Paul Beringer,* Amir Aminimanizani,* Timothy Synold, and Christy Scott

Transcription

1 Therapeutic Drug Monitoring 24: Lippincott Williams & Wilkins, Inc., Philadelphia Development of Population Pharmacokinetic Models and Optimal Sampling Times for Ibuprofen Tablet and Suspension Formulations in Children With Cystic Fibrosis Paul Beringer,* Amir Aminimanizani,* Timothy Synold, and Christy Scott *School of Pharmacy, University of Southern California, Los Angeles, California, Department of Medical Oncology, City of Hope National Medical Center, Duarte, California, Department of Pharmacy Practice, University of North Carolina, Chapel Hill, North Carolina, Current Affiliation: Medical Information Specialist, Astra-Zeneca Pharmaceuticals, Chapel Hill, North Carolina Summary: High-dose ibuprofen therapy has demonstrated to slow deterioration in pulmonary function in children with cystic fibrosis with mild lung disease. Therapeutic drug monitoring has been recommended to maintain peak concentrations within the range of 50 to 100 mg/l to ensure efficacy. Current methods for dosage individualization are based on dose proportionality using visual inspection of the peak concentration; however, because of interpatient variability in the absorption of the various formulations this method may result in incorrect assessments of the peak concentration achieved. Maximum a posteriori Bayesian analysis (MAP-B) has proven to be a useful and precise method of individualizing the dose of aminoglycosides but requires a description of the structural model. In this study we performed parametric population modeling analysis on plasma concentrations of ibuprofen after single doses of 20 to 30-mg/kg tablet or suspension in children with cystic fibrosis. Patients evaluated in this study were part of a single dose pharmacokinetic study that has been published previously. A one-compartment model with first order absorption and a lag time best described the data. The pharmacokinetic parameters differed significantly depending on the formulation administered. D-optimal sampling times for the suspension and tablet formulations are 0, 0.25 to 0.5, 1, and 3 to 4 hours and 0, 0.25 to 0.5, 1 to 1.5, and 5 hours respectively. Use of MAP-B analysis performed with the 4 d-optimal sampling strategy resulted in accurate and precise estimates of the pharmacokinetic parameters when compared with maximum likelihood analysis using the complete plasma concentrations data set. Further studies are needed to evaluate the performance of these models and the impact on patient outcomes. Respiratory disease is of unique importance in patients with cystic fibrosis (CF) because it is the primary factor responsible for repeated hospitalizations and decline in pulmonary function. More importantly, respiratory complications are the primary cause of mortality (1). Whereas the exact pathophysiologic mechanism linking the defective gene product, the cystic fibrosis Address correspondence and reprint requests to Paul Beringer, PharmD, School of Pharmacy, 1985 Zonal Avenue, Los Angeles, CA 90033; beringer@usc.edu transmembrane regulator (CFTR), to lung disease has not been clearly established, ineffective local host defense mechanisms resulting in chronic infection, inflammation and tissue damage has been implicated (2). Recognition of the potent inflammatory response to the presence of chronic infection within the airways and its destruction of the lung has led to investigations of various antiinflammatory agents. The goal of such therapies is to interrupt the cycle of infection inflammation with the intent of slowing the deterioration in pulmonary function. 315

