Population pharmacokinetics of gentamicin. Use of the nonparametric expectation maximisation (NPEM) algorithm

Aminoglycosides in the Intensive Care Unit: What Is New in Population PK Modeling?

Background: Although aminoglycosides are often used as treatment for Gram-negative infections, optimal dosing regimens remain unclear, especially in ICU patients. This is due to a large between- and within-subject variability in the aminoglycoside pharmacokinetics in this population. Objective: This review provides comprehensive data on the pharmacokinetics of aminoglycosides in patients hospitalized in the ICU by summarizing all published PopPK models in ICU patients for amikacin, gentamicin, and tobramycin. The objective was to determine the presence of a consensus on the structural model used, significant covariates included, and therapeutic targets considered during dosing regimen simulations. Method: A literature search was conducted in the Medline/PubMed database, using the terms: ‘amikacin’, ‘gentamicin’, ‘tobramycin’, ‘pharmacokinetic(s)’, ‘nonlinear mixed effect’, ‘population’, ‘intensive care’, and ‘critically ill’. Results: Nineteen articles were retained where amikacin, gentamicin, and tobramycin pharmacokinetics were described in six, 11, and five models, respectively. A two-compartment model was used to describe amikacin and tobramycin pharmacokinetics, whereas a one-compartment model majorly described gentamicin pharmacokinetics. The most recurrent significant covariates were renal clearance and bodyweight. Across all aminoglycosides, mean interindividual variability in clearance and volume of distribution were 41.6% and 22.0%, respectively. A common consensus for an optimal dosing regimen for each aminoglycoside was not reached. Conclusions: This review showed models developed for amikacin, from 2015 until now, and for gentamicin and tobramycin from the past decades. Despite the growing challenges of external evaluation, the latter should be more considered during model development. Further research including new covariates, additional simulated dosing regimens, and external validation should be considered to better understand aminoglycoside pharmacokinetics in ICU patients.

Limited-sampling strategies for anti-infective agents: systematic review

BACKGROUND

Area under the concentration-time curve (AUC) is a pharmacokinetic parameter that represents overall exposure to a drug. For selected anti-infective agents, pharmacokinetic-pharmacodynamic parameters, such as AUC/MIC (where MIC is the minimal inhibitory concentration), have been correlated with outcome in a few studies. A limited-sampling strategy may be used to estimate pharmacokinetic parameters such as AUC, without the frequent, costly, and inconvenient blood sampling that would be required to directly calculate the AUC.

OBJECTIVE

To discuss, by means of a systematic review, the strengths, limitations, and clinical implications of published studies involving a limited-sampling strategy for anti-infective agents and to propose improvements in methodology for future studies.

METHODS

The PubMed and EMBASE databases were searched using the terms "anti-infective agents", "limited sampling", "optimal sampling", "sparse sampling", "AUC monitoring", "abbreviated AUC", "abbreviated sampling", and "Bayesian". The reference lists of retrieved articles were searched manually. Included studies were classified according to modified criteria from the US Preventive Services Task Force.

RESULTS

Twenty studies met the inclusion criteria. Six of the studies (involving didanosine, zidovudine, nevirapine, ciprofloxacin, efavirenz, and nelfinavir) were classified as providing level I evidence, 4 studies (involving vancomycin, didanosine, lamivudine, and lopinavir-ritonavir) provided level II-1 evidence, 2 studies (involving saquinavir and ceftazidime) provided level II-2 evidence, and 8 studies (involving ciprofloxacin, nelfinavir, vancomycin, ceftazidime, ganciclovir, pyrazinamide, meropenem, and alpha interferon) provided level III evidence. All of the studies providing level I evidence used prospectively collected data and proper validation procedures with separate, randomly selected index and validation groups. However, most of the included studies did not provide an adequate description of the methods or the characteristics of included patients, which limited their generalizability.

