Pharmacokinetics of amikacin in intensive care unit patients

Objective: To characterize the population pharmacokinetics of amikacin in intensive care unit (ICU) patients and to analyse whether these patients show different kinetic behaviour on the basis of their clinical diagnoses.
Method: The patient population comprised 104 medical ICU patients on amikacin treatment for several presumed or documented Gram-negative infections. Four study groups were defined according to patients' clinical diagnosis: sepsis group ( n = 39), trauma group ( n = 20), pneumonia group ( n = 21) and 'other diagnosis' group ( n = 24). The pharmacokinetic parameters for amikacin in these patients were then compared.
Results: The ICU patients were found to have increased values for the amikacin volume of distribution (0.52 ± 0.21 litres/kg), whereas total amikacin clearance expressed as a linear function of creatinine clearance was Cl (ml/min/kg)= 0.13 ± 0.86 Cl _CR which is not significantly different from other estimations reported in the literature. However, this relationship revealed statistically significant differences among the four groups of ICU patients. Moreover, the septic and trauma patients showed higher (but not statistically significant) values for the amikacin volume of distribution.
Conclusion: The amikacin pharmacokinetic parameters obtained should allow Bayesian individualization of amikacin doses in patients admitted to medical ICUs, on the basis of their clinical diagnoses.     

Population pharmacokinetics of imipenem in burn patients

The interindividual variability of imipenem pharmacokinetic parameters in burn patients suggest that these parameters have to be estimated with a large number of patients. The aim of this study is (i) to estimate these parameters with a population pharmacokinetic approach, and (ii) to test the influence of factors on pharmacokinetics parameters. Data are provided by therapeutic drug monitoring (n = 47,118 samples) and analysed by a nonlinear mixed effect modelling method. Among the tested covariates (age, gender, body weight, height, size of burn and creatinine plasma level) creatinine plasma level affects imipenem pharmacokinetic parameters substantially. The best fit is obtained with a two-compartment model integrating a linear-inverse relationship between imipenem clearance and creatinine plasma level. The estimates of imipenem clearance (16.37 +/- 0.204 L/h) and of the distribution volume of the central compartment (0.376 +/- 0.039 L/kg) are higher in the population of burn patients than the estimates in healthy subjects. This result is connected with high values of glomerule filtration rate and confirms the interest of therapeutic drug monitoring of imipenem in burn patients and particularly for patients with extreme values of creatinine clearance.     

Population pharmacokinetics of intravenous valproic acid in Korean patients

OBJECTIVE: To determine population-based pharmacokinetic parameters for intravenous valproic acid, and the factors influencing these parameters, in Korean adults. METHODS: Valproic acid concentrations were obtained using a peak and trough sampling scheme for 102 Korean epileptic patients who were not taking concurrent antiepileptic medication. Three hundred and fifty-four serum concentrations were analysed according to a one-compartment model with a mixed effect modelling method (NONMEM Ver 5.0). The influence of body-weight (kg), height, daily valproic acid dose (mg/day), body mass index (kg/m2), sex, and age on volume of distribution (Vd) and clearance (CL) was assessed in the course of analysis. RESULTS: Vd and CL of valproic acid increased with body-weight. No significant influence of the other screened covariates was observed. The final regression model was: [equation: see text]. Interindividual variabilities (coefficient of variation) for CL and Vd were 32 and 18%, respectively. Residual error including intraindividual variability was 26.7%. CONCLUSION: The current results may be used as a basic reference to optimize drug therapy with intravenous valproic acid. Further research on the paediatric population is necessary to confirm the non-linearity of the relation between body-weight and Vd.     

Population pharmacokinetics of intravenous itraconazole in patients with persistent neutropenic fever

Purpose:  Empirical use of intravenous (IV) itraconazole (ITZ) for febrile neutropenic patients has recently been introduced in Korea. This study was designed to investigate the population pharmacokinetics (PK) of IV-ITZ.
Methods:  Sparse PK data were collected from febrile neutropenic patients undergoing empirical ITZ therapy at 200 mg/day after loading doses. NONMEM (Version. 5·1·1) was used to estimate population PK parameters.
Results:  Forty-two patients were enrolled in the study. Mean population CL and V of IV-ITZ were 10 L/h and 1050 L, respectively. Body weight was the only contributing covariate of CL. The median simulated trough concentration of ITZ after 10 days was predicted to be about 700 ng/mL.
Conclusions:  In this study, we explored the population PK profile of ITZ given in IV formulation. We found that the current dosage regimen of IV-ITZ (200 mg/day) was appropriate to obtain therapeutic trough concentrations for neutropenic patients in Korea.     

