A population pharmacokinetic model for escitalopram and its major metabolite in depressive patients during the perinatal period: Prediction of infant drug exposure through breast milk

Weisskopf, Etienne; Guidi, Monia; Fischer, Cyril; Graz, Myriam Bickle; Beaufils, É.; Nguyen, Khai T.; Harari, Mathilde Morisod; Rouiller, Sylvie; Rothenburger, Sophie; Gaucherand, P.; Kassaï-Koupaï, Behrouz; Tolsa, Cristina Borradori; Epiney, Manuella; Tolsa, Jean-François; Vial, Yvan; Hascoët, Jean‐Michel; Claris, Olivier; Eap, Chin B.; Panchaud, Alice; Csajka, Chantal

doi:10.1111/bcp.14278

Cited by 18 publications

(21 citation statements)

References 27 publications

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“…Since multiple administrations of MFX were included in the study, each administration interval (24 h) was considered as a different occasion in the model. Additionally, an emptying effect was established in each mammary gland compartment in order to include the milking effect of the udder every 24 h [ 24 ].…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

“…The covariates weight, age, total milk production (pool of both mammary glands), milk production of healthy mammary gland, milk production of infected mammary gland and the day of treatment (as categorical covariate) were evaluated in order to determine the possible effects of these covariates on pharmacokinetic parameters of MFX. A covariate was included in the final model if presented statistical significance (p < 0.05), and reduced the IIV and the likelihood ratio tests (LRT) as −2•log-likelihood (−2LL), Akaike information criterion (AIC), and Bayesian information criterion (BIC) [24,25]. The pharmacokinetic parameters estimated by the model were: Ka (absorption con stant), Cl (clearance of the central compartment), V1 (volume of distribution of the centr compartment), Q (inter-compartmental clearance between central and peripheral com partments), V2 (volume of distribution of the peripheral compartment), QHG (inter-com partmental clearance between central and healthy mammary gland compartments), VH (volume of distribution of the healthy mammary gland), QIG (inter-compartmental clea ance between central and infected mammary gland compartments), and VIG (volume o distribution of the infected mammary gland compartment).…”

Section: Pharmacokinetic Modeling and Simulationmentioning

confidence: 99%

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PK/PD Analysis by Nonlinear Mixed-Effects Modeling of a Marbofloxacin Dose Regimen for Treatment of Goat Mastitis Produced by Coagulase-Negative Staphylococci

Lorenzutti

Vico

Serrano-Rodríguez

et al. 2021

Animals

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Coagulase-negative staphylococci are main pathogens that produce goat mastitis. Marbofloxacin is a third-generation fluoroquinolone approved for treat mastitis in animals. The objectives of this study were: (i) to determine the pharmacokinetics of marbofloxacin (10 mg/kg/24 h) in serum and milk administered intramuscularly for five days in goats with mastitis induced by coagulase-negative staphylococci; (ii) to characterize the concentration–effect relationship of marbofloxacin against coagulase-negative staphylococci in Mueller Hinton broth and goat milk; (iii) to determine AUC/MIC cutoff values of marbofloxacin, and (iv) to perform a PK/PD analysis to evaluate the efficacy of the dose regimen for the treatment of goat mastitis produced by coagulase-negative staphylococci. Marbofloxacin presented context-sensitive pharmacokinetics, influenced by the evolution of the disease, which decreased marbofloxacin disposition in serum and milk. Marbofloxacin showed a median (95% CI) fAUC/MIC values for MIC of 0.4 and 0.8 µg/mL of 26.66 (22.26–36.64) and 32.28 (26.57–48.35) related with −2 log10CFU/mL reduction; and 32.26 (24.81–81.50) and 41.39 (29.38–128.01) for −3 log10CFU/mL reduction in Mueller Hinton broth. For milk, −2 log10CFU/mL reduction was achieved with 41.48 (35.29–58.73) and 51.91 (39.09–131.63), and −3 log10CFU/mL reduction with 51.04 (41.6–82.1) and 65.65 (46.68–210.16). The proposed dose regimen was adequate for the treatment of goat mastitis produced by coagulase-negative staphylococci, resulting in microbiological and clinical cure of all animals. The animal model used in this study provided important pharmacokinetic information about the effect of the infection on the pharmacokinetics of marbofloxacin. Pharmacodynamic modeling showed that fAUC/MIC cutoff values were higher in goat milk compared with Mueller Hinton broth.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Pharmacokinetic Modeling and Simulationmentioning

confidence: 99%

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PK/PD Analysis by Nonlinear Mixed-Effects Modeling of a Marbofloxacin Dose Regimen for Treatment of Goat Mastitis Produced by Coagulase-Negative Staphylococci

