Pharmacokinetics and pharmacodynamics of propofol in patients undergoing abdominal aortic surgery

Pharmacological Reports 212, 64, 113 122 ISSN 1734-114 Copyright 212 by Institute of Pharmacology Polish Academy of Sciences Pharmacokinetics and pharmacodynamics of propofol in patients undergoing abdominal aortic surgery Pawe³ Wiczling 1, Agnieszka Bienert 2, Pawe³ Sobczyñski 3, Roma Hartmann-Sobczyñska 4, Krzysztof Bieda 3, Aleksandra Marcinkowska 2, Maria Malatyñska 2, Roman Kaliszan 1, Edmund Grzeœkowiak 2 1 Department of Biopharmaceutics and Pharmacokinetics, Medical University of Gdansk, Hallera 17, PL 8-416, Gdañsk, Poland 2 Department of Clinical Pharmacy and Biopharmacy, 3 Department of Anaesthesiology and Intensive Therapy, 4 Department of Experimental Anaesthesiology, Poznan University of Medical Sciences, œw. Marii Magdaleny 14, PL 61-861 Poznañ, Poland Correspondence: Agnieszka Bienert, e-mail: agnbienert@op.pl Abstract: 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 4 and 6. 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 =.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.24 min 1. The BIS index was linked to the effect site concentrations through a sigmoidal E max model with EC 5 = 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. Key words: propofol, aortic surgery, pharmacokinetics and pharmacodynamics Introduction Propofol total intravenous anesthesia (TIVA) is a widely used technique to induce unconsciousness in patients undergoing major aortic surgery. Vascular surgery patients present a formidable challenge to the practising intensivist. These patients are often at advanced age and carry significant cardiac, respiratory, and renal co-morbidities [26]. Among different types of non-cardiac surgery, peripheral vascular surgery is likely to have the highest cardiac morbidity and overall mortality. The economic burden associated with this complication is estimated to be $2 billion annually [26]. As the patients undergoing this type of sur- Pharmacological Reports, 212, 64, 113 122 113

gery are at higher risk during general anesthesia [23, 26], optimal dosing of administered drugs is of great importance. Propofol is a drug with narrow therapeutic index, which may cause severe hypotension and hemodynamic instability during induction of anesthesia, especially if it is given in too large doses. Available propofol pharmacokinetic protocols, which are used for target controlled infusions (TCI), were derived on the basis of a relatively small number of healthy individuals [1, 19, 2]. However, the disposition as well as the response to any given drug may be altered by clinical conditions. During abdominal aortic surgery many factors may potentially alter the pharmacokinetics (PK) and pharmacodynamics (PD) of propofol. For example, the aortic cross-clamping affects the renal artery blood flow, either through direct interruption of the flow or through thromboembolic events. The aortic cross-clamping affects the cardiac output and organ flow during surgery [3, 1, 11, 23], thus vasopressors are given intraoperatively to prevent hypotension. In consequence, this may modify the clearance of drugs with a high hepatic extraction ratio, like propofol. Propofol is a highly extracted drug. Therefore, its clearance is flow-dependent. For such drugs changes in the cardiac output are expected to modify the concentration and effects. It has been demonstrated that propofol clearance in critically ill patients is decreased by 38% in patients with heart failure [16]. Propofol is a highly lipophilic drug, which tightly binds to various plasma components, i.e., erythrocytes, hemoglobin and serum albumin [14]. During abdominal aortic surgery patients are continuously infused with crystalloid and colloid fluids, which may dilute the blood, have influence on the hematocrit and in consequence on the free fraction of the drug. In the study by Knibbe et al. [12] the body temperature and serum triglycerides were found to influence the metabolic clearance of propofol. Hyper- and hypothermia, metabolic changes and blood loss are common events and complications during aortic surgery [23]. Thus, the available propofol TCI systems, which are based on data from healthy subjects, may fail in this group of patients. In literature there are limited data on PK/PD parameters of propofol during this type of surgery. The aim of our study was to develop the PK/PD model for propofol in patients undergoing abdominal aortic surgery and to compare it to the models available in TCI systems as well as to the literature models for healthy and ill subjects. Subjects and Methods After approval by the Research Ethics Committee at the University of Medical Sciences (Poznañ, Poland) and informed, written consent, ten male ASA physical status III patients (5 75 years, 5 92 kg weight) scheduled for elective abdominal aortic surgery were included. The surgery was conducted under propofolfentanyl TIVA. The TCI system Diprifusor (Astra Zeneca, UK) was used to administer propofol. Pancuronium.1 mg/kg was administered to facilitate intubation and then as required. Fentanyl, 2 3 µg/kg, was administered whenever inadequate analgesia was assessed throughout the surgery. The bispectral index (BIS; A-2, Aspect Medical System, Newton, MA, USA) was used to measure the depth of anesthesia and propofol dosing was adjusted to keep the BIS level between 4 and 6. During the surgery, crystalloid and colloid fluids were infused according to the standard protocol. After the surgery, the patients were mechanically ventilated in intensive care unit (ICU) settings until full recovery and propofol infusion was maintained until extubation. Blood samples for measuring the plasma propofol concentration were drawn from forearm veins before the propofol infusion, 1, 3, 5, 1, 15 and 3 min after the beginning of the infusion, then every 3 min until the end of anesthesia and also after 1, 3, 5, 1, 15, 3, 6 9, 12 and 24 min after the termination of propofol infusion. The blood samples were transferred into heparinized tubes and they were centrifuged immediately after collection. Plasma was stored at 4 C. Propofol concentration in the plasma was measured within 8 weeks by highperformance liquid chromatography with a fluorescence detector [7, 8]. The limit of quantification was estimated at 5 ng/ml. The within-day coefficients of variation were less than 1%. PK/PD model Population non-linear mixed-effect modeling was done with Nonmem (Version 7.1., Icon Development Solutions, Ellicott City, MD, USA) and the Intel Fortran Compiler 9.. Nonmem runs were executed with Wings for Nonmem (WFN711, http://wfn. sourceforge.net). The first-order conditional estimation with interaction (FOCE) method was used. The minimum value of the Nonmem objective function (MOF), typical goodness of fit diagnostic plots, and 114 Pharmacological Reports, 212, 64, 113 122

