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Purpose A population pharmacokinetic model of fosfomycin was developed in healthy volunteers after intravenous administration, and different dosing regimens were evaluated in terms of the probability of target attainment for Escherichia coli using both plasma and urinary pharmacokinetic/pharmacodynamic targets. Methods Eight healthy men received fosfomycin as both intermittent 8 g q8h and continuous infusion 1 g/h with a loading dose of 8 g in a crossover study design. Dense sampling was conducted during both regimens. Population pharmacokinetic modelling was performed using NONMEM. Monte Carlo simulations were conducted to evaluate the Probability of Target Attainment (PTA) of different dosing regimens using bactericidal (AUC24h/MIC of 83 and 75%T>MIC) and bacteriostatic (AUC24h/MIC of 25) plasma targets and bacteriostatic (AUC24h/MIC of 3994) urine target. Results A total of 176 plasma and 86 urine samples were available for PK analysis. A two-compartment model with a urine compartment best described the data. Glomerular filtration rate (GFR) showed a significant correlation with renal clearance and was implemented in the final model. Simulation results show that the dose of 4 g q8h reached 100% of PTA using bactericidal and bacteriostatic targets for MIC up to 16 mg/L. Conclusion For the clinical breakpoint of 32 mg/L, the standard dosing regimen (4 g q8h) might not be sufficient to reach the bactericidal target. Higher dosing of 8 g q8h as an intermittent infusion or 0.75 g/h as a continuous infusion might be required. Continuous infusion resulted in better attainment of the %T>MIC target than intermittent infusion.

Background and Objective: Intravenous immunoglobulin (IVIg) at a standard dosage is the treatment of choice for Guillain–Barré syndrome. The pharmacokinetics, however, is highly variable between patients, and a rapid clearance of IVIg is associated with poor recovery. We aimed to develop a model to predict the pharmacokinetics of a standard 5-day IVIg course (0.4 g/kg/day) in patients with Guillain–Barré syndrome. Methods: Non-linear mixed-effects modelling software (NONMEM®) was used to construct a pharmacokinetic model based on a model-building cohort of 177 patients with Guillain–Barré syndrome, with a total of 589 sequential serum samples tested for total immunoglobulin G (IgG) levels, and evaluated on an independent validation cohort that consisted of 177 patients with Guillain–Barré syndrome with 689 sequential serum samples. Results: The final two-compartment model accurately described the daily increment in serum IgG levels during a standard IVIg course; the initial rapid fall and then a gradual decline to steady-state levels thereafter. The covariates that increased IgG clearance were a more severe disease (as indicated by the Guillain–Barré syndrome disability score) and concomitant methylprednisolone treatment. When the current dosing regimen was simulated, the percentage of patients who reached a target ∆IgG > 7.3 g/L at 2 weeks decreased from 74% in mildly affected patients to only 33% in the most severely affected and mechanically ventilated patients (Guillain–Barré syndrome disability score of 5). Conclusions: This is the first population-pharmacokinetic model for standard IVIg treatment in Guillain–Barré syndrome. The model provides a new tool to predict the pharmacokinetics of alternative regimens of IVIg in Guillain–Barré syndrome to design future trials and personalise treatment.

Summary Glucocorticoids form the backbone of paediatric acute lymphoblastic leukaemia (ALL) treatment. Many studies have been performed on steroid resistance; however, few studies have addressed the relationship between dose, concentration and clinical response. The aim of the present study was to evaluate the pharmacokinetics of prednisolone in the treatment of paediatric ALL and the correlation with clinical parameters. A total of 1028 bound and unbound prednisolone plasma concentrations were available from 124 children (aged 0–18 years) with newly diagnosed ALL enrolled in the Dutch Childhood Oncology Group studies. A population pharmacokinetic model was developed and post hoc area under the curve (AUC) was tested against treatment outcome parameters. The pharmacokinetics of unbound prednisolone in plasma was best described with allometric scaling and saturable binding to proteins. Plasma protein binding decreased with age. The AUC of unbound prednisolone was not associated with any of the disease parameters or treatment outcomes. Unbound prednisolone plasma concentrations correlated with age. No effect of exposure on clinical treatment outcome parameters was observed and does not substantiate individualised dosing. Poor responders, high‐risk and relapsed patients showed a trend towards lower exposure compared to good responders. However, the group of poor responders was small and requires further research.

