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Stroe MS, Huang MC, Annaert P, Leys K, Smits A, Allegaert K, Van Bockstal L, Valenzuela A, Ayuso M, Van Ginneken C, Van Cruchten S. Drug Disposition in Neonatal Göttingen Minipigs: Exploring Effects of Perinatal Asphyxia and Therapeutic Hypothermia. Drug Metab Dispos 2024; 52:824-835. [PMID: 38906699 DOI: 10.1124/dmd.124.001677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 04/25/2024] [Accepted: 05/29/2024] [Indexed: 06/23/2024] Open
Abstract
Asphyxiated neonates often undergo therapeutic hypothermia (TH) to reduce morbidity and mortality. Since both perinatal asphyxia (PA) and TH influence physiology, altered pharmacokinetics (PK) and pharmacodynamics (PD) are expected. Given that TH is the standard of care for PA with moderate to severe hypoxic-ischemic encephalopathy, disentangling the effect of PA versus TH on PK/PD is not possible in clinical settings. However, animal models can provide insights into this matter. The (neonatal) Göttingen Minipig, the recommended strain for nonclinical drug development, was selected as translational model. Four drugs-midazolam (MDZ), fentanyl (FNT), phenobarbital (PHB), and topiramate (TPM)-were intravenously administered under four conditions: control (C), therapeutic hypothermia (TH), hypoxia (H), and hypoxia plus TH (H+TH). Each group included six healthy male neonatal Göttingen Minipigs anesthetized for 24 hours. Blood samples were drawn at 0 (predose) and 0.5, 2, 2.5, 3, 4, 4.5, 6, 8, 12, and 24 hours post drug administration. Drug plasma concentrations were determined using validated bioanalytical assays. The PK parameters were estimated through compartmental and noncompartmental PK analysis. The study showed a statistically significant decrease in FNT clearance (CL; 66% decrease), with an approximately threefold longer half-life (t1/2) in the TH group. The H+TH group showed a 17% reduction in FNT CL, with a 62% longer t1/2 compared with the C group; however, it was not statistically significant. Although not statistically significant, trends toward lower CL and longer t1/2 were observed in the TH and H+TH groups for MDZ and PHB. Additionally, TPM demonstrated a 28% decrease in CL in the H group compared with controls. SIGNIFICANCE STATEMENT: The overarching goal of this study using the neonatal Göttingen Minipig model was to disentangle the effects of systemic hypoxia and TH on PK using four model drugs. Such insights can subsequently be used to inform and develop a physiologically based pharmacokinetic model, which is useful for drug exposure prediction in human neonates.
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Affiliation(s)
- Marina-Stefania Stroe
- Comparative Perinatal Development, University of Antwerp, Antwerp, Belgium (M.S.-S., L.V.B., A.V., M.A., C.V.G., S.V.C.); Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (M.-C.H., P.A., K.L.); BioNotus GCV, Niel, Belgium (P.A.); Neonatal Intensive Care Unit, University Hospitals Leuven, Leuven, Belgium (A.S.); Departments of Development and Regeneration (A.S., K.A.) and Pharmaceutical and Pharmacological Sciences (K.A.), KU Leuven, Leuven, Belgium; and Department of Hospital Pharmacy, Erasmus MC, Rotterdam, the Netherlands (K.A.)
| | - Miao-Chan Huang
- Comparative Perinatal Development, University of Antwerp, Antwerp, Belgium (M.S.-S., L.V.B., A.V., M.A., C.V.G., S.V.C.); Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (M.-C.H., P.A., K.L.); BioNotus GCV, Niel, Belgium (P.A.); Neonatal Intensive Care Unit, University Hospitals Leuven, Leuven, Belgium (A.S.); Departments of Development and Regeneration (A.S., K.A.) and Pharmaceutical and Pharmacological Sciences (K.A.), KU Leuven, Leuven, Belgium; and Department of Hospital Pharmacy, Erasmus MC, Rotterdam, the Netherlands (K.A.)
| | - Pieter Annaert
- Comparative Perinatal Development, University of Antwerp, Antwerp, Belgium (M.S.-S., L.V.B., A.V., M.A., C.V.G., S.V.C.); Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (M.-C.H., P.A., K.L.); BioNotus GCV, Niel, Belgium (P.A.); Neonatal Intensive Care Unit, University Hospitals Leuven, Leuven, Belgium (A.S.); Departments of Development and Regeneration (A.S., K.A.) and Pharmaceutical and Pharmacological Sciences (K.A.), KU Leuven, Leuven, Belgium; and Department of Hospital Pharmacy, Erasmus MC, Rotterdam, the Netherlands (K.A.)
| | - Karen Leys
- Comparative Perinatal Development, University of Antwerp, Antwerp, Belgium (M.S.-S., L.V.B., A.V., M.A., C.V.G., S.V.C.); Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (M.-C.H., P.A., K.L.); BioNotus GCV, Niel, Belgium (P.A.); Neonatal Intensive Care Unit, University Hospitals Leuven, Leuven, Belgium (A.S.); Departments of Development and Regeneration (A.S., K.A.) and Pharmaceutical and Pharmacological Sciences (K.A.), KU Leuven, Leuven, Belgium; and Department of Hospital Pharmacy, Erasmus MC, Rotterdam, the Netherlands (K.A.)
| | - Anne Smits
- Comparative Perinatal Development, University of Antwerp, Antwerp, Belgium (M.S.-S., L.V.B., A.V., M.A., C.V.G., S.V.C.); Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (M.-C.H., P.A., K.L.); BioNotus GCV, Niel, Belgium (P.A.); Neonatal Intensive Care Unit, University Hospitals Leuven, Leuven, Belgium (A.S.); Departments of Development and Regeneration (A.S., K.A.) and Pharmaceutical and Pharmacological Sciences (K.A.), KU Leuven, Leuven, Belgium; and Department of Hospital Pharmacy, Erasmus MC, Rotterdam, the Netherlands (K.A.)
| | - Karel Allegaert
- Comparative Perinatal Development, University of Antwerp, Antwerp, Belgium (M.S.-S., L.V.B., A.V., M.A., C.V.G., S.V.C.); Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (M.-C.H., P.A., K.L.); BioNotus GCV, Niel, Belgium (P.A.); Neonatal Intensive Care Unit, University Hospitals Leuven, Leuven, Belgium (A.S.); Departments of Development and Regeneration (A.S., K.A.) and Pharmaceutical and Pharmacological Sciences (K.A.), KU Leuven, Leuven, Belgium; and Department of Hospital Pharmacy, Erasmus MC, Rotterdam, the Netherlands (K.A.)