PK/PD of propofol in aortic surgery patients Pawe³ Wiczling et al. Fig. 1. Diagram of PK/PD model of propofol evaluation of the precision of PK parameter and variability estimates were used to discriminate between various models during the model-building process. The Nonmem data processing and plots were done in Matlab Software version 7. (The MathWorks, Inc., Natick, MA, USA). The schematic representation of the PK and PD model is given in Figure 1. The free plasma propofol concentration was described with a two-compartment model (ADVAN3 TRANS4): (1) where C P and C T are the propofol concentrations in the central and peripheral compartment, V C and V T denote the volume of the central and peripheral compartment, and Cl and Q denote the metabolic and inter-compartmental clearance. The Input(t) reflects the infusion rate and all extra boluses that were given to individual patients In the PD analysis the fixed individual PK parameters were used to generate drug concentration for a given time point. Delay of the anesthetic effect, with respect to plasma concentrations, was described with the effect compartment. The time course of electroencephalographic (EEG) spectral frequency index (BIS) was linked to the effect (biophase) site concentrations through a sigmoidal Emax model: (2) where BIS denotes the baseline BIS score (fully awake). The E max is the maximal effect fixed to 1 and EC 5 is the concentration for 5% decrease in BIS score. The C e denotes the effect compartment (biophase) concentration: (3) where k eo denotes biophase distribution rate constant. Inter-individual variability (IIV) for the PK/PD parameters was modelled assuming log normal distribution: (4) where P is the individual parameter, P is the typical value of this parameter in the population, and P is a random effect for that parameter with the mean and variance P 2. The observed concentration of propofol and BIS score were defined by the following equations: (5) (6) where C P and BIS are defined by the Eq. (1) and (2) of the basic structural population model, prop,c represents the proportional residual random errors of propofol concentrations and prop,bis represents the additive residual random of BIS scores. It was assumed that is normally distributed with the mean of and variances denoted by 2 prop,c and 2 add,bis. Pharmacological Reports, 212, 64, 113 122 115

