Amélie Marsot

Pharmacokinetics and absolute bioavailability of phenobarbital in neonates and young infants, a population pharmacokinetic modelling approach

Phenobarbital is widely used for treatment of neonatal seizures. Its optimal use in neonates and young infants requires information regarding pharmacokinetics. The objective of this study is to characterize the absolute bioavailability of phenobarbital in neonates and young infants, a pharmacokinetic parameter which has not yet been investigated. Routine clinical pharmacokinetic data were retrospectively collected from 48 neonates and infants (weight: 0.7–10 kg; patients postnatal age: 0–206 days; GA: 27–42 weeks) treated with phenobarbital, who were administered as intravenous or suspension by oral routes and hospitalized in a paediatric intensive care unit. Total mean dose of 4.6 mg/kg (3.1–10.6 mg/kg) per day was administered by 30‐min infusion or by oral route. Pharmacokinetic analysis was performed using a nonlinear mixed‐effect population model software). Data were modelled with an allometric pharmacokinetic model, using three‐fourths scaling exponent for clearance (CL). The population typical mean [per cent relative standard error (%RSE)] values for CL, apparent volume of distribution (Vd) and bioavailability (F) were 0.0054 L/H/kg (7%), 0.64 L/kg (15%) and 48.9% (22%), respectively. The interindividual variability of CL, Vd, F (%RSE) and residual variability (%RSE) was 17% (31%), 50% (27%), 39% (27%) and 7.2 mg/L (29%), respectively. The absolute bioavailability of phenobarbital in neonates and infants was estimated. The dose should be increased when switching from intravenous to oral administration.

Pediatric Patients With Solid or Hematological Tumor Disease: Vancomycin Population Pharmacokinetics and Dosage Optimization.

Background: In pediatric cancer patients, determination of optimal vancomycin dosage is essential because of high risk of inadequate concentrations and bacterial resistance. The aim of this study was to determine vancomycin pharmacokinetic parameters in this population and propose dosage optimization to achieve optimal concentration. Methods: We retrospectively reviewed the use of vancomycin in pediatric cancer patients with febrile neutropenia (hematological or solid tumor disease). Vancomycin was administered by continuous infusion, and dosages were adapted according to therapeutic drug monitoring results. Blood cultures were performed before the first dose of antibiotic. Vancomycin pharmacokinetic population parameters were determined using NONMEM software, and dosage simulations were performed according to the target concentration (20–25 mg/L). Results: One hundred twenty-one patients were included in this study, representing 301 vancomycin concentrations. Blood cultures were positive in 37.5% of patients, and observed pathogens were mainly Staphylococcus spp. (43.8% methicillin resistant). Volume of distribution (95% confidence interval) was 34.7 L (17.3–48.0), and total apparent clearance (CL) (95% confidence interval) was correlated to body weight, tumor disease, and cyclosporine coadministration: CL = &thgr;CL × (WT/70)0.75 L/h with &thgr;CL = 3.49 (3.02–3.96), 4.66 (3.98–5.31), and 4.97 (4.42–5.41) in patients managed for hematological malignancies with or without cyclosporine coadministration and for solid malignancies, respectively. Based on simulation results, vancomycin dosage (milligram per kilogram) should be adapted to each child on the basis of its body weight and cyclosporine coadministration. Conclusions: Our results highlight the requirement to adapt vancomycin dosage in cancer pediatric population. Simulations have allowed to describe new dosage schedules, and a chart was created for clinicians to adapt vancomycin dosage.

Population pharmacokinetics model of THC used by pulmonary route in occasional cannabis smokers