Phenobarbital in intensive care unit pediatric population: predictive performances of population pharmacokinetic model

An external evaluation of phenobarbital population pharmacokinetic model described by Marsot et al. was performed in pediatric intensive care unit. Model evaluation is an important issue for dose adjustment. This external evaluation should allow confirming the proposed dosage adaptation and extending these recommendations to the entire intensive care pediatric population. External evaluation of phenobarbital published population pharmacokinetic model of Marsot et al. was realized in a new retrospective dataset of 35 patients hospitalized in a pediatric intensive care unit. The published population pharmacokinetic model was implemented in nonmem 7.3. Predictive performance was assessed by quantifying bias and inaccuracy of model prediction. Normalized prediction distribution errors (NPDE) and visual predictive check (VPC) were also evaluated. A total of 35 infants were studied with a mean age of 33.5 weeks (range: 12 days–16 years) and a mean weight of 12.6 kg (range: 2.7–70.0 kg). The model predicted the observed phenobarbital concentrations with a reasonable bias and inaccuracy. The median prediction error was 3.03% (95% CI: ?8.52 to 58.12%), and the median absolute prediction error was 26.20% (95% CI: 13.07–75.59%). No trends in NPDE and VPC were observed. The model previously proposed by Marsot et al. in neonates hospitalized in intensive care unit was externally validated for IV infusion administration. The model‐based dosing regimen was extended in all pediatric intensive care unit to optimize treatment. Due to inter‐ and intravariability in pharmacokinetic model, this dosing regimen should be combined with therapeutic drug monitoring.     

A study of once-daily amikacin with low peak target concentrations in intensive care unit patients: pharmacokinetics and associated outcomes

PURPOSE: The aim of this study was to assess the pharmacokinetics of individualized amikacin single-dosage regimens targeting low peak serum concentrations in a population of intensive care unit (ICU) patients, and to describe the outcomes associated with this dosing strategy. MATERIALS AND METHODS: In this prospective, noncomparative, pharmacokinetic study, 36 ICU patients with adequate renal function were treated with amikacin (intravenous infusion), in combination with other antibiotics, for hospital-acquired infections. The initial doses of amikacin were calculated based on individual creatinine clearance values whereas subsequent doses were calculated by using the amikacin pharmacokinetic parameters estimated from the serum concentration-time data of each individual patient (samples were drawn postinfusion, 1 h, 3 h, 6 h, and 10 h after the onset of the infusion and just before the next dose on days 2, 4, and 7 of therapy). RESULTS: Results showed moderate only interpatient and lack of intrapatient (except for the volume of distribution) variability in amikacin pharmacokinetic parameters. There were no significant differences between achieved and target peak levels. Clinical response was noted in 94% and bacteriologic response was noted in 86% of patients. Nephrotoxicity did not occur during or after treatment. CONCLUSIONS: Amikacin dosage individualization with low peak target concentrations was successful for the 36 ICU patients. This dosing strategy was not associated with nephrotoxicity, but conclusions on clinical efficacy cannot be drawn from this limited study.     

Population pharmacokinetics and metabolism of midazolam in pediatric intensive care patients