Covariates selection Possible relationships between patient-specific covariates (body size, age, blood pressure and gender) and the individual pharmacokinetic parameter estimates were explored by graphical analysis. During the covariate search, the effect of each covariate was examined by adding appropriate relationship into the base model. The likelihood ratio was determined as the difference in the objective function (MOF) of the full model (with covariate) and reduced model (without covariate) after refitting the data. Since the difference in the minimum of the NONMEM objective function (MOF) obtained for the two hierarchical models (likelihood ratio) is approximately 2 distributed, the difference in MOF between models of 7.9 for one degree of freedom was considered to be statistically significant at p <.5 for the factor to be included in the base model. Simulations In literature there is a great variety of models used to describe the PK/PD of propofol in healthy and ill patients. It makes the direct comparison of model parameters difficult, as the potential difference might be a consequence of different model structure. In this study, the final model has been compared with literature PK/PD models of propofol by means of simulations. We selected the following models: Schnider [19], Bjornsson [5], Schuttler [21], Marsh [13] and Peeters [17] and simulated concentrations and BIS index for a typical 4-year-old male of 7 kg and 17 cm To standardize the comparison of the models, the same infusion was used with the initial dose 2 mg/kg, rate of infusion.2 mg/min/kg and duration of infusion 2 min. The performance error (MDAPE) The propofol concentration calculated with the TCI system (target concentration) was recorded every time a sample was taken. At each time-point the percentage performance error was calculated as: PE = 1 (measured concentration-target concentration)/(target concentration). For each subject a median absolute performance error (MDAPE) was calculated as the median of the absolute PEs. Similarly, a median per- 2 ID: 1 ID: 2 1 2 1 2 ID: 3 ID: 4 Fig. 2. Plot of observed (open circle), population predicted (dotted line) and individual predicted (solid line) propofol concentrations vs. time for the final PK model Propofol Concentration, mg/l 1 2 1 2 1 2 ID: 5 ID: 6 1 2 ID: 7 ID: 8 1 2 1 2 ID: 9 ID: 1 1 2 5 1 15 2 5 1 15 2 Time, h 116 Pharmacological Reports, 212, 64, 113 122

PK/PD of propofol in aortic surgery patients Pawe³ Wiczling et al. Tab. 1. Summary of the final population PK parameters and inter-subject and residual error variance estimates of propofol Parameter, unit Description Estimate (% CV) Fixed effect V, (l) Volume of central compartment 24.7 (16.2) Cl (l/min) Elimination clearance 2.64 (48.2) VT (l) Volume of peripheral compartment 112 (24.6) Q (l/min) Distribution clearance.989 (11.2) Inter-individual variability 2 VC (%) Inter-individual variability of V C 4.2 (32.8) 2 CL (%) Inter-individual variability of CL 38.2 (48.2) 2 VT (%) Inter-individual variability of V T 9 (25.2) 2 Q (%) Inter-individual variability of Q Fixed Residual variability 2 prop,cp (%) Proportional residual error variability 39.5 (6.8) formance error (MDPE) was calculated as the median of PEs. MDAPE indicates the inaccuracy of TCI while the MDPE reflects the bias in achieving the target concentration [6, 24]. Results The pharmacokinetic model of propofol in patients scheduled for abdominal aortic surgery was based on 17 samples from 1 surgery patients (1 21 propofol concentration measurements per patient). A twocompartment pharmacokinetic model without any covariates best described the observations. The use of a two-compartment model is in agreement with the literature models of critically ill patients undergoing long term sedation [4, 12, 17]. On the contrary, for healthy subjects and very rich data sets even three- or four-compartment models have been identified [5, 21, 22]. In this study, it was impossible to distinguish all the fast disposition processes due to limited sampling, especially within the first 3 min after the beginning and end of the infusion. The propofol PK data along with model predictions is presented in Figure 2. This plot shows that the final PK model describes the measured concentrations well. The parameter estimates of the proposed PK model are listed in Table 1. All parameters were estimated with high precision (coefficient of variations lower than 5%). The typical value of the volume of the central and peripheral compartment was 24.7 l and 112 l. The metabolic and distribution clearances were estimated at 2.64 l/min and.989 l/min. Except Q, the inter-individual variability of all parameters was high, ranging from 4% to 9%. The body weight, age, blood pressure and gender were not identified as significant covariates during the model building process. It was most likely the consequence of a small number of patients with similar demographic characteristics. The literature metabolic clearances for a typical adult male patient of 7 kg ranged from 1.23 to 2.5 l/min [5, 13, 17, 19, 21,], and were much lower than the value of clearance estimated in this study. The simulations presented in Figure 3 show that a higher clearance led to lower concentrations than those predicted on the basis of literature models. It has a big consequence for the TCI system, where the dosing of the patients is based on the model predicted concentrations. In our study, the TCI inaccuracy (MDAPE) was estimated at 3.5% (14.9 57.9%), whereas the mean bias (MDPE) value was 11.% ( 37. 19.6%). The pharmacodynamic part of the model was based on 363 samples from 1 surgery patients (3 47 BIS index values per patient). A sigmoidal Emax model linking the BIS index with biophase concentration was used to describe the experimental data. This type of model has typically been used in literature to describe various indexes used to monitor the depth of anesthesia [4, 5, 17]. Pharmacological Reports, 212, 64, 113 122 117