Cannabis is the most widely used illegal drug in the world. Delta-9-tetrahydrocannabinol (THC) is the main source of the pharmacological effect. Some studies have been carried out and showed significant variability in the described models as the values of the estimated pharmacokinetic parameters. The objective of this study was to develop a population pharmacokinetic model for THC in occasional cannabis smokers. Twelve male volunteers (age: 20-28years, body weight: 62.5-91.0kg), tobacco (3-8 cigarette per day) and cannabis occasional smokers were recruited from the local community. After ad libitum smoking cannabis cigarette according a standardized procedure, 16 blood samples up to 72h were collected. Population pharmacokinetic analysis was performed using a non-linear mixed effects model, with NONMEM software. Demographic and biological data were investigated as covariates. A three-compartment model with first-order elimination fitted the data. The model was parameterized in terms of micro constants and central volume of distribution (V1). Normal ALT concentration (6.0 to 45.0IU/l) demonstrated a statistically significant correlation with k10. The mean values (%Relative Standard Error (RSE)) for k10, k12, k21, k23, k32 and V1 were 0.408h-1 (48.8%), 4.070h-1 (21.4%), 0.022h-1 (27.0%), 1.070h-1 (14.3%), 1.060h-1 (16.7%) and 19.10L (39.7%), respectively. We have developed a population pharmacokinetic model able to describe the quantitative relationship between administration of inhaled doses of THC and the observed plasma concentrations after smoking cannabis. In addition, a linear relationship between ALT concentration and value of k10 has been described and request further investigation.

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.

Population pharmacokinetics of rifampicin in adult patients with osteoarticular infections: interaction with fusidic acid

Aims Rifampicin represents the key antibiotic for the management of osteoarticular infections. An important pharmacokinetic variability has already been described, particularly for absorption and metabolism. All previous pharmacokinetic studies have been focused only on patients treated for tuberculosis. The objective of the present study was to describe a population pharmacokinetic model of rifampicin in patients with staphylococcal osteoarticular infections, which has not been investigated to date. Method Rifampicin concentrations were collected retrospectively from 62 patients treated with oral rifampicin 300 mg three times daily. Plasma concentration–time data were analysed using NONMEM to estimate population pharmacokinetic parameters. Demographic data, infection characteristics and antibiotics taken in addition to rifampicin antibiotics were investigated as covariates. Results A one‐compartment model, coupled to a transit absorption model, best described the rifampicin data. Fusidic acid coadministration was identified as a covariate in rifampicin pharmacokinetic parameters. The apparent clearance and apparent central volume of distribution mean values [95% confidence interval (CI)] were 5.1 1 h–1 (1.2, 8.2 1 h–1)/23.8 l (8.9, 38.7 l) and 13.7 1 h–1 (10.6, 18.0 1 h–1)/61.1 1 (40.8, 129.0 1) for patients with and without administration of fusidic acid, respectively. Interindividual variability (95% CI) in the apparent clearance and apparent central volume of distribution were 72.9% (49.5, 86.0%) and 59.1% (5.5, 105.4%), respectively. Residual variability was 2.3 mg l–1 (1.6, 2.6 mg l–1). Conclusion We developed the first population pharmacokinetic model of rifampicin in patients with osteoarticular infections. Our model demonstrated that fusidic acid affects rifampicin pharmacokinetics, leading to potential high drug exposure. This finding suggests that fusidic acid dosing regimens should be reconsidered.

Population pharmacokinetics of ertapenem in juvenile and old rats

Ertapenem is a parenteral broad‐spectrum carbapenem active against Gram‐negative pathogens, which has been approved for treatment of different infectious situations in adults and children. Favourable pharmacokinetics and pharmacodynamics have been established in young adults. In the elderly, dosing regimen adaptations are not recommended. Nevertheless, pharmacokinetic studies in paediatrics have not been published yet. The aim of this study was to document whether age influenced ertapenem disposition by comparing its pharmacokinetics in three groups of rats. Rats were separated into three groups: very young rats 21‐day‐old, 10‐week‐old and 7‐month‐old rats. A population pharmacokinetic model was built and evaluated, using the NONMEM software. Pharmacokinetic parameters, interindividual variability and residual variability were estimated. The final model was evaluated by a bootstrap procedure and visual predictive check. The ertapenem concentration–time data were best described by a one‐compartment model with zero‐order input and first‐order elimination. Effect of very young and old ages was estimated on central volume and clearance. Model evaluation indicated that the model was robust and parameter estimates were accurate. Central volume was found to be dependent on age and increase with age. Although the dosing regimen was weight adjusted, clearance was found to depend not only on age but also on weight. This study clearly documents changes in ertapenem pharmacokinetics according to group of age. These results suggest that paediatric dosing regimen cannot be directly extrapolated from a pharmacokinetic model in young adults unless it took into account age‐induced modifications.