Background Ciprofloxacin is used as antimicrobial prophylaxis in pediatric acute lymphoblastic leukemia (ALL) to decrease infections with gram-negative bacteria. However, there are no clear guidelines concerning prophylactic dose. Aims To determine the pharmacokinetics and pharmacodynamics (PKPD) of ciprofloxacin prophylaxis in a pediatric ALL population. The effect of patient characteristics and antileukemic treatment on ciprofloxacin exposure, the area under the concentration time curve over minimal inhibitory concentration (AUC24/MIC) ratios, and emergence of resistance were studied. Methods A total of 615 samples from 129 children (0–18 years) with ALL were collected in a multicenter prospective study. A population pharmacokinetic model was developed. Microbiological cultures were collected prior to and during prophylaxis. An AUC24/MIC of ≥125 was defined as target ratio. Results A 1-compartment model with zero-order absorption and allometric scaling best described the data. No significant (P < .01) covariates remained after backward elimination and no effect of asparaginase or azoles were found. Ciprofloxacin AUC24 was 16.9 mg*h/L in the prednisone prophase versus 29.3 mg*h/L with concomitant chemotherapy. Overall, 100%, 81%, and 18% of patients at, respectively, MIC of 0.063, 0.125, and 0.25 mg/L achieved AUC24/MIC ≥ 125. In 13% of the patients, resistant bacteria were found during prophylactic treatment. Conclusion Ciprofloxacin exposure shows an almost 2-fold change throughout the treatment of pediatric ALL. Depending on the appropriateness of 125 as target ratio, therapeutic drug monitoring or dose adjustments might be indicated for less susceptible bacteria starting from ≥ 0.125 mg/L to prevent the emergence of resistance and reach required targets for efficacy.

Erwinia asparaginase is an important component in the treatment of pediatric acute lymphoblastic leukemia. A large variability in serum concentrations has been observed after intravenous Erwinia asparaginase. Currently, Dutch Childhood Oncology Group protocols dose alterations are based on trough concentrations to ensure adequate asparaginase activity (≥100 IU/L). The aim of this study was to describe the population pharmacokinetics of intravenous Erwinia asparaginase to quantify and gather insight into inter-individual and inter-occasion variability. The starting dose was evaluated on the basis of the derived population pharmacokinetic parameters. In a multicenter prospective observational study, a total of 714 blood samples were collected from 51 children (age 1-17 years) with acute lymphoblastic leukemia. The starting dose was 20,000 IU/m(2) three times a week and adjusted according to trough levels from week three onwards. A population pharmacokinetic model was developed using NONMEM(®) A 2-compartment linear model with allometric scaling best described the data. Inter-individual and inter-occasion variability of clearance were 33% and 13%, respectively. Clearance in the first month of treatment was 14% higher (P

Pharmacokinetic research has become increasingly important in pediatric oncology as it can have direct clinical implications and is a crucial component in individualized medicine. Population pharmacokinetics has become a popular method especially in children, due to the potential for sparse sampling, flexible sampling times, computing of heterogeneous data, and identification of variability sources. However, population pharmacokinetic reports can be complex and difficult to interpret. The aim of this article is to provide a basic explanation of population pharmacokinetics, using clinical examples from the field of pediatric oncology, to facilitate the translation of pharmacokinetic research into the daily clinic.

Although dexamethasone is an effective treatment for acute lymphoblastic leukemia (ALL), it can induce a variety of serious neurobehavioral side effects. We hypothesized that these side effects are influenced by glucocorticoid sensitivity at the tissue level. We therefore prospectively studied whether we could predict the occurrence of these side effects using the very low-dose dexamethasone suppression test (DST) or by measuring trough levels of dexamethasone. Fifty pediatric patients (3-16 years of age) with acute lymphoblastic leukemia (ALL) were initially included during the maintenance phase (with dexamethasone) of the Dutch ALL treatment protocol. As a marker of glucocorticoid sensitivity, the salivary very low-dose DST was used. A post-dexamethasone cortisol level

Background Dopamine D3 receptors regulate sensorimotor gating in rats, as evidenced by changes in prepulse inhibition (PPI) of startle after acute administration of D3 agonists and antagonists. In this study, we tested the effects of the D3-preferential agonist, pramipexole, on PPI in normal men and Sprague–Dawley rats. Materials and Methods Acoustic startle and PPI were tested in clinically normal men, comparing the effects of placebo vs. 0.125 mg (n = 20) or placebo vs. 0.1875 mg (n = 20) pramipexole, in double blind, crossover designs. These measures were also tested in male Sprague–Dawley rats using a parallel design [vehicle vs. 0.1 mg/kg (n = 8), vehicle vs. 0.3 mg/kg (n = 8) or vehicle vs. 1.0 mg/kg pramipexole (n = 8)]. Autonomic and subjective measures of pramipexole effects and several personality instruments were also measured in humans. Results Pramipexole increased drowsiness and significantly increased PPI at 120-ms intervals in humans; the latter effect was not moderated by baseline PPI or personality scale scores. In rats, pramipexole causes a dose-dependent reduction in long-interval (120 ms) PPI, while low doses actually increased short-interval (10–20 ms) PPI. Effects of pramipexole on PPI in rats were independent of baseline PPI and changes in startle magnitude. Conclusion The preferential D3 agonist pramipexole modifies PPI in humans and rats. Unlike indirect DA agonists and mixed D2/D3 agonists, pramipexole increases long-interval PPI in humans, in a manner that is independent of baseline PPI and personality measures. These findings are consistent with preclinical evidence for differences in the D2- and D3-mediated regulation of sensorimotor gating.