CONCLUSIONS

Many limited-sampling strategies have been developed for anti-infective agents that do not have a clearly established link between AUC and clinical outcomes in humans. Future studies should first determine if there is an association between AUC monitoring and clinical outcomes. Thereafter, it may be worthwhile to prospectively develop and validate a limited-sampling strategy for the particular anti-infective agent in a similar population.

Gentamicin dosing for pediatric patients with congenital heart disease

Pediatric patients with congenital heart disease can have physiologies that alter the pharmacokinetics of certain medications, such as aminoglycosides. Currently, no literature describes the appropriate dosing of aminoglycoside antibiotics for infants and children with congenital heart disease. Patients were identified through the pharmacy and laboratory computer systems. Patients were included in the study if they were younger than 18 years, received gentamicin on the acute-care (nonintensive care) cardiology floor at the authors' institution, had structural congenital heart disease, and had a peak and trough level obtained at about the third dose or later. Cohort achievement of therapeutic peak and trough concentrations based on standard dosing guidelines was evaluated. The inclusion criteria were met by 48 patients (31 boys). Eight patients (17%) had baseline cyanosis. Cardiac surgery was performed for 23 patients (48%) during the same admission at which aminoglycoside therapy was initiated. A total of 27 patients (56%) received at least one other nephrotoxic medication at the time of aminoglycoside therapy. Six patients had undetectable serum trough levels. A therapeutic peak concentration was not achieved by 16.7% of the cohort, and 7.1% of the cohort did not achieve a therapeutic trough concentration. Pediatric patients with congenital heart disease may require alterations in gentamicin dosing. Close pharmacokinetic monitoring of aminoglycoside therapy for these patients is warranted to ensure attainment of goal concentrations.

Population pharmacokinetic modelling of repaglinide in healthy volunteers by using Non-Parametric Adaptive Grid Algorithm

OBJECTIVE

To estimate population pharmacokinetic parameters of repaglinide in 121 healthy Malaysian volunteers.

METHODS

Each subject received 4 mg of oral repaglinide. Six blood samples were taken per individual (0, 30, 60, 120, 180 and 240 min) for repaglinide's serum concentration determination by using high-performance liquid chromatography. The parametric Iterative Two-Stage Bayesian Population Model (it2b) program followed by the Non-Parametric Adaptive Grid (npag) program was used to determine a population pharmacokinetic modelling of repaglinide.

RESULTS

Using the npag program, the mean elimination rate constant (k(el)) of repaglinide was 0.58 +/- 0.27 h and the volume of distribution (V(d)) was 23.09 +/- 9.19 L/h.

CONCLUSION

In this first report, specifically on the population pharmacokinetic modelling of repaglinide, the data generated should help us to better understand appropriate dosage-regimens for the drug.

Administration of Tobramycin in the Beginning of the Hemodialysis Session: A Novel Intradialytic Dosing Regimen

BACKGROUND

Aminoglycoside antibiotic efficacy is related to peak concentration (C(max)) and postantibiotic effect, whereas toxicity is directly related to body exposure as measured by area under the serum concentration versus time curve (AUC). On the basis of pharmacokinetic simulation models, tobramycin administration during the first 30 min of high-flux hemodialysis achieves similar C(max) but significantly lower AUC and prehemodialysis concentrations compared with conventional dosing in the last 30 min of hemodialysis.

DESIGN, SETTING, PARTICIPANTS, AND MEASUREMENTS

To test this hypothesis, a pilot study in which five adult chronic hemodialysis patients who were undergoing high-flux dialysis received one dose of tobramycin 1.5 mg/kg intravenously during the first or last 30 min of hemodialysis was conducted. After a 1-mo washout period, patients crossed over to the other treatment schedule. Tobramycin serum concentrations were measured to determine C(max), interdialytic and intradialytic elimination rate constants and half-lives, AUC, and clearance.

RESULTS

Tobramycin administration during the first and last 30 min of hemodialysis resulted in similar C(max) of 5.63 +/- 0.49 and 5.83 +/- 0.67 mg/L (P > 0.05) but significantly lower prehemodialysis concentrations of 0.16 +/- 0.09 and 2.44 +/- 0.43 mg/L (P < 0.001) and AUC of 21.06 and 179.23 +/- 25.84 mg/h per L (P < 0.001), respectively.

CONCLUSIONS

Tobramycin administration during the first 30 min of hemodialysis results in similar C(max) but lower AUC to conventional dosing, which may translate into comparable efficacy but lower toxicity.

Population pharmacokinetics II: estimation methods

OBJECTIVE

To present, compare, and contrast the various approaches to estimating population pharmacokinetic (PPK) models with respect to the mathematical foundation, statistical aspects, software programs for implementation, and underlying assumptions.

DATA SOURCES

Information on PPK was retrieved from a MEDLINE search (1977-August 2004) of literature and a bibliographic review of review articles and books. This information is used in conjunction with experience to explain the various methodologic approaches to PPK.

STUDY SELECTION AND DATA EXTRACTION

All articles indentified from data sources were evaluated and relevant information was included in this review.

DATA SYNTHESIS

Over 80 articles dealing with PPK estimation methods and/or their implementation were identified and reviewed. Sixty-four of these were chosen for their direct relevance to the subject of this article. Different estimation methods ranging from the naive averaging and naive pooled approaches through the standard two-stage approach to the nonlinear mixed-effects modeling approaches for estimating PPK are reviewed with their advantages and limitations.

CONCLUSIONS

PPK estimation methods that rely on the characterizing of mixed (fixed and random) effects are known to produce PPK parameter estimates that are less biased than those obtained using the naive and standard two-stage approaches. The NONMEM software is the most widely used software for the characterization of PPK.

Bayesian Pharmacokinetics of Gentamicin in a Haemodialysis Population

BACKGROUND

Aminoglycosides are commonly used in the haemodialysis population. Standard pharmacokinetic approaches require multiple sampling to describe the parameters of drug distribution and elimination in the intra- and interdialytic periods.

OBJECTIVE

To characterise the pharmacokinetics of gentamicin in a haemodialysis population by using Bayesian pharmacokinetic methods and only two plasma concentrations.

DESIGN AND PARTICIPANTS

Prospective case series of 13 adult (aged 36-70 years) haemodialysis patients (Fresenius F80 dialysers were used) receiving gentamicin.

METHODS

Patients with suspected or confirmed Gram-negative infections were given gentamicin. At 48 hours after receiving the dose (at the next haemodialysis session), patients provided two blood samples, one immediately before the dialysis session and another 1 hour after haemodialysis. Data on dosage, timing and plasma concentrations for all subjects were analysed with PASTRX version 10.6 and Bayesian pharmacokinetic analysis. Volume of distribution (Vd), interdialytic elimination rate constant (k(inter)), interdialytic elimination half-life (t1/2beta, inter)) and interdialytic clearance (CL(inter)) were determined from a single predialysis plasma concentration. Elimination rate constant (k(dial)), elimination half-life (t1/2beta, dial)) and clearance (CL(dial)) during 3.5-4 hours of dialysis were also determined from the pre- and post-plasma concentrations.

RESULTS

Pharmacokinetic parameters (mean +/- SD) were: Vd 0.288 +/- 0.002 L/kg, k(inter) 0.015 +/- 0.004h(-1), t1/2beta, inter) 48 +/- 11h, CL(inter) 5.9 +/- 2.4 mL/min, k(dial) 0.25 +/- 0.05 h(-1), t1/2beta, dial) 3.0 +/- 1.0h and CL(dial) 91 +/- 24 mL/min.

CONCLUSIONS

The rate of elimination of gentamicin was 17-fold greater (95% CI 13.7-20.7) on haemodialysis with a Fresenius F80 than off haemodialysis. All of the pharmacokinetic parameters of interest were determined using Bayesian pharmacokinetic procedures and only two plasma gentamicin concentrations.

Mixed effects modeling of the disposition of gentamicin across domestic animal species

An interspecies pharmacokinetic model for gentamicin was developed using the mixed effects modeling approach and serum disposition data obtained from the Food Animal Residue Avoidance Databank (FARAD). Data that met a priori quality criteria was obtained from the database and analysed using the traditional double logarithmic analysis and the mixed effects modeling approach. Body weight, brain weight and fever were the covariates of interest in our study. Population pharmacokinetic models across species were developed and validated with swine data. The parameter volume of distribution was modeled as a function of body weight. The total clearance was initially modeled as a function of body weight. The predictability performance of the model improved dramatically when the parameter brain weight was included in the covariate model for clearance. This was a surprising finding worthy of further study. The covariate fever seemed to influence the magnitude of the volume of distribution, although the scarcity of data pertaining to diseased animals makes this finding uncertain. We conclude that the pharmacokinetic characteristics of drugs such as gentamicin, can be predicted across species using a population pharmacokinetics modeling approach, and that clinical features that affect species in a similar manner can be also explored in this fashion.

Population pharmacokinetics of flucytosine: comparison and validation of three models using STS, NPEM, and NONMEM

The objective of this study is to compare and validate three models of flucytosine (5-FC) population pharmacokinetics using three methods of analysis to elucidate which model describes 5-FC pharmacokinetics most accurately and which method is the most suitable for this purpose. Retrospectively, demographic and clinical data of two similar sets of a total of 88 intensive care unit (ICU) patients were gathered for calculation and validation of 5-FC pharmacokinetics respectively. Three pharmacokinetic models were analyzed: a one-compartment with renal elimination (renal model), a one-compartment with renal and metabolic elimination (mixed model), and a two-compartment with renal elimination (two-compartment model). Population pharmacokinetic parameters were calculated using the standard two-stage method (STS), NONMEM, and NPEM. Furthermore, a covariate model was built by NONMEM. Validation of the 10 calculated pharmacokinetic models showed that NONMEM is most suitable for predicting 5-FC population pharmacokinetics. Based upon AIC values, bias and precision, the best results are obtained using a two-compartment model with renal elimination (k(elr) = 0.000858 +/- 0.000143 l/h per mL per min, k12 = 0.0313 +/- 0.0168 h(-1), k21 = 0.0353 +/- 0.0145 h(-1), and Vd = 0.541 +/- 0.084 L/kg; bias = -13.16; 95% CI = -16.77; -9.55; precision = 30.50; 95% CI = 27.47; 33.26) or a two-compartment covariate model as built by NONMEM [Vd (L) = 0.572 x WT, Cl(5FC) (L/h) = 1.69 + 0.0273 x (Cl(cr) (mL/min) - 52.5), k12 = 0.0235 +/- 0.0107 h(-1), and k21 = 0.0375 +/- 0.0147 h(-1); bias = -8.29; 95% CI = -11.63; -4.95; precision = 26.77; 95% CI = 24.24; 29.07]. In conclusion, this study shows that a two-compartment model with renal elimination best describes 5-FC population pharmacokinetics and NONMEM is able to build a two-compartment covariate model that predicts 5-FC levels equally well in our population of ICU patients. Furthermore, NONMEM appeared to be the most suitable method of population pharmacokinetics in our population and for this purpose it offers more reliable and accurate results than NPEM or the STS method.

Population pharmacokinetics in veterinary medicine: potential use for therapeutic drug monitoring and prediction of tissue residues