Vancomycin: Predictive Performance of a Population Pharmacokinetic Model and Optimal Dose in Neonates and Young Infants

Introduction: Model evaluation is an important issue in population pharmacokinetic analyses. The objectives were to evaluate the predictive performance of previously published pediatric population pharmacokinetic models for vancomycin in a new data set and to propose an optimal dose to obtain a vancomycin concentration target. Methods: External evaluation was conducted for all the published models of vancomycin in neonates and young infants with a new data set of 70 patients. Bias and accuracy were calculated. Advanced analyses were performed to evaluate the predictive performance of the best model. This population pharmacokinetic analysis was performed to simulate doses of vancomycin according to the appropriate target concentration. Results: All models gave almost the same results, except 2 that were not acceptable. Nevertheless, the model described by Oudin et al presented the best results with a bias and accuracy of 4.0% and 27.8%, respectively. Simulations showed that the maintenance dose should be adjusted more precisely to each neonate based on his or her weight and serum creatinine value. Conclusion: Simulations have allowed the authors to describe new dosage schedules, and a chart was created to help clinicians to adapt dosage of vancomycin. Because of pharmacokinetic variability, vancomycin still requires therapeutic drug monitoring.

Ropivacaine Wound Infiltration for Pain Management After Breast Cancer Mastectomy: A Population Pharmacokinetic Analysis.

Ropivacaine continuous wound infusions (CWIs) are extensively used as a component of multimodal analgesia. The rational application of CWI of ropivacaine requires a thorough understanding of its pharmacokinetics to investigate the risk of potential systemic toxicity. A population pharmacokinetic (popPK) study was undertaken to describe the pharmacokinetics of ropivacaine CWI during 75 hours. Women undergoing a unilateral mastectomy were scheduled to receive CWI for 40 hours for postoperative analgesia. A 10‐mL ropivacaine 0.75% bolus followed by continuous infusion (400 mL of 0.2% ropivacaine at a flow rate of 10 mL/h) was administered via a multihole catheter placed on the major pectoral muscle. PopPK analysis was performed using the nonlinear mixed‐effects model. A 1‐compartment disposition model with an absorption compartment and a transit compartment for the infusion best describes the data (67 observations from 10 women). Population parameter estimates (between‐subject variability, %) are apparent central volume (V/F) 269 L (39.1%), apparent clearance (CL/F) 18.8 h‐1 (74.9%), and absorption rate (K12) 0.406 h‐1. The model predicted Cmax as 1.45 ± 0.80 μg/mL, which occurred in the 42.4th hour (39–45.9 hours). This popPK model describes the pharmacokinetics of ropivacaine during continuous wound infusion and confirms the safety profile of the present technique.

Analytical interference during cefepime therapeutic drug monitoring in intensive care patient: About a case report

β-lactams therapeutic drug monitoring (TDM) appears as an essential tool to ensure the achievement of pharmacokinetic-pharmacodynamic targets and prevent induced toxicity in intensive care unit patients. Indeed, those patients exhibit important pharmacokinetic variabilities that could lead to unpredictable plasma concentrations, potentially associated with poor clinical outcome, development of antibiotic resistance or increased side effects. Here, we report the case of a 48-year-old-patient admitted to intensive care unit and treated by cefepime using TDM. Due to inconsistency between observed cefepime plasma concentrations and patient clinical examination, investigations were started. After analytical tests, we highlighted an underlying analytical interference that overestimated cefepime plasma concentration with our in-house high performance liquid chromatography with ultraviolet detection (HPLC-UV) method. Only the inadequacy between plasmatic concentration and patient situation alerted pharmacologists and clinicians. As we found no previous case in literature, we believe this report must serve as an example of analytical limits that required pharmacologist awareness and expertise in TDM realization.

How to measure the net benefit of treatment

Estimating net benefit makes possible to clarify the basis for therapeutic decisions on an individual and collective level. This clarification is a must in shared medical decision-making and evidence-based medicine. Numerous methods are available, although none outweigh the others. The complex specifications of net benefit estimation should be tailored to the expectations of the central stakeholder, patient or society, and the unlimited range of potential contexts. The challenges, limitations, constraints and skills to be acquired by all stakeholders were discussed by the participants of the round table. They are described in this article, enabling key messages and guidelines to be presented. The essential priority is to ensure that all stakeholders receive the required training.