| | - Lieselotte Van Bockstal
- Comparative Perinatal Development, University of Antwerp, Antwerp, Belgium (M.S.-S., L.V.B., A.V., M.A., C.V.G., S.V.C.); Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (M.-C.H., P.A., K.L.); BioNotus GCV, Niel, Belgium (P.A.); Neonatal Intensive Care Unit, University Hospitals Leuven, Leuven, Belgium (A.S.); Departments of Development and Regeneration (A.S., K.A.) and Pharmaceutical and Pharmacological Sciences (K.A.), KU Leuven, Leuven, Belgium; and Department of Hospital Pharmacy, Erasmus MC, Rotterdam, the Netherlands (K.A.)
| | - Allan Valenzuela
- Comparative Perinatal Development, University of Antwerp, Antwerp, Belgium (M.S.-S., L.V.B., A.V., M.A., C.V.G., S.V.C.); Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (M.-C.H., P.A., K.L.); BioNotus GCV, Niel, Belgium (P.A.); Neonatal Intensive Care Unit, University Hospitals Leuven, Leuven, Belgium (A.S.); Departments of Development and Regeneration (A.S., K.A.) and Pharmaceutical and Pharmacological Sciences (K.A.), KU Leuven, Leuven, Belgium; and Department of Hospital Pharmacy, Erasmus MC, Rotterdam, the Netherlands (K.A.)
| | - Miriam Ayuso
- Comparative Perinatal Development, University of Antwerp, Antwerp, Belgium (M.S.-S., L.V.B., A.V., M.A., C.V.G., S.V.C.); Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (M.-C.H., P.A., K.L.); BioNotus GCV, Niel, Belgium (P.A.); Neonatal Intensive Care Unit, University Hospitals Leuven, Leuven, Belgium (A.S.); Departments of Development and Regeneration (A.S., K.A.) and Pharmaceutical and Pharmacological Sciences (K.A.), KU Leuven, Leuven, Belgium; and Department of Hospital Pharmacy, Erasmus MC, Rotterdam, the Netherlands (K.A.)
| | - Chris Van Ginneken
- Comparative Perinatal Development, University of Antwerp, Antwerp, Belgium (M.S.-S., L.V.B., A.V., M.A., C.V.G., S.V.C.); Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (M.-C.H., P.A., K.L.); BioNotus GCV, Niel, Belgium (P.A.); Neonatal Intensive Care Unit, University Hospitals Leuven, Leuven, Belgium (A.S.); Departments of Development and Regeneration (A.S., K.A.) and Pharmaceutical and Pharmacological Sciences (K.A.), KU Leuven, Leuven, Belgium; and Department of Hospital Pharmacy, Erasmus MC, Rotterdam, the Netherlands (K.A.)
| | - Steven Van Cruchten
- Comparative Perinatal Development, University of Antwerp, Antwerp, Belgium (M.S.-S., L.V.B., A.V., M.A., C.V.G., S.V.C.); Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (M.-C.H., P.A., K.L.); BioNotus GCV, Niel, Belgium (P.A.); Neonatal Intensive Care Unit, University Hospitals Leuven, Leuven, Belgium (A.S.); Departments of Development and Regeneration (A.S., K.A.) and Pharmaceutical and Pharmacological Sciences (K.A.), KU Leuven, Leuven, Belgium; and Department of Hospital Pharmacy, Erasmus MC, Rotterdam, the Netherlands (K.A.)
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Reeve K, On BI, Havla J, Burns J, Gosteli-Peter MA, Alabsawi A, Alayash Z, Götschi A, Seibold H, Mansmann U, Held U. Prognostic models for predicting clinical disease progression, worsening and activity in people with multiple sclerosis. Cochrane Database Syst Rev 2023; 9:CD013606. [PMID: 37681561 PMCID: PMC10486189 DOI: 10.1002/14651858.cd013606.pub2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/09/2023]
Abstract
BACKGROUND Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system that affects millions of people worldwide. The disease course varies greatly across individuals and many disease-modifying treatments with different safety and efficacy profiles have been developed recently. Prognostic models evaluated and shown to be valid in different settings have the potential to support people with MS and their physicians during the decision-making process for treatment or disease/life management, allow stratified and more precise interpretation of interventional trials, and provide insights into disease mechanisms. Many researchers have turned to prognostic models to help predict clinical outcomes in people with MS; however, to our knowledge, no widely accepted prognostic model for MS is being used in clinical practice yet. OBJECTIVES To identify and summarise multivariable prognostic models, and their validation studies for quantifying the risk of clinical disease progression, worsening, and activity in adults with MS. SEARCH METHODS We searched MEDLINE, Embase, and the Cochrane Database of Systematic Reviews from January 1996 until July 2021. We also screened the reference lists of included studies and relevant reviews, and references citing the included studies. SELECTION CRITERIA We included all statistically developed multivariable prognostic models aiming to predict clinical disease progression, worsening, and activity, as measured by disability, relapse, conversion to definite MS, conversion to progressive MS, or a composite of these in adult individuals with MS. We also included any studies evaluating the performance of (i.e. validating) these models. There were no restrictions based on language, data source, timing of prognostication, or timing of outcome. DATA COLLECTION AND ANALYSIS Pairs of review authors independently screened titles/abstracts and full texts, extracted data using a piloted form based on the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS), assessed risk of bias using the Prediction Model Risk Of Bias Assessment Tool (PROBAST), and assessed reporting deficiencies based on the checklist items in Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD). The characteristics of the included models and their validations are described narratively. We planned to meta-analyse the discrimination and calibration of models with at least three external validations outside the model development study but no model met this criterion. We summarised between-study heterogeneity narratively but again could not perform the planned meta-regression. MAIN RESULTS We included 57 studies, from which we identified 75 model developments, 15 external validations corresponding to only 12 (16%) of the models, and six author-reported validations. Only two models were externally validated multiple times. None of the identified external validations were performed by researchers independent of those that developed the model. The outcome was related to disease progression in 39 (41%), relapses in 8 (8%), conversion to definite MS in 17 (18%), and conversion to progressive MS in 27 (28%) of the 96 models or validations. The disease and treatment-related characteristics of included participants, and definitions of considered predictors and outcome, were highly heterogeneous amongst the studies. Based on the publication year, we observed an increase in the percent of participants on treatment, diversification of the diagnostic criteria used, an increase in consideration of biomarkers or treatment as predictors, and increased use of machine learning methods over time. Usability and reproducibility All identified models contained at least one predictor requiring the skills of a medical specialist for measurement or assessment. Most of the models (44; 59%) contained predictors that require specialist equipment likely to be absent from primary care or standard hospital settings. Over half (52%) of the developed models were not accompanied by model coefficients, tools, or instructions, which hinders their application, independent validation or reproduction. The data used in model developments were made publicly available or reported to be available on request only in a few studies (two and six, respectively). Risk of bias We rated all but one of the model developments or validations as having high overall risk of bias. The main reason for this was the statistical methods used for the development or evaluation of prognostic models; we rated all but two of the included model developments or validations as having high risk of bias in the analysis domain. None of the model developments that were externally validated or these models' external validations had low risk of bias. There were concerns related to applicability of the models to our research question in over one-third (38%) of the models or their validations. Reporting deficiencies Reporting was poor overall and there was no observable increase in the quality of reporting over time. The items that were unclearly reported or not reported at all for most of the included models or validations were related to sample size justification, blinding of outcome assessors, details of the full model or how to obtain predictions from it, amount of missing data, and treatments received by the participants. Reporting of preferred model performance measures of discrimination and calibration was suboptimal. AUTHORS' CONCLUSIONS The current evidence is not sufficient for recommending the use of any of the published prognostic prediction models for people with MS in clinical routine today due to lack of independent external validations. The MS prognostic research community should adhere to the current reporting and methodological guidelines and conduct many more state-of-the-art external validation studies for the existing or newly developed models.
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Affiliation(s)
- Kelly Reeve
- Epidemiology, Biostatistics and Prevention Institute, University of Zürich, Zurich, Switzerland
| | - Begum Irmak On
- Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Joachim Havla
- lnstitute of Clinical Neuroimmunology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Jacob Burns
- Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
- Pettenkofer School of Public Health, Munich, Germany
| | | | - Albraa Alabsawi
- Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Zoheir Alayash
- Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
- Institute of Health Services Research in Dentistry, University of Münster, Muenster, Germany
| | - Andrea Götschi
- Epidemiology, Biostatistics and Prevention Institute, University of Zürich, Zurich, Switzerland
| | | | - Ulrich Mansmann
- Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
- Pettenkofer School of Public Health, Munich, Germany
| | - Ulrike Held
- Epidemiology, Biostatistics and Prevention Institute, University of Zürich, Zurich, Switzerland
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Valentine K, Kummick J. PICU Pharmacology. Pediatr Clin North Am 2022; 69:509-529. [PMID: 35667759 DOI: 10.1016/j.pcl.2022.01.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The care of the critically-ill child often includes medications used to optimize organ function, treat infections, and provide comfort. Pediatric pharmacology has some key differences that should be leveraged for safe pharmacologic management.
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Affiliation(s)
- Kevin Valentine
- Indiana University School of Medicine, Riley Hospital for Children, 705 Riley Hospital Drive, Suite 4900, Indianapolis, IN 46202, USA.
| | - Janelle Kummick
- Butler University College of Pharmacy and Health Sciences, Riley Hospital for Children, 705 Riley Hospital Drive, Room W6111, Indianapolis, IN 46202, USA
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Mørk ML, Andersen JT, Lausten-Thomsen U, Gade C. The Blind Spot of Pharmacology: A Scoping Review of Drug Metabolism in Prematurely Born Children. Front Pharmacol 2022; 13:828010. [PMID: 35242037 PMCID: PMC8886150 DOI: 10.3389/fphar.2022.828010] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 01/25/2022] [Indexed: 12/30/2022] Open
Abstract
The limit for possible survival after extremely preterm birth has steadily improved and consequently, more premature neonates with increasingly lower gestational age at birth now require care. This specialized care often include intensive pharmacological treatment, yet there is currently insufficient knowledge of gestational age dependent differences in drug metabolism. This potentially puts the preterm neonates at risk of receiving sub-optimal drug doses with a subsequent increased risk of adverse or insufficient drug effects, and often pediatricians are forced to prescribe medication as off-label or even off-science. In this review, we present some of the particularities of drug disposition and metabolism in preterm neonates. We highlight the challenges in pharmacometrics studies on hepatic drug metabolism in preterm and particularly extremely (less than 28 weeks of gestation) preterm neonates by conducting a scoping review of published literature. We find that >40% of included studies failed to report a clear distinction between term and preterm children in the presentation of results making direct interpretation for preterm neonates difficult. We present summarized findings of pharmacokinetic studies done on the major CYP sub-systems, but formal meta analyses were not possible due the overall heterogeneous approaches to measuring the phase I and II pathways metabolism in preterm neonates, often with use of opportunistic sampling. We find this to be a testament to the practical and ethical challenges in measuring pharmacokinetic activity in preterm neonates. The future calls for optimized designs in pharmacometrics studies, including PK/PD modeling-methods and other sample reducing techniques. Future studies should also preferably be a collaboration between neonatologists and clinical pharmacologists.
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Affiliation(s)
- Mette Louise Mørk
- Department of Clinical Pharmacology, Copenhagen University Hospital Bispebjerg and Frederiksberg, Copenhagen, Denmark
| | - Jón Trærup Andersen
- Department of Clinical Pharmacology, Copenhagen University Hospital Bispebjerg and Frederiksberg, Copenhagen, Denmark
| | - Ulrik Lausten-Thomsen
- Department of Neonatology, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | - Christina Gade
- Department of Clinical Pharmacology, Copenhagen University Hospital Bispebjerg and Frederiksberg, Copenhagen, Denmark
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5
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Knowledge gaps in late-onset neonatal sepsis in preterm neonates: a roadmap for future research. Pediatr Res 2022; 91:368-379. [PMID: 34497356 DOI: 10.1038/s41390-021-01721-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 08/13/2021] [Accepted: 08/17/2021] [Indexed: 12/16/2022]
Abstract
Late-onset neonatal sepsis (LONS) remains an important threat to the health of preterm neonates in the neonatal intensive care unit. Strategies to optimize care for preterm neonates with LONS are likely to improve survival and long-term neurocognitive outcomes. However, many important questions on how to improve the prevention, early detection, and therapy for LONS in preterm neonates remain unanswered. This review identifies important knowledge gaps in the management of LONS and describe possible methods and technologies that can be used to resolve these knowledge gaps. The availability of computational medicine and hypothesis-free-omics approaches give way to building bedside feedback tools to guide clinicians in personalized management of LONS. Despite advances in technology, implementation in clinical practice is largely lacking although such tools would help clinicians to optimize many aspects of the management of LONS. We outline which steps are needed to get possible research findings implemented on the neonatal intensive care unit and provide a roadmap for future research initiatives. IMPACT: This review identifies knowledge gaps in prevention, early detection, antibiotic, and additional therapy of late-onset neonatal sepsis in preterm neonates and provides a roadmap for future research efforts. Research opportunities are addressed, which could provide the means to fill knowledge gaps and the steps that need to be made before possible clinical use. Methods to personalize medicine and technologies feasible for bedside clinical use are described.
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6
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Soeorg H, Sverrisdóttir E, Andersen M, Lund TM, Sessa M. The PHARMACOM-EPI Framework for Integrating Pharmacometric Modelling Into Pharmacoepidemiological Research Using Real-World Data: Application to Assess Death Associated With Valproate. Clin Pharmacol Ther 2021; 111:840-856. [PMID: 34860420 DOI: 10.1002/cpt.2502] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Accepted: 11/17/2021] [Indexed: 01/14/2023]
Abstract
In pharmacoepidemiology, it is usually expected that the observed association should be directly or indirectly related to the pharmacological effects of the drug/s under investigation. Pharmacological effects are, in turn, strongly connected to the pharmacokinetic and pharmacodynamic properties of a drug, which can be characterized and investigated using pharmacometric models. Recently, the use of pharmacometrics has been proposed to provide pharmacological substantiation of pharmacoepidemiological findings derived from real-world data. However, validated frameworks suggesting how to combine these two disciplines for the aforementioned purpose are missing. Therefore, we propose PHARMACOM-EPI, a framework that provides a structured approach on how to identify, characterize, and apply pharmacometric models with practical details on how to choose software, format dataset, handle missing covariates/dosing data, how to perform the external evaluation of pharmacometric models in real-world data, and how to provide pharmacological substantiation of pharmacoepidemiological findings. PHARMACOM-EPI was tested in a proof-of-concept study to pharmacologically substantiate death associated with valproate use in the Danish population aged ≥ 65 years. Pharmacological substantiation of death during a follow-up period of 1 year showed that in all individuals who died (n = 169) individual predictions were within the subtherapeutic range compared with 52.8% of those who did not die (n = 1,084). Of individuals who died, 66.3% (n = 112) had a cause of death possibly related to valproate and 33.7% (n = 57) with well-defined cause of death unlikely related to valproate. This proof-of-concept study showed that PHARMACOM-EPI was able to provide pharmacological substantiation for death associated with valproate use in the study population.
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Affiliation(s)
- Hiie Soeorg
- Department of Drug Design and Pharmacology, Pharmacovigilance Research Center, University of Copenhagen, Copenhagen, Denmark.,Department of Drug Design and Pharmacology, Pharmacometrics Research Group, University of Copenhagen, Copenhagen, Denmark
| | - Eva Sverrisdóttir
- Department of Drug Design and Pharmacology, Pharmacometrics Research Group, University of Copenhagen, Copenhagen, Denmark
| | - Morten Andersen
- Department of Drug Design and Pharmacology, Pharmacovigilance Research Center, University of Copenhagen, Copenhagen, Denmark
| | - Trine Meldgaard Lund
- Department of Drug Design and Pharmacology, Pharmacometrics Research Group, University of Copenhagen, Copenhagen, Denmark
| | - Maurizio Sessa
- Department of Drug Design and Pharmacology, Pharmacovigilance Research Center, University of Copenhagen, Copenhagen, Denmark
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Lommerse J, Plock N, Cheung SYA, Sachs JR. V 2 ACHER: Visualization of complex trial data in pharmacometric analyses with covariates. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2021; 10:1092-1106. [PMID: 34242494 PMCID: PMC8452296 DOI: 10.1002/psp4.12679] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 05/17/2021] [Accepted: 05/28/2021] [Indexed: 11/06/2022]
Abstract
Pharmacometric models can enhance clinical decision making, with covariates exposing potential contributions to variability of subpopulation characteristics, for example, demographics or disease status. Intuitive visualization of models with multiple covariates is needed because sparsity of data in visualizations trellised by covariate values can raise concerns about the credibility of the underlying model. V2 ACHER, introduced here, is a stepwise transformation of data that can be applied to a variety of static (non-ordinary-differential-equation-based) pharmacometric analyses. This work uses four examples of increasing complexity to show how the transformation elucidates the relationship between observations and model results and how it can also be used in visual predictive checks to confirm the quality of a model. V2 ACHER facilitates consistent, intuitive, single-plot visualization of a multicovariate model with a complex data set, thereby enabling easier model communication for modelers and for cross-functional development teams and facilitating confident use in support of decisions.
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Affiliation(s)
- Jos Lommerse
- Certara Strategic Consulting, Princeton, NJ, USA
| | - Nele Plock
- Certara Strategic Consulting, Princeton, NJ, USA
| | | | - Jeffrey R Sachs
- Pharmacokinetics, Pharmacodynamics, and Drug Metabolism-Quantitative Pharmacology and Pharmacometrics, Research Laboratories of Merck & Co., Inc., Kenilworth, NJ, USA
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8
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Völler S, Flint RB, Simons SHP, Knibbe CAJ. Comment on: "Preterm Physiologically Based Pharmacokinetic Model, Part I and Part II". Clin Pharmacokinet 2021; 60:677-679. [PMID: 33713305 PMCID: PMC8113170 DOI: 10.1007/s40262-021-00993-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/28/2021] [Indexed: 02/06/2023]
Affiliation(s)
- Swantje Völler
- Leiden Academic Centre for Drug Research, Pharmacy, Leiden University, Leiden, The Netherlands.
| | - Robert B Flint
- Division of Neonatology, Department of Pediatrics, Erasmus Medical Center, Sophia Children's Hospital, Rotterdam, The Netherlands.,Department of Hospital Pharmacy, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Sinno H P Simons
- Division of Neonatology, Department of Pediatrics, Erasmus Medical Center, Sophia Children's Hospital, Rotterdam, The Netherlands
| | - Catherijne A J Knibbe
- Leiden Academic Centre for Drug Research, Systems Biomedicine and Pharmacology, Leiden University, Leiden, The Netherlands.,Department of Clinical Pharmacy, St Antonius Hospital, Nieuwegein, The Netherlands
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9
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Ryu S, Jung WJ, Jiao Z, Chae JW, Yun HY. External evaluation of the predictive performance of seven population pharmacokinetic models for phenobarbital in neonates. Br J Clin Pharmacol 2021; 87:3878-3889. [PMID: 33638184 DOI: 10.1111/bcp.14803] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 02/09/2021] [Accepted: 02/13/2021] [Indexed: 02/06/2023] Open
Abstract
AIM Several studies have reported population pharmacokinetic models for phenobarbital (PB), but the predictive performance of these models has not been well documented. This study aims to do external evaluation of the predictive performance in published pharmacokinetic models. METHODS Therapeutic drug monitoring data collected in neonates and young infants treated with PB for seizure control was used for external evaluation. A literature review was conducted through PubMed to identify population pharmacokinetic models. Prediction- and simulation-based diagnostics, and Bayesian forecasting were performed for external evaluation. The incorporation of allometric scaling for body size and maturation factors into the published models was also tested for prediction improvement. RESULTS A total of 79 serum concentrations from 28 subjects were included in the external dataset. Seven population pharmacokinetic studies of PB were identified as relevant in the literature search and included for our evaluation. The model by Voller et al showed the best performance concerning prediction-based evaluation. In simulation-based analyses, the normalized prediction distribution error of two models (those of Shellhaas et al and Marsot et al) obeyed a normal distribution. Bayesian forecasting with more than one observation improved predictive capability. Incorporation of both allometric size scaling and maturation function generally enhanced the predictive performance, with improvement as observed in the model of Vucicevic et al. CONCLUSIONS: The predictive performance of published pharmacokinetic models of PB was diverse. Bayesian forecasting and incorporation of both size and maturation factors could improve the predictability of the models for neonates.
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Affiliation(s)
- Sunae Ryu
- College of Pharmacy, Chungnam National University, Daejeon, Republic of Korea.,National Institute of Food and Drug Safety Evaluation, Ministry of Food and Drug Safety, Cheongju, Republic of Korea
| | - Woo Jin Jung
- College of Pharmacy, Chungnam National University, Daejeon, Republic of Korea
| | - Zheng Jiao
- Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, P.R. China
| | - Jung-Woo Chae
- College of Pharmacy, Chungnam National University, Daejeon, Republic of Korea
| | - Hwi-Yeol Yun
- College of Pharmacy, Chungnam National University, Daejeon, Republic of Korea
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10
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What is the Best Predictor of Phenobarbital Pharmacokinetics to Use for Initial Dosing in Neonates? Pharmaceutics 2021; 13:pharmaceutics13030301. [PMID: 33668911 PMCID: PMC7996486 DOI: 10.3390/pharmaceutics13030301] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2021] [Revised: 02/21/2021] [Accepted: 02/22/2021] [Indexed: 11/17/2022] Open
Abstract
Phenobarbital is a first-line treatment of various seizure types in newborns. Dosage individualization maximizing the proportion of patients with drug levels in therapeutic range or sufficient treatment response is still challenging. The aim of this review was to summarize the available evidence on phenobarbital pharmacokinetics in neonates and to identify its possible covariates suitable for individualization of initial drug dosing. Several covariates have been considered: body weight and height, body surface area, gestational and postnatal age, laboratory parameters of renal and hepatic functions, asphyxia, therapeutic hypothermia, extracorporeal membrane oxygenation (ECMO), drug interactions, and genetic polymorphisms. The most frequently studied and well-founded covariate for the estimation of phenobarbital dosing is actual body weight. Loading dose of 15-20 mg/kg followed by a maintenance dose of 3-5 mg/kg/day seems to be accurate. However, the evidence for the other covariates with respect to dosing individualization is not sufficient. Doses at the lower limit of suggested range should be preferred in patients with severe asphyxia, while the upper limit of the range should be targeted in neonates receiving ECMO support.
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11
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van Hoogdalem MW, McPhail BT, Hahn D, Wexelblatt SL, Akinbi HT, Vinks AA, Mizuno T. Pharmacotherapy of neonatal opioid withdrawal syndrome: a review of pharmacokinetics and pharmacodynamics. Expert Opin Drug Metab Toxicol 2020; 17:87-103. [PMID: 33049155 DOI: 10.1080/17425255.2021.1837112] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
INTRODUCTION Neonatal opioid withdrawal syndrome (NOWS) often arises in infants born to mothers who used opioids during pregnancy. Morphine, methadone, and buprenorphine are the most common first-line treatments, whereas clonidine and phenobarbital are generally reserved for adjunctive therapy. These drugs exhibit substantial pharmacokinetic (PK) and pharmacodynamic (PD) variability. Current pharmacological treatments for NOWS are based on institutional protocols and largely rely on empirical treatment of patient symptoms. AREAS COVERED This article reviews the PK/PD of NOWS pharmacotherapies with a focus on the implication of physiological development and maturation. Body size-standardized clearance is consistently low in neonates, except for methadone. This can be ascribed to underdeveloped metabolic and elimination pathways. The effects of pharmacogenetics have been clarified especially for morphine. The PK/PD relationship of medications used in the treatment of NOWS is generally understudied. EXPERT OPINION Providing an appropriate opioid dose in neonates is challenging. Advancements in quantitative pharmacology and PK/PD modeling approaches facilitate identification of key factors driving PK/PD variability and characterization of exposure-response relationships. PK/PD model-informed simulations have been widely employed to define age-appropriate pediatric dosing regimens. The model-informed approach holds promise to aid more rational use of medications in the treatment of NOWS.