2 316 P. BERINGER ET AL The course of the lung disease in patients with CF progresses rapidly throughout childhood and adolescence such that early therapy is desirable to slow the deterioration. Therapeutic agents that have been evaluated include oral corticosteroids, and nonsteroidals. Because of an increased incidence of growth retardation, cataracts, and glucose intolerance in CF children, prolonged therapy with oral corticosteroids (>2 years) is not recommended (3). Ibuprofen, a potent cyclooxygenase inhibitor, given in high doses can inhibit neutrophil migration and activation (4). It has been shown to be beneficial in children aged 5 to 13 years with mild lung disease (5). Whereas results of this trial indicate ibuprofen therapy is well tolerated, concern for the development of adverse effects (i.e. bleeding, renal failure) has limited the widespread use of this agent (6 8). Individualization of the ibuprofen dose is recommended because of the high doses necessary to achieve therapeutic concentrations ( g/ml) and the large interpatient variability in the pharmacokinetic parameters (9 12); however, the number and timing of concentrations obtained and the method in which the data is analyzed has not been critically evaluated. Current methods for dosage individualization are based on dose proportionality using visual inspection of the peak concentration (13). Because of variability in the absorption of the various formulations of ibuprofen it is possible that this method may miss the actual peak concentration resulting in inappropriate dosage adjustment. In addition, sampling only at the peak time does not enable determination of the elimination phase, which may be beneficial in characterizing the extent of ibuprofen exposure. The use of maximum a posteriori Bayesian analysis (MAP-B) has proved to be a useful and precise method of controlling drug concentrations of aminoglycosides and is routinely used for monitoring and adjusting doses to maximize efficacy and minimize the risk of toxicity (14). The use of MAP-B analysis requires a structural model describing the disposition of the drug (15). Most of the studies of ibuprofen in patients with CF conducted to date used noncompartmental analysis, which does not provide sufficient information about the structural model (9,10,12). The purpose of this study was to develop population pharmacokinetic models for tablet and suspension forms of ibuprofen in children with CF. In addition, we determined the optimal sampling times for each dosage form. These tools are necessary to provide the framework for dosage individualization using MAP-B analysis. METHODS Patients and Study Design The patients evaluated in this study were part of a prior single dose pharmacokinetic study designed to compare the time to peak concentration with various oral ibuprofen dosage forms in children with CF (10). Details regarding the patient enrollment and study design have previously been published (10). Briefly, after an overnight fast, each individual was administered a single 20-mg/kg dose of ibuprofen as suspension or tablet formulation depending on patient preference. Pancreatic enzymes were administered with a standard low-fat breakfast 10 minutes after ibuprofen administration. All other medications were withheld for 2 hours after ibuprofen administration. Serial blood samples (2 ml) were obtained at the following times: immediately prior to administration, 15, 30, 45, 60, 120, 240, and 360 minutes after administration and transferred to tubes containing heparin. The samples were centrifuged and plasma was harvested and frozen at 70 C until assayed. Ibuprofen was quantified using a validated reversed-phase highperformance liquid chromatographic method as previously described (16). Pharmacokinetic Analysis Plasma concentrations were fit with several different compartmental models using an iterative two-stage Bayesian method (IT2S). Each observation was weighted by 1/C. Model discrimination based on Akaike information criterion and examination of the residual errors was performed on a subset of patients using maximum likelihood (ADAPT II) (18). Candidate models included 1- and 2-compartment models with and without lag times. The pharmacokinetic parameters determined included the volume of distribution (V d ), the elimination rate constant (K e ), the absorption rate constant (K a ), and the lag time (T lag ). Individual d-optimal sampling times were determined using the SAMPLE module of the ADAPT II software. The optimal sampling strategy for the population was determined from examination of the frequency distribution of individual optimal sampling times. MAP-B analysis was performed on concentrations obtained at the d-optimal times and compared with the parameters obtained from maximum likelihood analysis performed on the full set of concentrations for each patient. Statistical Analysis Differences in pharmacokinetic parameters between the suspension and tablet dosage forms were assessed by

3 PK AND OPTIMAL SAMPLING TIMES FOR IBUPROFEN IN CHILDREN WITH CF 317 a one-sample t test. A p value less than 0.05 was considered statistically significant. Linear regression and correlation analysis were performed to assess the relationship between fitted pharmacokinetic parameters obtained using MAP-B analysis and ML using the full data set. The bias and precision of the MAP-B analysis using the d-optimal sampling strategy was determined through predictive performance analysis (17). The mean prediction error (ME) and the mean absolute error (MAE) and their 95% confidence intervals were calculated to evaluate the bias and precision, respectively, of each method. Bias was defined as the mean of the difference between the ML and the MAP-B estimates. Using this definition, a biased estimate will either over (a positive ME value) or under (a negative ME value) predict the true estimate. Precision was defined as the absolute value of the difference between the MAP-B and the ML estimates. In this case, the prediction method with the smallest MAE is the most precise. A one-sample t test was used to assess differences in bias and precision obtained by each method. A p value less than 0.05 was considered statistically significant. RESULTS Patients Patients evaluated in this study were initiated on ibuprofen to control chronic airway inflammation. Single dose pharmacokinetic experiments were performed for dose optimization the results of which have previously been published. Plasma concentration data from 32 patients were included in the current study designed to develop population pharmacokinetic models and determine optimal sampling times for therapeutic drug monitoring. Twenty-two patients received the suspension whereas the remaining 10 patients received the tablet formulation. The mean age of the patients receiving the suspension and tablet formulations was 5.2 ± 2.1 and 9.5 ± 2.2 years respectively. The mean weight of the patients in the suspension and tablet groups was 17.9 ± 5.5 and 30.6 ± 8.7 kg respectively. The larger size of the patients receiving the tablet formulation is a reflection of the older age of this group. Pharmacokinetics A comparison of AIC values demonstrated that a 1-compartment was superior to a 2-compartment model in the first 10 patients analyzed. As a result, the 1-compartment model was chosen for further evaluation. A 1-compartment model with first-order absorption and a FIG. 1. Structural Model lag time best described the disposition of ibuprofen tablet and suspension formulations (Figure 1, Tables 1 and 2). The population pharmacokinetic parameters of the two formulations are summarized in Table 3. Significant differences in the pharmacokinetic parameters between the two dosage forms were noted. The suspension formulation exhibited a shortened lag time and more rapid absorption when compared with the tablet formulation. In addition, a smaller volume of distribution was noted for the patients receiving the suspension formulation, which may have been caused by a greater bioavailability when compared with the tablet formulation. The d-optimal sampling times for the suspension and tablet formulations are 0, 0.25 to 0.5, 1, and 3 to 4 hours and 0, 0.25 to 0.5, 1 to 1.5, and 5 hours respectively (see Figure 1). Correlation analysis revealed a good correlation between the volume of distribution and elimination rate constant estimates obtained utilizing MAP-B analysis at the d-optimal sampling times and the parameters TABLE 1. Model discrimination, suspension formulation 1-comp, lag 1-comp, no lag Patient AIC r 2 AIC r AIC, Akaike information criterion; comp, compartment.