OBJECTIVE: To determine the pharmacokinetics and metabolism of midazolam in pediatric intensive care patients. DESIGN: Prospective population pharmacokinetic study. SETTING: Pediatric intensive care unit. PATIENTS: Twenty-one pediatric intensive care patients aged between 2 days and 17 yrs. INTERVENTIONS: The pharmacokinetics of midazolam and metabolites were determined during and after a continuous infusion of midazolam (0.05-0.4 mg/kg/hr) for 3.8 hrs to 25 days administered for conscious sedation. MEASUREMENTS AND MAIN RESULTS: Blood samples were taken at different times during and after midazolam infusion for determination of midazolam, 1-OH-midazolam, and 1-OH-midazolam-glucuronide concentrations via high-performance liquid chromatography-ultraviolet detection. A population analysis was conducted via a two-compartment pharmacokinetic model by the NPEM program. The final population model was used to generate individual Bayesian posterior pharmacokinetic parameter estimates. Total body clearance, apparent volume distribution in terminal phase, and plasma elimination half-life were (mean +/- sd, n = 18): 5.0 +/- 3.9 mL/kg/min, 1.7 +/- 1.1 L/kg, and 5.5 +/- 3.5 hrs, respectively. The mean 1-OH-midazolam/midazolam ratio and (1-OH-midazolam + 1-OH-midazolam-glucuronide)/midazolam ratio were 0.14 +/- 0.21 and 1.4 +/- 1.1, respectively. Data from three patients with renal failure, hepatic failure, and concomitant erythromycin-fentanyl therapy were excluded from the final pharmacokinetic analysis. CONCLUSIONS: We describe population and individual midazolam pharmacokinetic parameter estimates in pediatric intensive care patients by using a population modeling approach. Lower midazolam elimination was observed in comparison to other studies in pediatric intensive care patients, probably as a result of differences in study design and patient differences such as age and disease state. Covariates such as renal failure, hepatic failure, and concomitant administration of CYP3A inhibitors are important predictors of altered midazolam and metabolite pharmacokinetics in pediatric intensive care patients. The derived population model can be useful for future dose optimization and Bayesian individualization.     

Population pharmacokinetics of amikacin in critically ill patients.

The pharmacokinetic parameters of amikacin were determined in a population of 20 adults and 36 pediatric patients admitted into an intensive care unit. Amikacin was administered by repeated intravenous infusion over 0.5 h (600 to 1,350 mg for adults; 70 to 1,500 mg for children). The number of administrations ranged from 2 to 17, and the number of samples collected from each patient ranged from 2 to 70. The population enrolled in the study had large variabilities in age (0.5 to 85 years), weight (6 to 95 kg), height (72 to 187 cm), creatinine clearance rate (18 to 110 ml/min), blood urea nitrogen concentration (1.5 to 15 mmol/liter), and total protein concentration (30 to 91 g/liter). The mean population parameters and their interindividual variabilities were obtained for an initial group of 44 patients (16 adults and 28 children). A two-compartment model was fitted to the population data by using the computer program P-PHARM. Model selection was guided by evaluation of the minimum objective function and the weighted residuals. The population analysis has been performed with the complete set of the collected data, including the individual serum amikacin concentration together with the individual estimate of the creatinine clearance values. The potential sources of variability in the population parameters were investigated by using patients' age, height, weight, creatinine clearance, blood urea nitrogen concentration, and total protein concentration as covariables. A test group of 12 additional patients (4 adults and 8 children) was used to evaluate the predictive performances of the population parameters. The individual pharmacokinetic parameters were computed by a Bayesian fitting procedure. From the resulting individualized values of the parameters, the concentrations of amikacin in the serum of the patients were calculated. To evaluate the performance of the Bayesian estimation, the experimental concentrations were compared with the predicted ones. The Bayesian approached developed in the study accurately predicts amikacin concentrations in serum and allows for the estimation of amikacin pharmacokinetics parameters, minimizing the risk of bias in the prediction. This was demonstrated in patients with both stable and unstable renal functions.     

Population pharmacokinetics of rifampicin in Mexican patients with tuberculosis

What is known and Objective: Rifampicin (RIF) shows wide variability in its pharmacokinetics. The purpose of this study was to develop and validate a population pharmacokinetic model to characterize the inter‐ and intra‐individual variability in pharmacokinetic parameters of RIF in Mexican patients. Methods: Ninety‐four patients receiving antituberculosis therapy participated in this prospective study. Plasma concentration‐time data were described using a one‐compartment model with lag time, absorption and first‐order elimination. The potential influence of demographic and clinical characteristics of the patients, and the pharmaceutical formulation (A, B, C and D) on the pharmacokinetics parameters, was evaluated by non‐linear mixed‐effect modelling (nonmem ). Seventy‐seven additional patients participated in the validation of the model. Results and Discussion: The final population pharmacokinetic model obtained was as follows: apparent clearance CL/F = 8·17 L/h (1·40 as high for males), apparent distribution volume V_d/F = 50·1 L (1·29 as high for males), absorption rate constant K_aA = 0·391/h, K_aB,C,D = 2·70/h, relative bioavailability F_A = 0·468, F_B,C,D = 1, lag time in the absorption phase T_lag = 0·264 h. The final model improved the precision on the parameter estimates (CL/F, V_d/F and K_a by 31·9%, 16·7% and 92·9%, respectively). The residual variability was 27·3%. What is new and Conclusion: Gender was associated with changes in CL/F and V_d/F whereas the pharmaceutical formulation was associated with changes in F and altered the K_a. The validation data set showed that the model could be used in clinical practice for Bayesian dose adjustment of RIF in TB patients.     

Population pharmacokinetics of micafungin in adult patients

We performed population pharmacokinetic analysis of micafungin in adult patients treated with doses between 12.5 and 200 mg/day. Our analysis identified a breakpoint patient weight of 66.3 kg above which serum clearance increased by approximately 50%. Patients with weight >66.3 kg may need larger doses to achieve similar exposures to those <66.3 kg. However, the clinical implications are still unknown.     

Population pharmacokinetics of ABT-594 in subjects with diabetic peripheral neuropathic pain

What is known and Objective:  ABT‐594 is a non‐opioid, non‐NSAID analgesic. The objective of this work was to characterize the population pharmacokinetics of ABT‐594 in subjects with neuropathic pain. Methods:  Efficacy, safety and pharmacokinetics of ABT‐594 in subjects with painful diabetic polyneuropathy were evaluated in a randomized, double‐blind, placebo‐controlled, parallel‐group, multi‐centre, 7‐week Phase 2 study. Subjects (N = 266) were approximately equally divided into four groups to receive BID regimens of placebo or 150, 225 and 300 μg of ABT‐594. ABT‐594 concentrations were determined from all subjects, whereas a subset of subjects provided intensive pharmacokinetic samples on two occasions. One‐ and two‐compartment models were explored for characterizing plasma ABT‐594 concentration–time profiles. The relative importance of covariates (age, weight, body surface area, creatinine clearance, gender, nicotine use and albumin concentrations) was examined by use of the likelihood ratio test. Model building was accomplished using stepwise forward selection (P < 0·05) and backward elimination (P < 0·005) of covariates. Population analyses were performed using NONMEM. Results and Discussion:  Optimal characterization of the plasma concentration data was achieved using a one‐compartment base model. Creatinine clearance and age were found to be significant covariates in the forward selection process; backward elimination process identified only creatinine clearance as a significant covariate. What is new and Conclusion:  A population pharmacokinetic model was developed to characterize ABT‐594 concentrations in subjects with neuropathic pain. As ABT‐594 is primarily eliminated as unchanged drug in the urine, creatinine clearance and age were significant covariates of clearance with creatinine clearance being the optimal predictor of ABT‐594 clearance.     

Population pharmacokinetic study of isepamicin with intensive care unit patients.

The pharmacokinetics (PK) of isepamicin, a new aminoglycoside, were studied in 85 intensive care unit (ICU) patients and were compared with those observed in 10 healthy volunteers. A parametric method based on a nonlinear mixed-effect model was used to assess population PK. Isepamicin was given intravenously over 0.5 h at dosages of 15 mg/kg once daily or 7.5 mg/kg twice daily. The data were fitted to a bicompartmental open model. Compared with healthy volunteers, the mean values of the PK parameters were profoundly modified in ICU patients: elimination clearance was reduced by 48%, the volume of distribution in the central compartment (Vc) was increased by 50%, the peripheral volume of distribution was 70% higher, the distribution clearance was 146% lower, and the elimination half-life was ca. 3.4 times higher. The interindividual variability in PK parameters was about 50% in ICU patients. Five covariates (body weight [BW], simplified acute physiology score [SAPS], temperature, serum creatinine level, and creatinine clearance [CLCR]) were tentatively correlated with PK parameters by multivariate linear regression analysis with stepwise addition and deletion. The variability of isepamicin clearance was explained by three covariates (BW, SAPS, and CLCR), that of Vc was explained by BW and SAPS, and that of the elimination half-life was explained by CLCR and SAPS. Simulation of the concentration-versus-time profile for 500 individuals showed that the mean peak (0.75 h) concentration was 18% lower in ICU patients than in healthy volunteers and that the range in ICU patients was very broad (28.4 to 95.4 mg/liter). Therefore, monitoring of the isepamicin concentration is in ICU patients is mandatory.     