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Affiliation(s)
- Matthijs W van Hoogdalem
- Division of Clinical Pharmacology, Cincinnati Children's Hospital Medical Center , Cincinnati, OH, USA.,James L. Winkle College of Pharmacy, University of Cincinnati , Cincinnati, OH, USA
| | - Brooks T McPhail
- Division of Clinical Pharmacology, Cincinnati Children's Hospital Medical Center , Cincinnati, OH, USA.,School of Medicine Greenville, University of South Carolina , Greenville, SC, USA
| | - David Hahn
- Division of Clinical Pharmacology, Cincinnati Children's Hospital Medical Center , Cincinnati, OH, USA
| | - Scott L Wexelblatt
- Perinatal Institute, Division of Neonatology, Cincinnati Children's Hospital Medical Center , Cincinnati, OH, USA.,Department of Pediatrics, College of Medicine, University of Cincinnati , Cincinnati, OH, USA.,Center for Addiction Research, College of Medicine, University of Cincinnati , Cincinnati, OH, USA
| | - Henry T Akinbi
- Perinatal Institute, Division of Neonatology, Cincinnati Children's Hospital Medical Center , Cincinnati, OH, USA.,Department of Pediatrics, College of Medicine, University of Cincinnati , Cincinnati, OH, USA
| | - Alexander A Vinks
- Division of Clinical Pharmacology, Cincinnati Children's Hospital Medical Center , Cincinnati, OH, USA.,Department of Pediatrics, College of Medicine, University of Cincinnati , Cincinnati, OH, USA.,Center for Addiction Research, College of Medicine, University of Cincinnati , Cincinnati, OH, USA
| | - Tomoyuki Mizuno
- Division of Clinical Pharmacology, Cincinnati Children's Hospital Medical Center , Cincinnati, OH, USA.,Department of Pediatrics, College of Medicine, University of Cincinnati , Cincinnati, OH, USA.,Center for Addiction Research, College of Medicine, University of Cincinnati , Cincinnati, OH, USA
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12
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Pokorná P, Michaličková D, Völler S, Hronová K, Tibboel D, Slanař O, Krekels EH. Severity parameters for asphyxia or hypoxic-ischemic encephalopathy do not explain inter-individual variability in the pharmacokinetics of phenobarbital in newborns treated with therapeutic hypothermia. Minerva Pediatr (Torino) 2020; 74:107-115. [PMID: 33107271 DOI: 10.23736/s2724-5276.20.05740-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
BACKGROUND The current study uses a population modeling approach to evaluate and quantify the impact of severity of asphyxia and hypoxic-ischemic encephalopathy (HIE) on the pharmacokinetics of phenobarbital in asphyxiated newborns treated with therapeutic hypothermia. METHODS Included newborns received phenobarbital (the TOBY trial protocol). 120 plasma samples were available from 50 newborns, median (IQR) weight 3.3 (2.8-3.5) kg and gestational age 39 (39-40) weeks. NONMEM® version 7.2 was used for the data analysis. Age, body weight, sex, concomitant medications, kidney and liver function markers, as well as severity parameters of asphyxia and HIE were tested as potential covariates of pharmacokinetics of phenobarbital. Severe asphyxia was defined as pH of arterial umbilical cord blood ≤7.1 and Apgar 5 ≤5, and severe HIE was defined as time to normalization of amplitude-integrated electroencephalography (aEEG) >24 h. RESULTS Weight was found to be the only statistically significant covariate for the volume of distribution. At weight of 1 kg volume of distribution was 0.91 L and for every additional kg it increased in 0.91 L. Clearance was 0.00563 L/h. No covariates were statistically significant for the clearance of phenobarbital. CONCLUSIONS Phenobarbital dose adjustments are not indicated in the studied population, irrespective of the severity of asphyxia or HIE.
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Affiliation(s)
- Pavla Pokorná
- Department of Pediatrics and Inherited Metabolic Disorders, General University Hospital.,st Faculty of Medicine, Charles University, Prague, Czech Republic.,Institute of Pharmacology, General University Hospital.,st Faculty of Medicine, Charles University, Prague, Czech Republic
| | | | - Swantje Völler
- st Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Karolina Hronová
- st Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Dick Tibboel
- Department of Pediatrics and Inherited Metabolic Disorders, General University Hospital.,Institute of Pharmacology, General University Hospital
| | - Ondřej Slanař
- st Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Elke H Krekels
- st Faculty of Medicine, Charles University, Prague, Czech Republic
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13
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Pharmacokinetic variability of phenobarbital: a systematic review of population pharmacokinetic analysis. Eur J Clin Pharmacol 2020; 77:291-309. [PMID: 33078242 DOI: 10.1007/s00228-020-03011-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Accepted: 10/01/2020] [Indexed: 01/14/2023]
Abstract
AIMS AND BACKGROUND Population pharmacokinetics with Bayesian forecasting provides for an effective approach when individualized drug dosing, while phenobarbital is a narrow therapeutic index drug that requires therapeutic drug monitoring. To date, several population pharmacokinetic models have been developed for phenobarbital, these showing a number of significant predictors of phenobarbital clearance and volume of distribution. We have therefore conducted a systematic review to summarize how these predictors affect phenobarbital pharmacokinetics as well as their relationships with pharmacokinetic parameters. METHOD A systematic search for studies of phenobarbital population pharmacokinetics that were carried out in humans and that employed a nonlinear mixed-effect approaches was made using the PubMed, Scopus, CINAHL Complete, and ScienceDirect databases. The search covered the period from these databases' inception to March 2020. RESULTS Eighteen studies were included in this review, all of which used a one-compartment structure. The estimated phenobarbital clearance and volume of distribution ranged from 0.0034 to 0.0104 L/h/kg and 0.37 to 1.21 L/kg, respectively, with body weight, age, and concomitant antiepileptic drugs being the three most frequently identified predictors of clearance. Most models were validated through the use of an advanced internal approach. CONCLUSION Phenobarbital clearance may be predicted from previously developed population pharmacokinetic models and their significant covariate-parameter relationships along with Bayesian forecasting. However, when applying these models in a target population, an external evaluation of these models using the target population is warranted, and it is recommended that future research be conducted to investigate the link between population pharmacokinetics and pharmacodynamics.
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14
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Thibault C, Massey SL, Abend NS, Naim MY, Zoraian A, Zuppa AF. Population Pharmacokinetics of Phenobarbital in Neonates and Infants on Extracorporeal Membrane Oxygenation and the Influence of Concomitant Renal Replacement Therapy. J Clin Pharmacol 2020; 61:378-387. [PMID: 32960986 DOI: 10.1002/jcph.1743] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 08/25/2020] [Indexed: 01/20/2023]
Abstract
The objective of this study was to describe the pharmacokinetics (PK) of intravenous phenobarbital in neonates and infants on extracorporeal membrane oxygenation (ECMO) and to provide dosing recommendations in this population. We performed a retrospective single-center PK study of phenobarbital in neonates and infants on ECMO between January 1, 2014, and December 31, 2018. We developed a population PK model using nonlinear mixed-effects modeling, performed simulations using the final PK parameters, and determined optimal dosing based on attainment of peak and trough concentrations between 20 and 40 mg/L. We included 35 subjects with a median (range) age and weight of 14 days (1-154 days) and 3.4 kg (1.6-8.1 kg), respectively. A total of 194 samples were included in the analysis. Five children (14%) contributing 30 samples (16%) were supported by continuous venovenous hemodiafiltration (CVVHDF). A 1-compartment model best described the data. Typical clearance and volume of distribution for a 3.4-kg infant were 0.038 L/h and 3.83 L, respectively. Clearance increased with age and CVVHDF. Although on ECMO, phenobarbital clearance in children on CVVHDF was 6-fold higher than clearance in children without CVVHDF. In typical subjects, a loading dose of 30 mg/kg/dose followed by maintenance doses of 6-7 mg/kg/day administered as divided doses every 12 hours reached goal concentrations. Age did not impact dosing recommendations. However, higher doses were needed in children on CVVHDF. We strongly recommend therapeutic drug monitoring in children on renal replacement therapy (excluding slow continuous ultrafiltration) while on ECMO.