Lorenzutti

Vico

Serrano-Rodríguez

et al. 2021

Animals

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“…Compared to the classic methods, population approaches allow for PK characterization using fewer or unequal numbers of observations per patient, irregularly measured concentrations, and concentrations without regard to steady‐state conditions, all opening up the possibility of gathering information, especially for populations who are challenging to study, like pregnant women or neonates 26,27 . Both P and NP methods can be used in both industrial drug development and optimization of clinical patient care and constitute the basis of model‐based TDM software programs.…”

Section: General Questions On Both Approachesmentioning

confidence: 99%

Parametric and Nonparametric Methods in Population Pharmacokinetics: Experts’ Discussion on Use, Strengths, and Limitations

Goutelle

Woillard

Buclin

et al. 2021

The Journal of Clinical Pharma

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Population pharmacokinetics consists of analyzing pharmacokinetic (PK) data collected in groups of individuals. Population PK is widely used to guide drug development and to inform dose adjustment via therapeutic drug monitoring and model‐informed precision dosing. There are 2 main types of population PK methods: parametric (P) and nonparametric (NP). The characteristics of P and NP population methods have been previously reviewed. The aim of this article is to answer some frequently asked questions that are often raised by scholars, clinicians, and researchers about P and NP population PK methods. The strengths and limitations of both approaches are explained, and the characteristics of the main software programs are presented. We also review the results of studies that compared the results of both approaches in the analysis of real data. This opinion article may be informative for potential users of population methods in PK and guide them in the selection and use of those tools. It also provides insights on future research in this area.

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“…The PK parameters have been compared in HIV-infected and uninfected psychiatric patients ( Courlet et al, 2019 ). A PopPK model of escitalopram in patients during the perinatal period has been established ( Weisskopf et al, 2020 ). The effect of age, weight, gender and CYP2C19 genotype on escitalopram exposure has been studied in American and Italian patients.…”

Section: Introductionmentioning

confidence: 99%

Population pharmacokinetics model for escitalopram in Chinese psychiatric patients: effect of CYP2C19 and age

et al. 2022

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Objective: To establish a population pharmacokinetic model in Chinese psychiatric patients to characterize escitalopram pharmacokinetic profile to identify factors influencing drug exposure, and through simulation to compare the results with the established therapeutic reference range.Methods: Demographic information, dosing regimen, CYP2C19 genotype, concomitant medications, and liver and kidney function indicators were retrospectively collected for inpatients taking escitalopram with therapeutic drug monitoring from 2018 to 2021. Nonlinear mixed-effects modeling was used to model the pharmacokinetic characteristics of escitalopram. Goodness-of-fit plots, bootstrapping, and normalized prediction distribution errors were used to evaluate the model. Simulation for different dosing regimens was based on the final estimations.Results: The study comprised 106 patients and 337 measurements of serum sample. A structural model with one compartment with first-order absorption and elimination described the data adequately. The population-estimated apparent volume of distribution and apparent clearance were 815 and 16.3 L/h, respectively. Age and CYP2C19 phenotype had a significant effect on the apparent clearance (CL/F). CL/F of escitalopram decreased with increased age, and CL/F of poor metabolizer patients was significantly lower than in extensive and immediate metabolizer patients. The final model-based simulation showed that the daily dose of adolescents with poor metabolizer might be as high as 15 mg or 20 mg and referring to the therapeutic range for adults may result in overdose and a high risk of adverse effects in older patients.Conclusion: A population pharmacokinetics model of escitalopram was successfully created for the Chinese population. Depending on the age of the patients, CYP2C19 genotype and serum drug concentrations throughout treatment are required for adequate individualization of dosing regimens. When developing a regimen for older patients, especially those who are poor metabolizers, vigilance is required.

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A population pharmacokinetic model for escitalopram and its major metabolite in depressive patients during the perinatal period: Prediction of infant drug exposure through breast milk

Cited by 18 publications

References 27 publications

PK/PD Analysis by Nonlinear Mixed-Effects Modeling of a Marbofloxacin Dose Regimen for Treatment of Goat Mastitis Produced by Coagulase-Negative Staphylococci

PK/PD Analysis by Nonlinear Mixed-Effects Modeling of a Marbofloxacin Dose Regimen for Treatment of Goat Mastitis Produced by Coagulase-Negative Staphylococci

Parametric and Nonparametric Methods in Population Pharmacokinetics: Experts’ Discussion on Use, Strengths, and Limitations

Population pharmacokinetics model for escitalopram in Chinese psychiatric patients: effect of CYP2C19 and age

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