4 318 P. BERINGER ET AL TABLE 2. Model discrimination, tablet formulation 1-comp, lag Patient AIC r 2 AIC r determined using maximum likelihood analysis on all levels (Figures 2 and 3). In contrast, relatively poor correlations were noted with the absorption rate constants and lag times when comparing the two methods. With the exclusion of a possible outlier the correlation with the absorption rate constant for the suspension formulation improved greatly (r , data not shown); however, this did not alter the predictive performance of the models. Analysis of the bias and precision revealed that use of MAP-B using the 4 d-optimal samples provides an unbiased and precise method of estimating the pharmacokinetic parameters of ibuprofen (see Figure 4). DISCUSSION 1-comp, no lag AIC, Akaike information criterion; comp, compartment. The aim of performing therapeutic drug monitoring on a specific agent is to determine the optimal dose of the agent necessary to achieve the goal of maximizing the therapeutic effect while minimizing the risk of potential dose related toxicities. This approach is typically necessary for drugs that exhibit a narrow therapeutic index or exhibit wide interpatient variability. The number and timing of concentrations obtained and the method in which the data is analyzed are critical to identification of the appropriate dose. Ibuprofen has been shown to reduce airway inflammation in vitro and in animal models when peak concentrations of 50 to 100 g/ml are achieved. Maintenance of peak concentrations in this range results in TABLE 3. Population pharmacokinetic parameters Parameter Suspension* Tablet* P value V c (L/kg) (0.053) (0.103) K e (h 1) (0.142) (0.200) K a (h 1) (6.558) (1.202) T lag (h) (0.042) (0.194) < * Values given as mean (standard deviation). K a, absorption rate constant; K e, elimination rate constant; T lag, lag time; V c, volume of central compartment uncorrected for bioavailability. FIG. 2. Plasma concentration time profile after a single dose of ibuprofen 20 mg/kg (A) suspension and (B) tablet formulations and d- optimal sampling times significantly reduced deterioration in pulmonary function in cystic fibrosis patients. Therapeutic drug monitoring has been recommended because of the high doses necessary to achieve these concentrations and the high degree of interpatient variability in the pharmacokinetics of ibuprofen. Current methods for dosage individualization are based on dose proportionality using visual inspection of the peak concentration (13). The peak concentration is determined from a 3 point sampling strategy obtained 1, 2, and 3 hours after a tablet dose or 30, 45, and 60 minutes after a suspension dose of ibuprofen (10,13). Because of the wide variability in absorption characteristics identified in this study, identification of the actual peak concentration may not be possible for patients exhibiting an absorption pattern that differs significantly from the norm. Ironically, these are the patients in which TDM is probably the most important. In

5 PK AND OPTIMAL SAMPLING TIMES FOR IBUPROFEN IN CHILDREN WITH CF 319 FIG. 3. Correlation of Pharmacokinetic Parameters Obtained with Optimal Sampling Methods (OST4) and Maximum Likelihood (ML): (A) Suspension formulation. (B) Tablet formulation. addition, this method provides no means of assessing the degree of exposure (i.e. AUC), which may be relevant for determining the risk of toxicity. Recent advances in mathematical modeling have resulted in the development of more advanced methods of controlling drug concentrations and therefore behavior. Maximum a posteriori (MAP) Bayesian analysis is a cost-effective method widely used to individualize the dose of aminoglycosides (14). This method has shown to be more accurate and precise than using nomograms or log-linear regression analysis even with relatively sparse sampling (15). The number and timing of drug concentrations is determined by the structural model used and the expected value of the parameters to be estimated. According to the d-optimal sampling theory at least one measurement is necessary for each parameter to be estimated in the model. The timing of the sample is determined to coincide with the time when the information about the parameter to be estimated is maximal. We have shown that the combination of MAP-B analysis and d-optimal sampling provides an accurate, precise, and efficient means of determining the pharmacokinetic parameters of ibuprofen in children with cystic fibrosis.

6 320 P. BERINGER ET AL FIG. 4. Bias and Precision of limited sampling schedule The pharmacokinetic parameters identified in this study compare favorably to the results found in previous investigations (9 12). Similar to the findings of others, we found that the pharmacokinetic parameters differ significantly between dosage forms (10,12). The majority of the studies published to date have focused on a description of the cmax and tmax and have not characterized the pharmacokinetics of the absorptive process. One exception is the data of Murry et al. who used a onecompartment model with first order absorption and incorporated a lag time (11). The absorption rate constant was smaller whereas the lag time was longer when compared with the data in the current study. One possible explanation for this apparent discrepancy is that in the study by Murry et al., the first sample was not obtained until 1 hour after the dose which may have limited the ability to accurately characterize the absorption phase. In addition, the authors chose to pool data from the various dosage forms administered to the patients in their study. Whereas the number of patients receiving dosage forms other than the tablet formulation was small, this may have been an additional contributing factor to the differences noted. Indeed, our data suggest that ibuprofen pharmacokinetics are dependent on the dosage form used. As a result, predictive models for each dosage form should be developed. Whereas we have demonstrated that the pharmacokinetic models in this study using MAP-B analysis on the d-optimal samples provided accurate and precise estimates of the pharmacokinetic parameters, these results will need to be validated using an independent sample. In addition, the impact of use of these models on treatment outcomes (e.g. airway inflammation and gastrointestinal adverse effects) requires further study. REFERENCES 1. Ramsey BW. Management of pulmonary disease in patients with cystic fibrosis. N Engl J Med 1996;335: Van Heeckeren A, Walenga R, Konstan MW, et al. Excessive inflammatory response of cystic fibrosis mice to bronchopulmonary infection with Pseudomonas aeruginosa. J Clin Invest 1997; 100: Rosenstein BJ, Eigen H. Risks of alternate-day prednisone in patients with cystic fibrosis. Pediatrics 1991;87: Konstan MW, Vargo KM, Davis PB. Ibuprofen attenuates the inflammatory response to Pseudomonas aeruginosa in a rat model of chronic infection. Am Rev Respir Dis 990;141: Konstan MW, Byard PJ, Hoppel CL, Davis PB. Effect of high-dose ibuprofen in patients with cystic fibrosis. New Engl J Med 1995; 332: Oermann CM, Sockrider MM, Konstan MW. The use of antiinflammatory medications in cystic fibrosis: trends and physician attitudes. Chest 1999;115: Kovesi TA. Swartz R. MacDonald N. Transient renal failure due to simultaneous ibuprofen and aminoglycoside therapy in children with cystic fibrosis [letter]. New Engl J of Med 1998;338: Bell EA. Grothe R. Zivkovich V. Foote JM. Wellendorf J. Pyloric channel stricture secondary to high-dose ibuprofen therapy in a patient with cystic fibrosis. Ann Pharmacother 1999;33: Konstan MW, Hoppel CL, Chai B, Davis PB. Ibuprofen in children with cystic fibrosis: pharmacokinetics and adverse effects. J Pediatr 1991;118: Scott CS, Retsch-Bogart GZ, Kustra RP, et al. The pharmacokinetics of ibuprofen suspension, chewable tablets, and tablets in children with cystic fibrosis. J Pediatr 1999;134: Murry DJ, Oermann CM, Ou CN, et al. Pharmacokinetics of ibuprofen in patients with cystic fibrosis. Pharmacotherapy 1999;19: Rifai N, Sakamoto M, Law T, et al.use of a rapid HPLC assay for

7 PK AND OPTIMAL SAMPLING TIMES FOR IBUPROFEN IN CHILDREN WITH CF 321 determination of pharmacokinetic parameters of ibuprofen in patients with cystic fibrosis. 13. Questions and answers ibuprofen: information for cystic fibrosis physicians. Bethesda (MD): Cystic Fibrosis Foundation. March 30, van Lent-Evers N, Mathot RA, Geus WP, et al. Impact of goaloriented and model-based clinical pharmacokinetic dosing of aminoglycosides on clinical outcome: a cost-effectiveness analysis. Ther Drug Monitor 1999;21: Jelliffe, RW. Schumitzky, A. Bayard, D. Milman, M. Maire, P. et al. Model-based, goal-oriented, individualized drug therapy: linkage of population modeling, new multiple model dosage design, Bayesian feedback and individualized target goals. Clin Pharmacokinet 1998;34: Castillo M, Smith PC. Direct determination of ibuprofen and ibuprofen acyl glucoronide in plasma by high-performance liquid chromatography using solid-phase extraction. J Chromatography 1993;614: Sheiner LB, Beal SL. Some suggestions for measuring predictive performance. J Pharmacokinet Biopharm 1981;9: D Argenio, D.Z. and A. Schumitzky. ADAPT II User s Guide: Pharmacokinetic / Pharmacodynamic Systems Analysis Software. Biomedical Simulations Resource, Los Angeles, 1997.