Although dexamethasone is highly effective in the treatment of pediatric acute lymphoblastic leukemia (ALL), it can cause serious metabolic side effects. Because studies regarding the effects of dexamethasone are limited by their small scale, we prospectively studied the direct effects of treating pediatric ALL with dexamethasone administration with respect to activation of components of metabolic syndrome (MetS); in addition, we investigated whether these side effects were correlated with the level of dexamethasone. Fifty pediatric patients (3-16 years of age) with ALL were studied during a 5-day dexamethasone course during the maintenance phase of the Dutch Childhood Oncology Group ALL-10 and ALL-11 protocols. Fasting insulin, glucose, total cholesterol, HDL, LDL, and triglycerides levels were measured at baseline (before the start of dexamethasone; T1) and on the fifth day of treatment (T2). Dexamethasone trough levels were measured at T2. We found that dexamethasone treatment significantly increased the following fasting serum levels (P3.4) from 8% to 85% (P

Asparaginase is an important component in the treatment of pediatric acute lymphoblastic leukemia (ALL). Erwinia asparaginase is used in patients who develop hypersensitivity to the E. coli derived asparaginase (native asparaginase or PEGasparaginase). Little is known about the pharmacokinetics (PK) of Erwinia asparaginase, especially after intravenous administration. A 100-fold difference in Erwinia asparaginase serum trough levels between patients has been observed during therapeutic drug monitoring (TDM). Currently, in DCOG ALL-protocols dose alterations of asparaginase and erwinase are based on TDM, with the aim to keep the trough asparaginase activity above the 100 IU/L threshold. No formal guidelines for increasing or decreasing the dose are available, and dose-adaptations are based on empirical knowledge. With a PK model, individual dose requirements can be estimated based on their PK parameters like clearance. The final aim is to avoid under-exposure and relapse, or over-exposure which may induce side-effects and results in unnecessary costs. However the upper limit of the therapeutic window that causes toxicity is not known. Aims The aim of this retrospective study was to describe the population PK of Erwinia asparaginase to gather insight in the inter-individual and intra-individual variability, and which co-variates influence exposure. Availability of a population PK model will allow the calculation of a starting dose and subsequent dosing in TDM-setting in the future. Methods A total of 714 evaluable blood samples were collected from 51 children with ALL who received intravenous Erwinia asparaginase as a substitute for E. coli or PEG asparaginase, when treated according to the DCOG ALL-10 or 11 protocol. Patients (32 males and 19 females), had a median age of 6 years (range 1-17), median weight of 25 kg (12-99) and median BSA of 0.92 m2 (0.53-2.22). The median number of samples per patient was 11 (2 - 43). Samples were taken approximately 48 (52.2%) and 72 (36.8%) hours after administration. In addition, samples within 5h (2.4%), between 5-40h (1.3%) and between 80-120h (7.3%) after administration were available. The Erwinia starting dose was 20,000 IU/m2/3x per week, and was given IV over 1 hour, and was later adapted based on TDM to 5,000-50,400 IU/m2 twice (54.2%) or thrice (45.8%) weekly. A population pharmacokinetic model was developed using nonlinear mixed-effects modeling (NONMEM 7.2; pirana 2.7.1; Xpose4). Monte Carlo simulations were performed with different doses and stratification for body weight (n=5000 per dose per weight). Results The concentration versus time profiles were best described with a 2-compartment model with allometric scaling (weight). The parameter estimates were: Cl 0.439 L/h/70kg, V1 (central compartment) 3.22 L/70kg, intercompartimental clearance 0.149 L/h/70kg and V2 (peripheral compartment) 1.14 L/70kg. The interindividual variability of clearance was 32.6%. There was an interoccasion variability of 12.7% based on monthly intervals. Clearance in the first month of treatment was 14% higher compared to the other months (p Based on the simulations, patients with a lower body weight appeared to require higher starting doses to achieve sufficient erwinase levels after 48 hours. With the current starting dose of 20,000 IU/m2, circa 75% of the patients >50kg would have levels >100 IU/L after 48h. For patients between 20-50 kg the dose starting dose should be 25,000 IU/m2 in order to achieve levels >100 IU/L at 48h in 75% of the patients. In our study, of 36 patients with evaluable starting doses (dosed 20,000 IU/m2 and with an available 48h sample), 38.7% (from a total of 31 patients Conclusions A population PK model was developed for Erwinia asparaginase in pediatric ALL patients. Depending on the weight of the patients the currently used starting dose of 20,000 IU/m2 may need to be adjusted to produce similar trough asparaginase activity, which needs to be confirmed prospectively. The PK model can be used for TDM to calculate dose adjustments in individual patients based on single PK samples, which might result in better dose-predictions than used in current practice. Disclosures Pieters: Eusa Pharma: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Kaspers:Celgene: Consultancy; Boehringer Ingelheim: Consultancy; Galen Pharmaceuticals: Consultancy. van der Sluis:Eusa Pharma: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding.