Marc R. Gastonguay

Population Pharmacokinetics of Fluconazole in Young Infants

ABSTRACT Fluconazole is being increasingly used to prevent and treat invasive candidiasis in neonates, yet dosing is largely empirical due to the lack of adequate pharmacokinetic (PK) data. We performed a multicenter population PK study of fluconazole in 23- to 40-week-gestation infants less than 120 days of age. We developed a population PK model using nonlinear mixed effect modeling (NONMEM) with the NONMEM algorithm. Covariate effects were predefined and evaluated based on estimation precision and clinical significance. We studied fluconazole PK in 55 infants who at enrollment had a median (range) weight of 1.02 (0.440 to 7.125) kg, a gestational age at birth (BGA) of 26 (23 to 40) weeks, and a postnatal age (PNA) of 2.3 (0.14 to 12.6) weeks. The final data set contained 357 samples; 217/357 (61%) were collected prospectively at prespecified time intervals, and 140/357 (39%) were scavenged from discarded clinical specimens. Fluconazole population PK was best described by a one-compartment model with covariates normalized to median values. The population mean clearance (CL) can be derived for this population by the equation CL (liter/h) equals 0.015 · (weight/1)0.75 · (BGA/26)1.739 · (PNA/2)0.237 · serum creatinine (SCRT)−4.896 (when SCRT is >1.0 mg/dl), and using a volume of distribution (V) (liter) of 1.024 · (weight/1). The relative standard error around the fixed effects point estimates ranged from 3 to 24%. CL doubles between birth and 28 days of age from 0.008 to 0.016 and from 0.010 to 0.022 liter/kg/h for typical 24- and 32-week-gestation infants, respectively. This population PK model of fluconazole discriminated the impact of BGA, PNA, and creatinine on drug CL. Our data suggest that dosing in young infants will require adjustment for BGA and PNA to achieve targeted systemic drug exposures.

Fluconazole dosing for the prevention or treatment of invasive candidiasis in young infants.

Background: Young infants are susceptible to developmental factors influencing the pharmacokinetics of drugs. Fluconazole is increasingly used to prevent and treat invasive candidiasis in infants. Dosing guidance remains empiric and variable because limited pharmacokinetic data exist. Methods: Our population pharmacokinetic model derived from 357 fluconazole plasma concentrations from 55 infants (23–40 week gestation) illustrates expected changes in fluconazole clearance based upon gestational age, postnatal age, weight, and creatinine. We used a Monte Carlo simulation approach based on parametric description of a patient populations pharmacokinetic response to fluconazole to predict fluconazole exposure (median: 10th and 90th percentile population variability range) after 3, 6, and 12 mg/kg dosing. Results: For the treatment of invasive candidiasis, a dose of at least 12 mg/kg/d in the first 90 days after birth is needed to achieve an area under the concentration curve (AUC) of >400 mg*h/L and an AUC/minimum inhibitory concentration (MIC) >50 for Candida species with MIC <8 &mgr;g/mL in ≥90% of <30 week gestation infants and 80% of 30 to 40 week gestation infants. The more preterm infants achieve a higher median AUC (682 mg*hr/L) compared with more mature infants (520 mg*hr/L). For early prevention of candidiasis in 23 to 29 week infants, a dose of 3 or 6 mg/kg twice weekly during the first 42 days of life is equivalent to an AUC of 50 and 100 mg*hr/L, respectively, and maintains fluconazole concentrations ≥2 or 4 &mgr;g/mL, respectively, for half of the dosing interval. For late prevention, the 6 mg/kg dose every 72 hours provides similar exposure to 3 mg/kg daily dose. Infants with serum creatinine ≥1.3 mg/dL have delayed drug clearance and dose adjustment is indicated if creatinine does not improve within 96 hours. Conclusions: A therapeutic concentration of fluconazole in premature infants with invasive candidiasis requires dosing substantially greater than commonly recommended in most reference texts. To prevent invasive candidiasis, twice weekly prophylaxis regimens can provide adequate exposure when unit specific MICs are taken into account.

Pharmacometrics: A Multidisciplinary Field to Facilitate Critical Thinking in Drug Development and Translational Research Settings

Pharmacometrics has evolved beyond quantitative analysis methods used to facilitate decision making in drug development, although the application of the discipline in this arena continues to represent the primary emphasis of scientists calling themselves pharmacometricians. While related fields populate and interface with pharmacometrics, there is a natural synergy with clinical pharmacology due to common areas of research and the decision‐making expectation with respect to evolving conventional and translational research paradigms. Innovative and adaptable training programs and resources are essential in this regard as both disciplines promise to be key elements of the clinical research workplace of the future. The demand for scientists with pharmacometrics skills has risen substantially. Likewise, the salary garnered by those with these skills appears to be surpassing their counterparts without such backgrounds. Given the paucity of existing training programs, available training materials, and academic champions, a virtual faculty and online curriculum would allow students to matriculate into one of several programs associated with their advisor but take instruction from faculty at multiple institutions, including instructors in both industrial and regulatory settings. Flexibility in both the curriculum and the governance of the degree would provide the greatest hope of addressing the short supply of trained pharmacometricians.

Population pharmacokinetics of ciprofloxacin in pediatric patients

The objective of this study was to characterize ciprofloxacin population pharmacokinetics in pediatric patients. A total of 150 pediatric patients (including 28 patients with cystic fibrosis [CF], ages 0.27–16.9 years) received ciprofloxacin by the oral and/or intravenous routes. Population pharmacokinetic analyses were performed with NONMEM software. Exponential error models were used to describe the interindividual variance in pharmacokinetic parameters, and the residual error model included both proportional and additive components. Based on principles of allometry, the patients body weight was used as a covariate, along with appropriate allometric exponents, in the construction of the base model. Model building was accomplished by a stepwise forward inclusion procedure, and the final model was evaluated by multiple techniques, including bootstrap, leverage analysis, and cross‐validation. With body weight included in the model (two compartments with first‐order absorption), ciprofloxacin clearance was influenced by age, and the absorption rate constant was altered in CF patients. The final model is summarized as follows: CL (L/h) = 30.3 × (WT/70)0.75 × (1 + 0.045 [AGE −2.5]), VC (L) = 56.7 × (WT/70)1.0, VP (L) = 89.8 × (WT/70)1.0, Q (L/h) = 37.5 × (WT/70)0.75, Ka (1/h) = 1.27 × (1 + [−0.611 × CF]), absorption lag time = 0.35 hours, and bioavailability fraction = 61.1%, where WT and AGE are the patients body weight (kg) and age (years), respectively, and the variable CF equals 1 for CF patients and 0 for non‐CF patients. The interpatient variability in pharmacokinetic parameters (percentage coefficient of variation [%CV]) ranged from 22.5% to 49.8%. The residual variabilities (%CV) for the oral and intravenous data were 40% and 27%, respectively. The shared additive residual variance component was small (SD = 0.04 mg/L). Model evaluation by the different methods indicated that the final model was robust and parameter estimates were precise. A small difference (< 6%) was noted when the patients age was not used in dose calculation. Therefore, in routine clinical use, for pediatric patients older than 3 months, ciprofloxacin dose may be calculated solely based on body weight.

Development and evaluation of a population pharmacokinetic-pharmacodynamic model of darbepoetin alfa in patients with nonmyeloid malignancies undergoing multicycle chemotherapy.

Anemia is frequently observed in patients undergoing chemotherapy. Administration of darbepoetin alfa, a recombinant erythropoiesis-stimulating agent that has longer residence time than endogenous erythropoietin, to patients with chemotherapy-induced anemia (CIA) increases mean hemoglobin concentration, reduces risk of red blood cell transfusions, and improves patient-reported outcomes. A pharmacokinetic/pharmacodynamic (PkPd) model was developed using data from patients with nonmyeloid malignancies and CIA who were receiving darbepoetin alfa. A 2-compartment Pk model with linear elimination described the Pk data obtained in 140 CIA patients after intravenous and subcutaneous (SC) doses of 2.25 μg/kg every week and SC doses of 6.75 μg/kg every 3 weeks. The population typical values of key Pk parameters were clearance, 2010 mL/day; steady-state volume of distribution, 3390 mL; and bioavailability, 44.3%. A modified indirect response model, wherein serum concentrations stimulated the production of hemoglobin through an Emax-type equation, described the hemoglobin levels after SC doses of 0.5 μg/kg every week to 15 μg/kg every 3 weeks in 573 CIA patients. The estimated incremental maximum stimulation of hemoglobin production was 43.7% and darbepoetin alfa serum concentration at half-maximal stimulation was 3.68 ng/mL. The impact of covariates (body weight and platinum-containing chemotherapy) on the PkPd response was evaluated based on point and interval estimates of parameters, rather than through stepwise hypothesis testing. The final PkPd model adequately predicted hemoglobin response in a test data set, thereby confirming the predictive capability of the model. Based on simulations, it was not possible to categorize the influence of any covariate as clinically important.

Population pharmacokinetics of dexmedetomidine in infants after open heart surgery.

BACKGROUND: Dexmedetomidine is a highly selective &agr;2-agonist with hypnotic, analgesic, and anxiolytic properties. In adults, it provides sedation while preserving respiratory function facilitating extubation. Only limited pharmacokinetic data are available for pediatric patients. The primary aim of this study was to determine the pharmacokinetics of dexmedetomidine in infants after open heart surgery. METHODS: We evaluated 36 infants, aged 1 to 24 months, after open heart surgery. Cohorts of 12 infants requiring mechanical ventilation after open heart surgery were enrolled sequentially to 1 of the 3 initial loading dose—continuous IV infusion (CIVI) regimens: 0.35–0.25, 0.7–0.5, or 1–0.75 &mgr;g/kg-&mgr;g/kg/h. The initial loading dose was administered over 10 minutes immediately postoperatively followed by a CIVI of up to 24 hours. Plasma dexmedetomidine concentrations were determined using a validated high-performance liquid chromatography tandem mass spectrometry assay. A population nonlinear mixed effects modeling approach was used to characterize dexmedetomidine pharmacokinetics. RESULTS: Pharmacokinetic parameters of dexmedetomidine were estimated using a 2-compartment disposition model with weight on drug clearance, intercompartmental clearance, central and peripheral volume of distributions, total bypass time as a covariate on clearance and central volume of distribution, and age and ventricular physiology as covariates on clearance. Infants demonstrated a clearance of 28.1 mL/min/kg0.75, intercompartmental clearance of 93.4 mL/min/kg0.75, central volume of distribution of 1.2 L/kg, and peripheral volume of distribution of 1.5 L/kg. CONCLUSIONS: Dexmedetomidine clearance increased with weight, age, and single-ventricle physiology, whereas total bypass time was associated with a trend toward decreasing clearance, and central volume of distribution increased as a function of total bypass time. The dependence of clearance on body weight supports current practice of weight-based dexmedetomidine dosing, whereas the clinical impact of the remaining covariate effects requires further investigation. Initial loading doses in the range of 0.35 to 1 &mgr;g/kg over 10 minutes and CIVI of 0.25 to 0.75 &mgr;g/kg/h were well tolerated in this infant population.

Combining patient-level and summary-level data for Alzheimer’s disease modeling and simulation: a beta regression meta-analysis

Our objective was to develop a beta regression (BR) model to describe the longitudinal progression of the 11 item Alzheimer’s disease (AD) assessment scale cognitive subscale (ADAS-cog) in AD patients in both natural history and randomized clinical trial settings, utilizing both individual patient and summary level literature data. Patient data from the coalition against major diseases database (3,223 patients), the Alzheimer’s disease neruroimaging initiative study database (186 patients), and summary data from 73 literature references (representing 17,235 patients) were fit to a BR drug-disease-trial model. Treatment effects for currently available acetyl cholinesterase inhibitors, longitudinal changes in disease severity, dropout rate, placebo effect, and factors influencing these parameters were estimated in the model. Based on predictive checks and external validation, an adequate BR meta-analysis model for ADAS-cog using both summary-level and patient-level data was developed. Baseline ADAS-cog was estimated from baseline MMSE score. Disease progression was dependent on time, ApoE4 status, age, and gender. Study drop out was a function of time, baseline age, and baseline MMSE. The use of the BR constrained simulations to the 0–70 range of the ADAS-cog, even when residuals were incorporated. The model allows for simultaneous fitting of summary and patient level data, allowing for integration of all information available. A further advantage of the BR model is that it constrains values to the range of the original instrument for simulation purposes, in contrast to methodologies that provide appropriate constraints only for conditional expectations.

Population pharmacokinetics and pharmacodynamics of sotalol in pediatric patients with supraventricular or ventricular tachyarrhythmia.

Aims: To derive useful pharmacokinetic (PK) and pharmacodynamic (PD) information for guiding the clinical use of sotalol in pediatric patients with supraventricular (SVT) or ventricular tachyarrhythmia (VT).Methods: Two studies were conducted in-patients with SVT or VT in the age range between birth and 12 years old. Both studies used an extemporaneously compounded formulation prepared from sotalol HCl tablets. In the PK study, following a single dose of 30 mg/m2 sotalol, extensive blood samples (n=10) were taken. The PK–PD study used a dose escalation design with doses of 10, 30, and 70 mg/m2, each administered three times at 8-hr intervals without a washout. Six ECG recordings for determination of QT and RR were obtained prior to the initial dose of sotalol. Four blood samples were collected six ECGs were determined during the third interval at each dose level. Plasma concentrations of sotalol (C) were assayed by LC/MS/MS. The data analysis used NONMEM to obtain the population PK and PD parameter estimates. The individual PK and PD parameters were estimated with empirical Bayes methodology.Results: A total of 611 C from 58 patients, 477 QTc and 499 RR measurements from 23 and 22 patients, respectively, were available for analysis. The PK of sotalol was best described by a linear two-compartment model. Oral clearance (CL/F) and volume of central compartment (Vc/F) were linearly correlated with body surface area (BSA), body weight or age. CL/F was also linearly correlated with creatinine clearance. The best predictor for both CL/F and Vc/F was BSA. The remaining intersubject coefficients of variation (CVs) in CL/F, and Vc/F were 21.6% and 20.3%, respectively. The relationship of QTc to C was adequately described by a linear model. The intersubject CVs in slope (SL) and intercept (E0) were 56.2 and 4.7%, respectively. The relationship of RR to C was also adequately described by a linear model in which the baseline RR and SL were related to age or BSA. The intersubject CVs for SL and E0 were 86.7 and 14.4%, respectively.Conclusions: BSA is the best predictor for the PK of sotalol. Both QTc and RR effects are linearly related to C. No covariates are found for the QTc–C relation, while the RR–C relation shows age or BSA dependency.

Population Pharmacokinetic/Pharmacodynamic Model of Subcutaneous Adipose 11β‐Hydroxysteroid Dehydrogenase Type 1 (11β‐HSD1) Activity After Oral Administration of AMG 221, a Selective 11β‐HSD1 Inhibitor

Inhibition of 11β‐HSD1 is hypothesized to improve measures of insulin sensitivity and hepatic glucose output in patients with type II diabetes. AMG 221 is a potent, small molecule inhibitor of 11β‐HSD1. The objective of this analysis is to describe the pharmacokinetic/pharmacodynamic (PK/PD) relationship between AMG 221 and 11β‐HSD1 inhibition in ex vivo adipose tissue samples. Healthy, obese subjects were administered a single dose of 3, 30, or 100 mg of oral AMG 221 (n = 44) or placebo (n = 11). Serial blood samples were collected over 24 hours. Subcutaneous adipose tissue samples were collected by open biopsy. Population PK/PD analysis was conducted using NONMEM. The inhibitory effects (mean ± standard error of the estimate) of AMG 221 on 11β‐HSD1 activity were directly related to adipose concentrations with Imax (the maximal inhibition of 11β‐HSD1 activity) and IC50 (the plasma AMG 221 concentration associated with 50% inhibition of enzyme activity) of 0.975 ± 0.003 and 1.19 ± 0.12 ng/mL, respectively. The estimated baseline 11β‐HSD1 enzyme activity was 755 ± 61 pmol/mg. An equilibration rate constant (keo) of 0.220 ± 0.021 h–1 described the delay between plasma and adipose tissue AMG 221 concentrations. AMG 221 potently blocked 11β‐HSD1 activity producing sustained inhibition for the 24‐hour study duration as measured in ex vivo adipose samples. Early characterization of concentration‐response relationships can support rational selection of dose and regimen for future studies.

Population Pharmacokinetic Investigation of Actinomycin‐D in Children and Young Adults

Actinomycin‐D is an antineoplastic agent that inhibits RNA synthesis by binding to guanine residues and inhibiting DNA‐dependent RNA polymerase. Although actinomycin‐D has been used to treat rhabdomyosarcoma and Wilms tumor for more than 40 years, the dose/exposure relationship is not well characterized. The objective of this study was to develop an initial population pharmacokinetic model to describe actinomycin‐D disposition in children and young adults from which a prospective study could be designed. A total of 165 actinomycin‐D plasma concentration measurements from 33 patients, aged 1.6 to 20.3 years, were used for the analysis. The data were analyzed using nonlinear mixed‐effects modeling with the NONMEM software system. Age, weight, and gender were examined as covariates for the ability to explain interindividual variability in actinomycin‐D pharmacokinetics. The final model was qualified via predictive check and nonparametric bootstrap procedures. A 3‐compartment model with first‐order elimination was chosen as the structural model. Allometric expressions incorporating weight were used to describe the effects of body size on actinomycin‐D pharmacokinetics. Age and gender had no discernible effects on actinomycin‐D pharmacokinetics in the population studied. The predictive check showed that the developed model was able to simulate data in close agreement with the actual study observations. The availability of an initial population pharmacokinetic model to describe actinomycin‐D pharmacokinetics will facilitate the development of a large‐scale clinical trial to study the actinomycin‐D dose/exposure relationship in pediatric patients with rhabdomyosarcoma and Wilms tumor. The covariate analysis described by the current data set suggests that indices of body size captured via allometric expressions improve the partition of variation in actinomycin‐D pharmacokinetics from this pilot data set. Relationships between pharmacokinetics and toxicity will be examined in future prospective studies in which children less than 1 year old will be enrolled.