Population pharmacokinetic modelling of carbamazepine by using the iterative Bayesian (IT2B) and the nonparametric EM (NPEM) algorithms: implications for dosage

OBJECTIVE: To estimate individual and population postinduction pharmacokinetics of carbamazepine (CBZ) in epileptic adult and paediatric patients who received chronic CBZ monotherapy. METHODS: We have used the USC*PACK collection of PC programs for the estimations. The preinduction CBZ metabolism was also estimated in 16 volunteers after a single dose of CBZ (200 mg). We used a linear one-compartmental model with oral absorption and found the pharmacokinetic parameter values of CBZ behaviour to be in good agreement with those reported earlier. RESULTS: Serum CBZ concentrations correlated poorly with daily doses in both the adult and child populations. Because of the diversity within the population, use of the mean population model without knowledge of an individual patient's pharmacokinetic characteristics gives poor prediction. In contrast, the individual Bayesian posterior models gave good prediction for all subjects in the population, due to the removal of the interindividual variability. CONCLUSION: This approach permits one to individualize drug therapy for patients even when only sparse therapeutic drug monitoring (TDM) data are available. Future individual CBZ serum level predictions were acceptable from a clinical point of view (mean absolute error = 13.2 +/- 9.7%). The optimal sampling strategy approach helped to design an optimal cost-effective TDM protocol for CBZ therapy management.     

Population pharmacokinetics of cefepime in neonates with severe nosocomial infections

Objective: To define the pharmacokinetic behaviour of cefepime in neonates with severe nosocomial infections using a mixed effects model. Patients and methods: Thirty‐one newborn infants were included in the study; 10 additional infants participated in the validation of the pharmacokinetic model. Cefepime CL and V were determined using an open monocompartmental model with first‐order elimination. The influence of demographic and clinical characteristics on the model was evaluated. The non‐linear mixed effect model (nonmem ) program was used to determine the pharmacokinetic population model. Results: The mean corrected gestational age for infants participating in the construction and validation of the model were 35 and 33 weeks, respectively. Factors included in the final pharmacokinetic model were body surface area (BSA) and calculated CL_CR. The final population model was CL (L/h) = 0·457 BSA (m²) + 0·243 CL_CR (L/h) and V(L) = 4·12 BSA (m²). This model explains 33·3% of the interindividual variability for CL and 12·8% for V. This model was validated in ten neonates with nosocomial infections by assessing the predictive capacity of plasma cefepime concentrations using a priori and Bayesian strategies. Conclusions: The predictive performance of this population model for cefepime plasma concentrations was adequate for clinical purposes and can be used for individualizing cefepime therapy in newborn infants with severe infections. Cefepime plasma concentrations can be predicted based on BSA and calculated CL_CR. Cefepime therapy using a 250 mg/m² dose administered every 12 h is adequate to achieve plasma concentrations greater than 8 μg/mL during more than 60% of the dosing interval and is expected to be effective in the treatment of bloodstream infections caused by most gram negative organisms in newborn infants. A dose of 550 mg/m² would be required for the treatment of infections caused by Pseudomonas sp.     

Population pharmacokinetics and pharmacodynamics of biapenem in paediatric patients

Objective: To develop a population pharmacokinetic model for biapenem in paediatric patients and to use the parameter estimates to assess pharmacodynamic exposure of common bacterial populations. Methods: Biapenem plasma concentrations (n = 125) from 25 paediatric patients were analysed using nonmem . The parameter estimates were used in a Monte Carlo simulation to predict the exposure time during which the drug concentration remains above the minimum inhibitory concentration. Results: A two‐compartment model fitted the data, and creatinine clearance (CL_cr) and total body weight (TBW) were the most significant covariates. The final model was CL (L/h) = 0·0458 × CL_cr, V_c (L) = 0·162 × TBW, Q (L/h) = 2·05, V_p (L) = 1·73, where CL is the clearance, V_c is the volume of distribution of the central compartment, Q is the intercompartmental clearance and V_p is the volume of distribution of the peripheral compartment. Biapenem regimens of 5 mg/kg q8h and 10 mg/kg q8h provided sufficient pharmacodynamic exposures to Pseudomonas aeruginosa and Streptococcus pneumoniae in most typical patient populations. Conclusion: These results better define the pharmacokinetics of biapenem and help in the choice of the appropriate dosage regimens for paediatric.     

