

We read with interest the recently published manuscript [...].

Cardiac Arrest Caused by an Acute Intrathoracic Gastric Volvulus Treated With Percutaneous Gastrostomy.

During cardiopulmonary resuscitation, one of the first priorities after establishing basic and advanced life support is to identify the cause of the arrest. We present a rare case of cardiac arrest due to a decreased venous return from mediastinal shift caused by a paraesophageal hernia with an incarcerated thoracic gastric volvulus, which was treated by percutaneous gastrostomy.

Prospective clinical validation of the Eleveld propofol pharmacokinetic-pharmacodynamic model in general anaesthesia.

BACKGROUND: Target-controlled infusion (TCI) systems incorporating pharmacokinetic (PK) or PK-pharmacodynamic (PK-PD) models can be used to facilitate drug administration. Existing models were developed using data from select populations, the use of which is, strictly speaking, limited to these populations. Recently a propofol PK-PD model was developed for a broad population range. The aim of the study was to prospectively validate this model in children, adults, older subjects, and obese adults undergoing general anaesthesia. METHODS: The 25 subjects included in each of four groups were stratified by age and weight. Subjects received propofol through TCI with the Eleveld model, titrated to a bispectral index (BIS) of 40-60. Arterial blood samples were collected at 5, 10, 20, 30, 40, and 60 min after the start of propofol infusion, and every 30 min thereafter, to a maximum of 10 samples. BIS was recorded continuously. Predictive performance was assessed using the Varvel criteria. RESULTS: For PK, the Eleveld model showed a bias < ±20% in children, adults, and obese adults, but a greater bias (-27%) in older subjects. Precision was <30% in all groups. For PD, the bias and wobble were <5 BIS units and the precision was close to 10 BIS units in all groups. Anaesthetists were able to achieve intraoperative BIS values of 40-60 using effect-site target concentrations about 85-140% of the age-adjusted Ce50. CONCLUSIONS: The Eleveld propofol PK-PD model showed predictive precision <30% for arterial plasma concentrations and BIS predictions with a low (population) bias when used in TCI in clinical anaesthesia practice.

The role of pharmacokinetics and pharmacodynamics in clinical anaesthesia practice.

PURPOSE OF REVIEW: Growing concerns about the environmental effects of volatile anaesthetics are likely to lead to increased use of intravenous anaesthetic drugs. Pharmacokinetic/pharmacodynamic (PKPD) models can increase the accuracy of intravenous drug titration, especially in populations that differ from the 'average.' However, with a growing number of PKPD models, and other technology available to date, it can be hard to see the wood for the trees. This review attempts to guide the reader through the PKPD jungle. RECENT FINDINGS: General purpose PKPD models for propofol and remifentanil designed to apply to a broader population, including children, the elderly and the obese, reduce the need for population-specific models. PKPD models for drugs such as dexmedetomidine and antimicrobial agents may be useful for procedural sedation or in the ICU. Technological advances such as Bayesian model adjustment based on point-of-care plasma concentration measurements, closed-loop drug delivery and artificial intelligence may improve the ease of use of the anaesthetic drugs and increase the accuracy of titration. SUMMARY: Newer and more complex modelling techniques and technological advancements can help to deliver anaesthetic drugs, sedatives and other drugs in a more stable and thereby safer way.

Clinical Pharmacokinetics and Pharmacodynamics of Dexmedetomidine.

Dexmedetomidine is an α2-adrenoceptor agonist with sedative, anxiolytic, sympatholytic, and analgesic-sparing effects, and minimal depression of respiratory function. It is potent and highly selective for α2-receptors with an α2:α1 ratio of 1620:1. Hemodynamic effects, which include transient hypertension, bradycardia, and hypotension, result from the drug's peripheral vasoconstrictive and sympatholytic properties. Dexmedetomidine exerts its hypnotic action through activation of central pre- and postsynaptic α2-receptors in the locus coeruleus, thereby inducting a state of unconsciousness similar to natural sleep, with the unique aspect that patients remain easily rousable and cooperative. Dexmedetomidine is rapidly distributed and is mainly hepatically metabolized into inactive metabolites by glucuronidation and hydroxylation. A high inter-individual variability in dexmedetomidine pharmacokinetics has been described, especially in the intensive care unit population. In recent years, multiple pharmacokinetic non-compartmental analyses as well as population pharmacokinetic studies have been performed. Body size, hepatic impairment, and presumably plasma albumin and cardiac output have a significant impact on dexmedetomidine pharmacokinetics. Results regarding other covariates remain inconclusive and warrant further research. Although initially approved for intravenous use for up to 24 h in the adult intensive care unit population only, applications of dexmedetomidine in clinical practice have been widened over the past few years. Procedural sedation with dexmedetomidine was additionally approved by the US Food and Drug Administration in 2003 and dexmedetomidine has appeared useful in multiple off-label applications such as pediatric sedation, intranasal or buccal administration, and use as an adjuvant to local analgesia techniques.

Development of an Optimized Pharmacokinetic Model of Dexmedetomidine Using Target-controlled Infusion in Healthy Volunteers.