Population pharmacokinetics can be defined as a study of the basic features of drug disposition in a population, accounting for the influence of diverse pathophysiological factors on pharmacokinetics, and explicitly estimating the magnitude of the interindividual and intraindividual variability. It is used to identify subpopulations of individuals that may present with differences in drug kinetics or in kinetic/dynamic responses. Rooted in procedures used in engineering systems, population pharmacokinetics methods were conceived as a means to determine the pharmacokinetic profile in populations in which a sparse number of samples were obtained per individual, such as those in late stage human clinical trials. This is the situation commonly encountered in all aspects of veterinary medicine. The exploratory nature of this technique allows one to probe relationships between clinical factors (such as age, gender, renal function, etc.) and drug disposition and/or effect. Similarly, the utilization of these techniques in the clinical research phases of drug development optimize the determination of efficacy and safety of drugs. Given the observational nature of most studies published so far, statistical methods to validate the population models are necessary. Simulation studies may be conducted to explore data collection designs that maximize information yield with a minimum expenditure of resources. The breadth of this approach has allowed population studies to be more commonly employed in all areas of drug therapy and clinical research. Finally, in veterinary medicine, there is an additional field in which population studies are potentially ideally suited: the application of this methodology to the study of tissue drug depletion and drug residues in production animals, and the establishment of withdrawal times tailored to the clinical or production conditions of populations or individuals. Such application would provide a major step toward assuring a safe food supply under a wide variety of dose and off-label clinical uses. Population pharmacokinetics is an ideal method for generating data in support of the implementation of flexible labelling policies and extralabel drug use recently approved under AMDUCA (Animal Medicinal Drug Use Clarification Act. 21 CFR Part 530).

Population pharmacokinetic parameters of gentamicin in patients with solid tumors: estimation by one- and two-stage methods

Gentamicin monitoring has been improved with the introduction of Bayesian methods but the usefulness depends on the quality of the population parameters (PP) used. The objective of this study was to determine PP of gentamicin in patients with solid tumors. A total of 198 adult patients with cancer were included in the analysis. Population parameters were estimated by both a two-stage and a one-stage method (NPEM, Non Parametric Expectation Maximization). Individual parameters (IP) were estimated by the Sawchuk-Zaske method and by nonlinear regression. The estimated distribution volume and clearance of gentamicin (mean +/- SD) were 18.37 +/- 5.021 (0.30-0.32 l/kg of dosing weight) and 3.34 +/- 1.6 l/h, respectively. No significant differences between IP or PP obtained by the different methods were found. The results indicated a wide variability of gentamicin pharmacokinetics making monitoring necessary and that patients with solid tumors may have larger gentamicin volume and slower clearance than normal patients. These observations imply that different population pharmacokinetic parameters should be used for this group of patients.

The CYP2D6 genotype predicts the oral clearance of the neuroleptic agents perphenazine and zuclopenthixol

BACKGROUND

Most antidepressant and neuroleptic agents are metabolized by the polymorphic cytochrome P450 enzyme CYP2D6. This study evaluates the importance of the CYP2D6 genotype for the disposition of the neuroleptic agents perphenazine and zuclopenthixol.

METHODS

Patients treated with neuroleptic agents (n = 36) were studied prospectively with regard to CYP2D6 genotype and neuroleptic plasma concentration during oral treatment. Because no patient provided enough samples for individual kinetic modeling, a bayesian approach was used for determination of the clearance. Population kinetic parameters for this procedure were collected from retrospective therapeutic drug monitoring data (n = 113) by use of a nonparametric approach.

RESULTS

The CYP2D6 genotype significantly predicted the oral clearance of perphenazine and zuclopenthixol (p < 0.01 by multiple regression). The difference in clearance between homozygous extensive metabolizers and poor metabolizers was threefold for perphenazine and twofold for zuclopenthixol.

CONCLUSION

The results show that the genotype for CYP2D6 is closely related to the oral clearances of perphenazine and zuclopenthixol. If this finding can be confirmed in a larger population, genotyping may become an important tool for the dosing of these two neuroleptic agents.

Population pharmacokinetics of amikacin in intensive care unit patients studied by NPEM algorithm