Propofol Concentration, mg/l 1 2 Our Model Bjornsson 5 1 15 2 25 3 35 4 1 2 Our Model Peeters 1 2 5 1 15 2 25 3 35 4 Our Model Schnider 5 1 15 2 25 3 35 4 1 2 Our Model Schuttler Fig. 3. The comparison of our model and the literature pharmacokinetic models of propofol (Schnider [19], Bjornsson [5], Schuttler [21], Marsh [13] and Peeters [17]) for a 4-year-old male of 7 kg and 17 cm. The following infusion was used for simulations: initial dose 2 mg/kg, rate of infusion.2 mg/min/kg and duration of infusion 2 min 5 1 15 2 25 3 35 4 1 2 Our Model Marsch 5 1 15 2 25 3 35 4 Time, min 1 5 1 ID: 1 ID: 2 ID: 3 ID: 4 Fig. 4. Plot of observed (open circle), population predicted (dotted line) and individual predicted (solid line) propofol concentrations vs. time for the final PD model 5 Bispectral Index, BIS 1 5 1 ID: 5 ID: 6 ID: 7 ID: 8 5 1 ID: 9 ID: 1 5 5 1 15 2 5 1 15 2 Time, h 118 Pharmacological Reports, 212, 64, 113 122

PK/PD of propofol in aortic surgery patients Pawe³ Wiczling et al. Tab. 2. Summary of the final population PD parameters and inter-subject and residual error variance estimates of propofol Parameter, unit Description Estimate (% CV) Fixed effect Baseline ( ) Baseline BIS score 97 (3.4) Emax ( ) Maximum decrease of BIS from baseline 1 Fixed keo (min -1 ) Rate constant for distribution from effect compartment.24 (36.7) ( ) Shape factor 1 Fixed C5 (mg/l) Effect site concentration needed to reach 5% of E max 2.19 (16.8) Inter-individual variability 2 EC5 (%) Inter-individual variability of EC5 41.7 (37.4) Residual variability 2 add,bis (%) Additive residual error variability 14 (6.8) The propofol BIS index along with model predictions is presented in Figure 4. This plot shows that the final PD model describes the experimental data well. All the estimated PD parameters are listed in Table 2. This baseline BIS value is 97, which corresponds to a fully awake patient. The high biophase drug concentrations were assumed to produce BIS index zero (maximal anesthetic effect). The biophase distribution rare constant equalled.24 min 1. The estimated EC5 (2.19 mg/l) was in agreement with the literature values of 1.98 mg/l for ICU patients [4] and 1.84 mg/l for the patients with Sequential Organ Failure Assessment (SOFA) score equal to 15 [17]. For healthy subjects the EC5 was found to be higher (2.55 mg/l) [5]. The EC5 was the only PD parameter for which it was possible to estimate inter-individual variability (42%). The predicted BIS index changes after standard infusion protocol are given in Figure 5. Interestingly, the BIS index profiles are considerably different for all the presented simulations. The Björnsson model (healthy patients) predicts the lowest, whereas Peeters model the highest BIS values for the same infusion protocol. The BIS values of this study are between the literature model predictions. Taking into consideration the dependence of EC5 on the SOFA physical status in the Peeters model, the worsening of ICU patient conditions from the SOFA index of 3 to 15 changes the EC5 from 4.48 mg/l to 1.84 mg/l. It explains our low EC5 value very well, as the patients in this study were in serious conditions (ASA III). Discussion In this study we demonstrated a population PK and PD model of propofol in patients scheduled for abdominal aortic surgery. This model was compared with existing models, especially those used in TCI devices (Schnider and Marsh model). Since the group of patients is severely ill (ASA III), it is desirable to compare the TCI model predictions, which were based on healthy individuals with the actual experimental data. Intuitively, the propofol models should be different for healthy and ill patients, especially for patients undergoing serious surgical procedures. The literature shows that in ICU, for patients suffering from reduced myocardial contractility, the clearance was slower by as much as 38% in comparison with critically ill patients without heart failure. Simultaneously, the pharmacodynamics of propofol depended on the severity of the patient s state expressed according to the SOFA score [17]. In the case of our study, elimination clearance is higher than the literature data in healthy and ill patients. These results are difficult to explain and might be attributed to the use of an opioid and other co-administered drugs, high blood loss, administration of fluids, etc. Rapid fluid infusion therapy to treat hypovolemia in anesthetized patients is a common practical regimen in daily clinical settings. Adachi et al. [2] studied the effects of rapid fluid infusion Pharmacological Reports, 212, 64, 113 122 119