BACKGROUND: Several pharmacokinetic models are available for dexmedetomidine, but these have been shown to underestimate plasma concentrations. Most were developed with data from patients during the postoperative phase and/or in intensive care, making them susceptible to errors due to drug interactions. The aim of this study is to improve on existing models using data from healthy volunteers. METHODS: After local ethics committee approval, the authors recruited 18 volunteers, who received a dexmedetomidine target-controlled infusion with increasing target concentrations: 1, 2, 3, 4, 6, and 8 ng/ml, repeated in two sessions, at least 1 week apart. Each level was maintained for 30 min. If one of the predefined safety criteria was breached, the infusion was terminated and the recovery period began. Arterial blood samples were collected at preset times, and NONMEM (Icon plc, Ireland) was used for model development. RESULTS: The age, weight, and body mass index ranges of the 18 volunteers (9 male and 9 female) were 20 to 70 yr, 51 to 110 kg, and 20.6 to 29.3 kg/m, respectively. A three-compartment allometric model was developed, with the following estimated parameters for an individual of 70 kg: V1 = 1.78 l, V2 = 30.3 l, V3 = 52.0 l, CL = 0.686 l/min, Q2 = 2.98 l/min, and Q3 = 0.602 l/min. The predictive performance as calculated by the median absolute performance error and median performance error was better than that of existing models. CONCLUSIONS: Using target-controlled infusion in healthy volunteers, the pharmacokinetics of dexmedetomidine were best described by a three-compartment allometric model. Apart from weight, no other covariates were identified.

A response surface model approach for continuous measures of hypnotic and analgesic effect during sevoflurane-remifentanil interaction: quantifying the pharmacodynamic shift evoked by stimulation.

BACKGROUND: The authors studied the interaction between sevoflurane and remifentanil on bispectral index (BIS), state entropy (SE), response entropy (RE), Composite Variability Index, and Surgical Pleth Index, by using a response surface methodology. The authors also studied the influence of stimulation on this interaction. METHODS: Forty patients received combined concentrations of remifentanil (0 to 12 ng/ml) and sevoflurane (0.5 to 3.5 vol%) according to a crisscross design (160 concentration pairs). During pseudo-steady-state anesthesia, the pharmacodynamic measures were obtained before and after a series of noxious and nonnoxious stimulations. For the "prestimulation" and "poststimulation" BIS, SE, RE, Composite Variability Index, and Surgical Pleth Index, interaction models were applied to find the best fit, by using NONMEM 7.2.0. (Icon Development Solutions, Hanover, MD). RESULTS: The authors found an additive interaction between sevoflurane and remifentanil on BIS, SE, and RE. For Composite Variability Index, a moderate synergism was found. The comparison of pre- and poststimulation data revealed a shift of C50SEVO for BIS, SE, and RE, with a consistent increase of 0.3 vol%. The Surgical Pleth Index data did not result in plausible parameter estimates, neither before nor after stimulation. CONCLUSIONS: By combining pre- and poststimulation data, interaction models for BIS, SE, and RE demonstrate a consistent influence of "stimulation" on the pharmacodynamic relationship between sevoflurane and remifentanil. Significant population variability exists for Composite Variability Index and Surgical Pleth Index.

Hemodynamics and tissue oxygenation during balanced anesthesia with a high antinociceptive contribution: an observational study.

BACKGROUND: In particular surgical conditions, a balanced anesthesia with a high-antinociceptive contribution is required. This may induce cardiovascular impairment and thus compromise tissue oxygenation. In this prospective observational study, we investigated the hemodynamic stability and tissue oxygen saturation (StO2) in 40 patients with a high-antinociceptive general anesthesia, goal-directed fluid therapy, and norepinephrine. In addition, optimal surgical conditions and safe and fast emergence are pivotal parts of anesthetic management. METHODS: In high-antinociceptive propofol/remifentanil anesthesia with bispectral index (BIS) between 40 and 60, norepinephrine was administered to maintain mean arterial pressure (MAP) above 80% of individual baseline. Fluid was administered if the ∆ plethysmographic waveform amplitude exceeded 10%. Surgical and recovery conditions, hemodynamic responses, and tissue oxygenation were investigated. RESULTS: Mean (SD) StO2 at the left thenar eminence increased from 83 (6)% before to 86 (4)% 20 min after induction of anesthesia (p <0.05). Cardiac index dropped from 3.0 (0.7) to 2.1 (0.4) L min(-1) (p <0.05), MAP from 109 (16) to 83 (14) mm Hg, and heart rate from 73 (12) to 54 (8) bpm (p <0.05). Thirteen out of 40 patients received a fluid bolus. The median (range) norepinephrine administration rate was 0.05 (0.0-0.10) µg kg(-1) min(-1). After complete akinesia in all patients during surgery, a median (IQR) extubation time of 311 (253-386) s was observed. CONCLUSIONS: This high-antinociceptive balanced anesthesia with goal-directed fluid and vasopressor therapy adequately preserved StO2 and hemodynamic homeostasis. TRIAL REGISTRATION: ISRCTN20153044.