The population pharmacokinetics of amikacin was studied in 40 intensive care unit patients (212 plasma concentrations) by NPEM algorithm using a one-compartment model. The population was best characterized by the following pharmacokinetic parameters: renal clearance relative to creatinine clearance (Cs = 0.96 +/- 0.33), and either the total volume of distribution (Vd = 23.9 +/- 7.0 l) or the volume of distribution relative to body weight (Vs = 0.36 +/- 0.10 l.kg-1. The volume of distribution was increased with respect to the usual value of 0.25 l.kg-1. The statistical distribution of these pharmacokinetic parameters was approximately gaussian, with no significant correlation between volume of distribution and clearance. The medians and standard deviations of Cs and Vs were used as reference population values to estimate the pharmacokinetics of amikacin in a second group of 29 patients by the bayesian method, with two blood samples per patient. For each patient, the fitted parameters were able to predict the plasma concentrations of amikacin during the next 72 h with no significant bias and good precision (2.9 mg.l-1 for peaks and 0.5 mg.l-1 for troughs). This study confirms the ability of the NPEM algorithm to provide reference population values for use in bayesian monitoring of aminoglycoside therapy.

NM-Win: a personal computer-based Microsoft Windows front-end to NONMEM IV

A Microsoft Windows-based front-end, NM-Win, has been written to provide a more user-friendly environment to do nonlinear mixed effect modeling with the NONMEM program. NM-Win utilizes an object-oriented interface design which allows users to view and edit control, PRED, and/or data files using Windows Notepad. In addition, calls made to the Microsoft FORTRAN compiler and linker which generate the final NONMEN executable are performed simply by clicking the "Run NONMEN" button. During the executive step, interactions can be viewed in a window to check the progress of the run. Errors encountered while NONMEN or NM-TRAN is running are brought to a window for ease in debugging. Advanced options allow the user the flexibility of compiling user-written PRED files and creating linker response files. While the PC platform is not optimal for large data set or complex models, it does permit easier debugging and offers multitasking while Windows is running.

Selection of optimal prophylactic aminoglycoside dosage in cancer patients: population pharmacokinetic approaches

We report an alternative dose-finding approach for the selection of optimal prophylactic aminoglycoside dosage in specific (sub)populations of patients. Relative a priori utility of several intervals of gentamicin or tobramycin (AMG) peak and trough serum levels were assigned by a group of pharmacokinetics experts, assuming prophylactic administration for laryngectomy interventions. A group of 27 adult patients, with normal renal function, undergoing elective surgery for laryngeal problems and treated prophylactically with gentamicin (80 mg t.i.d.) or tobramycin (100 mg t.i.d.) was studied. Two blood samples (peak and trough) were drawn at steady-state for AMG assay. Three different methods, standard two-stage (STS), extended least-squares non-linear regression [MULTI(ELS)] and non-parametric expected maximization (NEPM), were used to estimate the pharmacokinetic (PK) population parameters. PK simulations were applied to estimate the AMG steady-state concentrations from the PK population parameters. From these data, relative utility values were calculated, allowing the selection of the optimal dosage schedule for this group of patients. There were no statistically significant differences between the PK population estimates as generated by the three methods. Using the STS estimates, the simulation of several dosages indicated that the optimal dosage is 170 mg every 8 h. Conversely, using the individual PK parameters and the mean AMG levels simulated from them, the dose with best relative utility is 130 mg every 8 h. This important difference points out the relevance of the use of relative utilities for the AMG serum concentrations in the selection of optimal a priori dosage. We propose the use of 120 mg every 8 h as the safer dose for our population. Further studies are needed to validate this proposal in patients similar to ours.

Nonparametric approach to population pharmacokinetics in oncology patients receiving aminoglycoside therapy

A nonparametric expectation maximization approach to the study of population pharmacokinetics is described for an aminoglycoside antibiotic. The method is used to explore population estimates for gentamicin clearance (liters per hour per creatinine clearance) and volume of distribution (liters per kilogram) in tumor patients. Joint and marginal probability distributions are plotted and further characterized by using standard descriptors such as mean, median, mode, standard deviation, skewness, and kurtosis. Results of additional analyses using hematologic or solid tumor subpopulations agree with those of a recent larger study which found no significant pharmacokinetic differences between these groups. Nonparametric maximum-expectation analyses are convenient and allow exploratory analysis of population estimates directly from routine laboratory information.

Population pharmacokinetics: development of a medical intensive care unit-specific gentamicin dosing nomogram

OBJECTIVE

This study was designed to develop a population-specific dosing nomogram for gentamicin in medical intensive care unit (MICU) patients using the population pharmacokinetic program nonparametric expectation maximization (NPEM).