Population pharmacokinetics of oral baclofen at steady‐state in alcoholic‐dependent adult patients

Baclofen has been proposed for few years to help treating alcohol dependence at higher doses than those used in neurology. Baclofen pharmacokinetics has been previously well described at low oral or intravenous doses but remains poorly investigated with such high oral doses. We here describe dose regimens of baclofen in 143 alcohol‐dependent patients treated with steady‐state oral doses of baclofen. Plasma baclofen levels were measured in blood samples using liquid chromatography coupled with tandem mass spectrometry. One hundred and forty‐nine baclofen concentrations were sampled 30 min to 15 h after the last dose, and baclofen pharmacokinetics was determined using population pharmacokinetics approach. Our population, whose average age and BMI were 51.5 years and 25.5 kg/m², respectively, was composed of two‐thirds of men. Daily baclofen doses ranged from 15 to 250 mg and 26% were higher than 120 mg. A one‐compartment model with first‐order absorption and elimination allowed to determine mean values for clearance (CL/F), volume of distribution (V/F) and absorption rate constant at 8.0 L/h, 44.5 L and 2.23 h^?1, respectively. Inter‐individual variability on CL/F and V/F was 27.4 and 86% for the parameters. None of the demographic and biological covariates significantly decreased inter‐individual variability. A proportional relationship between oral dose and plasma baclofen exposure indicated a linear pharmacokinetics of baclofen even at doses over 120 mg/day. Our large population study evidenced a linear pharmacokinetics of oral baclofen even at high daily doses with an inter‐individual variability of baclofen exposure that could not be explained by demographic and biological data.     

Population pharmacokinetics of fluconazole after administration of fosfluconazole and fluconazole in critically ill patients

What is known and Objective: Fluconazole is an antifungal agent that is commonly used to treat patients with serious systemic fungal infections in intensive care units. Fosfluconazole is a phosphate prodrug of fluconazole, which was developed to reduce the volume of fluid required to administer fluconazole by intravenous injection. The objective of this study was to characterize the pharmacokinetics of the antifungal fluconazole after the intravenous administration of the prodrug fosfluconazole or fluconazole in critically ill patients with serious systemic fungal infections, by population pharmacokinetic analysis using the nonmem software package. Methods: Clinical biochemical data including serum fluconazole levels were obtained from 57 patients treated in the intensive care unit along with two naïve pooled patients gleaned from previous reports. The pharmacokinetic model of fluconazole was estimated using a one‐compartment model. The probability that the area under the concentration–time curve is higher than 800 μg h/mL was determined by simulation. Results: It was assumed that all the administered fosfluconazole was converted to fluconazole with an estimated fosfluconazole‐fluconazole conversion rate constant of 2·05/h. The significant covariates for clearance for fluconazole (CL) and volume of distribution for fluconazole (Vd) were resulted in creatinine clearance (CLcr) and body weight (BW), respectively, in the final pharmacokinetic model equations: CL (L/h) = 0·799 × [CLcr (mL/min)/92·7]^0·685 and Vd (L) = 48·1 × [BW (kg)/65]^1·40, where the interpatient variabilities in CL and Vd and the intrapatient variability were 44·8%, 79·7% and 19·8%, respectively. On the basis of the results of the Monte Carlo simulation, the probabilities of target attainment were 60%, 26% and 11% for 400 mg/day administration as fluconazole equivalent at CLcr values of 40, 70 and 100 mL/min, respectively. What is new and Conclusion: The present population pharmacokinetic analysis strongly indicates that fosfluconazole (and fluconazole) dosage should be optimized in terms of CLcr in critically ill patients.