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Affiliation(s)
- Céline Thibault
- Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Center for Clinical Pharmacology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Department of Pediatrics, CHU Sainte-Justine, Montreal, QC, Canada
| | - Shavonne L Massey
- Departments of Neurology and Pediatrics, Children's Hospital of Philadelphia and the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Nicholas S Abend
- Departments of Neurology and Pediatrics, Children's Hospital of Philadelphia and the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Maryam Y Naim
- Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Alexandra Zoraian
- Center for Clinical Pharmacology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Athena F Zuppa
- Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Center for Clinical Pharmacology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
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15
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Rapid Increase in Clearance of Phenobarbital in Neonates on Extracorporeal Membrane Oxygenation: A Pilot Retrospective Population Pharmacokinetic Analysis. Pediatr Crit Care Med 2020; 21:e707-e715. [PMID: 32639476 DOI: 10.1097/pcc.0000000000002402] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVES This study characterizes the changes in the pharmacokinetics of phenobarbital associated with extracorporeal membrane oxygenation treatment in neonates, to illustrate our findings and provide guidance on dosing. DESIGN Retrospective pilot population pharmacokinetic analysis. SETTING Neonatal ICU. PATIENTS Thirteen critically ill neonates (birth body weight, 3.21 kg [2.65-3.72 kg]; postnatal age at start of treatment: 2 d [0-7 d]; gestational age: 38 wk [38-41 wk]) receiving venovenous or venoarterial extracorporeal membrane oxygenation. INTERVENTIONS Phenobarbital administered in a loading dose of 7.5 mg/kg (8.5-16 mg/kg) and maintenance dose of 6.9 mg/kg/d (4.5-8.5 mg/kg/d). MEASUREMENTS AND MAIN RESULTS Therapeutic drug monitoring data were available, yielding 5, 31, and 19 phenobarbital concentrations before, during, and after extracorporeal membrane oxygenation, respectively. Population pharmacokinetic analysis was performed using NONMEM 7.3.0 (ICON Development Solutions, Ellicott City, MD). Maturation functions for clearance and volume of distribution were obtained from literature. In a one-compartment model, clearance and volume of distribution for a typical neonate off extracorporeal membrane oxygenation and with a median birth body weight (3.21 kg) at median postnatal age (2 d) were 0.0096 L/hr (relative SE = 11%)) and 2.72 L (16%), respectively. During extracorporeal membrane oxygenation, clearance was found to linearly increase with time. Upon decannulation, phenobarbital clearance initially decreased and subsequently increased slowly driven by maturation. Extracorporeal membrane oxygenation-related changes in volume of distribution could not be identified, possibly due to sparse data collection shortly after extracorporeal membrane oxygenation start. According to the model, target attainment is achieved in the first 12 days of extracorporeal membrane oxygenation with a regimen of a loading dose of 20 mg/kg and a maintenance dose of 4 mg/kg/d divided in two doses with an increase of 0.25 mg/kg every 12 hours during extracorporeal membrane oxygenation treatment. CONCLUSIONS We found a time-dependent increase in phenobarbital clearance during the first 12 days of extracorporeal membrane oxygenation treatment in neonates, which results in continuously decreasing phenobarbital exposure and increases the risk of therapeutic failure over time. Due to high unexplained variability, frequent and repeated therapeutic drug monitoring should be considered even with the model-derived regimen.
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16
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Abstract
OBJECTIVES To develop a population pharmacokinetic model for IV phenobarbital in neonates following cardiac surgery and perform simulations to identify optimal dosing regimens. DESIGN Retrospective single-center pharmacokinetic study. SETTING Cardiac ICU at Children's Hospital of Philadelphia. PATIENTS Consecutive neonates who received greater than or equal to one dose of IV phenobarbital and had greater than or equal to one phenobarbital concentration drawn per standard of care from June 15, 2012, to October 15, 2018. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS A population pharmacokinetic model was developed using nonlinear mixed-effects modeling. Simulations were performed using the final model variables. Optimal phenobarbital loading doses were determined based on attainment of peak and maintenance concentrations between 20 and 40 mg/L. A total of 37 neonates contributed 159 pharmacokinetic samples. The median (range) weight, postmenstrual age, and postnatal age were 3.2 kg (1.3-3.8), 39 2/7 weeks (28 2/7 to 42 6/7), and 5 days (0-26 d), respectively. Twelve patients (32%) were on extracorporeal membrane oxygenation. An one-compartment model best described the data. The final population pharmacokinetic model included (1) weight and postnatal age for clearance and (2) weight, extracorporeal membrane oxygenation, and albumin for volume of distribution. In neonates not on extracorporeal membrane oxygenation, loading doses of 30 and 20 mg/kg reached goal concentration with albumin values less than or equal to 3 and 3.5 mg/dL, respectively. Loading doses of 30 mg/kg reached goal concentration on extracorporeal membrane oxygenation regardless of albumin values. Maintenance doses of 4-5 mg/kg/d reached goal concentration in all neonates. CONCLUSIONS In neonates following cardiac surgery, phenobarbital clearance increased with postnatal age. Volume of distribution increased with extracorporeal membrane oxygenation and lower albumin values. Loading doses of 30 mg/kg on extracorporeal membrane oxygenation and 20-30 mg/kg without extracorporeal membrane oxygenation were needed to reach goal concentration based on simulations.