DESIGN

Observational clinical gentamicin dosing data were collected, entered into the USC*PACK database program PASTRX, and downloaded into the population pharmacokinetic program NPEM. NPEM generated population pharmacokinetic parameter values that were used to develop a gentamicin dosing nomogram. The nomogram was tested in the next 15 patients admitted to MICU to determine accuracy. Doses given per the MICU and the Hull-Sarubbi nomograms were compared with doses based on actual patient-specific pharmacokinetic parameter values. Reliability coefficients (intraclass correlation coefficients) were calculated to assess the agreement between observations.

SETTING

Data were gathered from patients receiving gentamicin therapy in the MICU, Presbyterian University Hospital, Pittsburgh.

PATIENTS

Baseline population pharmacokinetic parameter values were determined in 36 MICU patients receiving gentamicin therapy. Patients with renal failure receiving hemodialysis or another mechanical method of blood clearance or fluid removal were excluded. The population parameter values in the form of a dosing nomogram were then used prospectively to dose gentamicin in 15 patients.

RESULTS

NPEM generated population parameter values similar to those previously published using the Sawchuk-Zaske method in ICU patients. The mean volume of distribution generated using NPEM was 0.34 +/- 0.12 L/kg. The relationship between creatinine clearance (Clcr) and elimination rate constant (Ke) was: Ke = 0.00218 x Clcr + 0.007. The nomogram-derived doses correlated with doses determined by using actual patient-specific pharmacokinetic values (p < 0.05). The Hull-Sarubbi derived doses, however, did not correlate with patient-specific doses (p > 0.05). Only one patient had a peak concentration < 6 mg/L. Two of 15 patients had trough concentrations prior to the first maintenance dose > 2 mg/L.

CONCLUSIONS

The use of NPEM to generate population-specific pharmacokinetic parameter values has been previously described. Application of population-specific dosing nomograms can improve initial dosing regimens such that conventional therapeutic concentrations can be achieved early in therapy. This nomogram, however, does not preclude follow-up patient-specific pharmacokinetic analysis.

Comparison of population pharmacokinetic models for gentamicin in spinal cord-injured and able-bodied patients

Population pharmacokinetic models for gentamicin were developed by using data obtained from 29 spinal cord-injured patients and 11 able-bodied control patients. With a one-compartment model, the population parameters were clearance (CL), volume of distribution (V), and their associated variances. Parameter estimates were found by using the computer program NPEM and by the standard two-stage (STS) method. NPEM uses a nonparametric approach incorporating the expectation maximization algorithm to evaluate a joint probability density function at 900 intersections over a bivariate grid. In contrast, the STS method requires conventional assumptions of normality for the underlying distributions. For NPEM, the mean CL was 97.6 ml/h/kg of body weight (coefficient of variation, 33.0% in the spinal cord-injured patients and 67.8 ml/h/kg +/- 28.2% in the able-bodied patients; the mean V was 0.31 liter/kg +/- 32.3% in the spinal cord-injured patients and 0.23 liter/kg +/- 15.8% in the able-bodied patients. For STS, the mean CL was 101.0 ml/h/kg +/- 37.5% in the spinal cord-injured patients and 65.0 ml/h/kg +/- 33.8% in the able-bodied patients; the mean V was 0.29 liter/kg +/- 34.0% in the spinal cord-injured patients and 0.21 liter/kg +/- 21.0% in the able-bodied patients. Although the means and variances found by NPEM and the STS method were similar, the NPEM analysis revealed that the distributions of CL and V, even after they were linked to weight, were positively skewed and kurtotic. The cumulative distribution functions for CL (P < 0.001) and V (P < 0.001) in spinal cord-injured patients were different from those in able-bodied patients. Unique population models are required for the initial dosage selection for spinal cord-injured patients. Future approaches for developing population models should allow the linkage of structural parameters to multiple patient covariates.