1 8 6 4 2 Our Model Bjornsson Fig. 5. The comparison of our model and the literature pharmacodynamic models of propofol (Bjornsson [5] and Peeters [17]) for a 4-year-old male of 7 kg and 17 cm. The following infusion was used for simulations: initial dose 2 mg/kg, rate of infusion.2 mg/ min/kg and duration of infusion 2 min. For the Peeters et al. model, profiles of patient with two different Sequential Organ Failure Assessment (SOFA) scores are presented 5 1 15 2 25 3 35 4 BIS 1 8 Our Model Peeters (SOFA = 15) Peeters (SOFA = 3) 6 4 2 5 1 15 2 25 3 35 4 Time, min therapy on propofol concentrations and BIS value during general anesthesia in ASA I and II patients and they found that the rapid infusion therapy significantly decreases propofol concentrations without any changes in the BIS value. Thus, the authors concluded that this phenomenon may be of little clinical importance. However, in contrast to our study, they examined relatively healthy subjects. We assessed the PK and PD of propofol in ASA III patients undergoing abdominal aortic surgery, where large volumes of crystalloid and colloid fluids are continuously infused to the patients. Therefore, these changes may be exacerbated. Adachi et al. [2] found that after fluid infusion therapy both the cardiac output and cardiac index increased. It is known that propofol clearance is flow dependent [16]. Therefore, any increase in the cardiac output may lead to an enhanced elimination process resulting in lower plasma concentrations of this drug. Unfortunately, we did not record the cardiac output in our study, so we are not able to confirm this hypothesis. On the other hand, in the case of pharmacodynamics, the obtained EC5 corresponds very well to the literature values of seriously ill patients and is lower than the one observed in healthy subjects. Thus, lower propofol concentrations, simultaneously with the greater CNS sensitivity to propofol observed in our patients, may compensate each other, leading to no dosing changes required in this group of patients. Our results may therefore partly explain the ones obtained by Adachi et al. [2]. The obtained results suggest that the actual plasma concentrations of propofol are lower than predicted from the Schnider or Marsh model. We used the Diprifusor TCI system in our study, which is based on the Marsh model [13]. The tendency of the TCI system to overestimate the propofol concentrations in plasma was also demonstrated, as shown by the negative bias value (MDPE) obtained in our study. The mean inaccuracy of the TCI system (MDAPE) was estimated at 3.5%. Swinhoe et al. [24] evaluated the MDAPE of the TCI Dipriphusor system in ASA I-III (mainly ASA II) status patients and obtained the value of 24.1%. Thus, the higher error obtained in our study 12 Pharmacological Reports, 212, 64, 113 122

PK/PD of propofol in aortic surgery patients Pawe³ Wiczling et al. may be connected with the disease severity of our patients (all were ASA III status). Another factor which should be taken into account as the cause of high interindividual variability in propofol pharmacokinetics is the polymorphism in genes coding for metabolizing enzymes. Propofol is mainly metabolized by glucuronosyltransferase UGT1A9. The secondary metabolic cascade mediated mainly by CYP2B6 and to lesser extent by CYP2C9 leads to the production of 4-hydroxypropofol that is further metabolized by conjugation. Over 28 variant alleles and several subvariants have been described for CYP2B6 and it appears to be one of the most polymorphic cytochrome P-45 genes in humans. Also, for UGT1A9 gene several polymorphisms including mutations in the gene promoter have been described [15, 18]. Recently it has been demonstrated that D256N mutation lowers UGT1A9 activity for propofol, suggesting that carriers of D256N may be at risk of suffering adverse effects of propofol [25]. Propofol acts by activation of GABAA receptor. Also mutations in the coding genes may potentially be of some importance as far as the inter-patient variability in the pharmacodynamics of propofol is concerned. However, the data in this field are limited. Until now the influence of polymorphism in genes for GABAA on the propofol anesthesia has not been confirmed [9]. The small number of patients used in our study to build a PK model needs to be increased in order to obtain results applicable to a broader population of patients encountered in the clinic. A larger number of patients would give a possibility to build a more comprehensive PK/PD model with various covariates, such as weight, age, gender, genomic data, or health status. A model developed in this way could be used to control the TCI instruments for precise dosage of propofol. To conclude, a population PK/PD model was successfully developed to describe the time course and variability of propofol concentration and BIS index in ASA III patients undergoing aortic surgery. The results suggest that the models currently used in the TCI system should be used with caution, as the real concentration and BIS index might be different than predicted by currently used models. Additional experiments are needed to fully understand the interplay between all factors affecting propofol PK/PD, especially the administration of fluids, the co-administration of other drugs and surgical procedure affecting blood flow through eliminating organs. Acknowledgment: One of the authors (Pawe³ Wiczling) was supported by a grant from Iceland, Liechtenstein, and Norway through the EEA Financial Mechanism via Homing Program from the Foundation for Polish Science. References: 1. 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