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17
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Engbers AGJ, Flint RB, Völler S, de Klerk JCA, Reiss IKM, Andriessen P, Liem KD, Degraeuwe PLJ, Croubels S, Millecam J, Allegaert K, Simons SHP, Knibbe CAJ. Enantiomer specific pharmacokinetics of ibuprofen in preterm neonates with patent ductus arteriosus. Br J Clin Pharmacol 2020; 86:2028-2039. [PMID: 32250464 PMCID: PMC7495289 DOI: 10.1111/bcp.14298] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Revised: 03/11/2020] [Accepted: 03/21/2020] [Indexed: 02/06/2023] Open
Abstract
Aims Racemic ibuprofen is widely used for the treatment of preterm neonates with patent ductus arteriosus. Currently used bodyweight‐based dosing guidelines are based on total ibuprofen, while only the S‐enantiomer of ibuprofen is pharmacologically active. We aimed to optimize ibuprofen dosing for preterm neonates of different ages based on an enantiomer‐specific population pharmacokinetic model. Methods We prospectively collected 210 plasma samples of 67 preterm neonates treated with ibuprofen for patent ductus arteriosus (median gestational age [GA] 26 [range 24–30] weeks, median body weight 0.83 [0.45–1.59] kg, median postnatal age [PNA] 3 [1–12] days), and developed a population pharmacokinetic model for S‐ and R‐ibuprofen. Results We found that S‐ibuprofen clearance (CLS, 3.98 mL/h [relative standard error {RSE} 8%]) increases with PNA and GA, with exponents of 2.25 (RSE 6%) and 5.81 (RSE 15%), respectively. Additionally, a 3.11‐fold higher CLS was estimated for preterm neonates born small for GA (RSE 34%). Clearance of R‐ibuprofen was found to be high compared to CLS (18 mL/h [RSE 24%]), resulting in a low contribution of R‐ibuprofen to total ibuprofen exposure. Current body weight was identified as covariate on both volume of distribution of S‐ibuprofen and R‐ibuprofen. Conclusion S‐ibuprofen clearance shows important maturation, especially with PNA, resulting in an up to 3‐fold increase in CLS during a 3‐day treatment regimen. This rapid increase in clearance needs to be incorporated in dosing guidelines by adjusting the dose for every day after birth to achieve equal ibuprofen exposure.
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Affiliation(s)
- Aline G J Engbers
- Division of Systems Biomedicine & Pharmacology, LACDR, Leiden University, Leiden, the Netherlands.,Department of Paediatrics, Division of Neonatology, Erasmus UMC - Sophia Children's Hospital, Rotterdam, the Netherlands
| | - Robert B Flint
- Department of Paediatrics, Division of Neonatology, Erasmus UMC - Sophia Children's Hospital, Rotterdam, the Netherlands.,Department of Pharmacy, Radboud University Medical Centre, Nijmegen, the Netherlands.,Department of Pharmacy, Erasmus MC, Rotterdam, The Netherlands
| | - Swantje Völler
- Division of Systems Biomedicine & Pharmacology, LACDR, Leiden University, Leiden, the Netherlands.,Division of BioTherapeutics, LACDR, Leiden University, Leiden, the Netherlands
| | - Johan C A de Klerk
- Department of Paediatrics, Division of Neonatology, Erasmus UMC - Sophia Children's Hospital, Rotterdam, the Netherlands
| | - Irwin K M Reiss
- Department of Paediatrics, Division of Neonatology, Erasmus UMC - Sophia Children's Hospital, Rotterdam, the Netherlands
| | - Peter Andriessen
- Department of Neonatology, Máxima Medical Centre, Veldhoven, the Netherlands
| | - Kian D Liem
- Department of Neonatology, Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Pieter L J Degraeuwe
- Department of Paediatrics, Division of Neonatology, Maastricht University Medical Centre, the Netherlands
| | - Siska Croubels
- Department of Pharmacology, Toxicology and Biochemistry, Faculty of Veterinary Medicine, Ghent University, Belgium
| | - Joske Millecam
- Department of Pharmacology, Toxicology and Biochemistry, Faculty of Veterinary Medicine, Ghent University, Belgium
| | - Karel Allegaert
- Department of Paediatrics, Division of Neonatology, Erasmus UMC - Sophia Children's Hospital, Rotterdam, the Netherlands.,Department of Development and Regeneration, KU Leuven, Belgium
| | - Sinno H P Simons
- Department of Paediatrics, Division of Neonatology, Erasmus UMC - Sophia Children's Hospital, Rotterdam, the Netherlands
| | - Catherijne A J Knibbe
- Division of Systems Biomedicine & Pharmacology, LACDR, Leiden University, Leiden, the Netherlands.,Department of Paediatrics, Division of Neonatology, Erasmus UMC - Sophia Children's Hospital, Rotterdam, the Netherlands.,Department of Clinical Pharmacy, St. Antonius Hospital, Nieuwegein, the Netherlands
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18
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Abstract
In covariate (sub)models of population pharmacokinetic models, most covariates are normalized to the median value; however, for body weight, normalization to 70 kg or 1 kg is often applied. In this article, we illustrate the impact of normalization weight on the precision of population clearance (CLpop) parameter estimates. The influence of normalization weight (70, 1 kg or median weight) on the precision of the CLpop estimate, expressed as relative standard error (RSE), was illustrated using data from a pharmacokinetic study in neonates with a median weight of 2.7 kg. In addition, a simulation study was performed to show the impact of normalization to 70 kg in pharmacokinetic studies with paediatric or obese patients. The RSE of the CLpop parameter estimate in the neonatal dataset was lowest with normalization to median weight (8.1%), compared with normalization to 1 kg (10.5%) or 70 kg (48.8%). Typical clearance (CL) predictions were independent of the normalization weight used. Simulations showed that the increase in RSE of the CLpop estimate with 70 kg normalization was highest in studies with a narrow weight range and a geometric mean weight away from 70 kg. When, instead of normalizing with median weight, a weight outside the observed range is used, the RSE of the CLpop estimate will be inflated, and should therefore not be used for model selection. Instead, established mathematical principles can be used to calculate the RSE of the typical CL (CLTV) at a relevant weight to evaluate the precision of CL predictions.
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19
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O’Hara K, Martin JH, Schneider JJ. Barriers and Challenges in Performing Pharmacokinetic Studies to Inform Dosing in the Neonatal Population. PHARMACY 2020; 8:E16. [PMID: 32033361 PMCID: PMC7151681 DOI: 10.3390/pharmacy8010016] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Revised: 01/31/2020] [Accepted: 02/02/2020] [Indexed: 12/22/2022] Open
Abstract
A number of barriers and challenges must be overcome in order to conduct the pharmacokinetic studies that are urgently needed to inform the selection and dosing of medication in neonates. However, overcoming these barriers can be difficult. This review outlines the common barriers researchers are confronted with, including issues with ethics approval and consent, study design for pharmacokinetic studies and the ability to measure the drug concentrations in the blood samples obtained. Strategies to overcome these challenges are also proposed.
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Affiliation(s)
- Kate O’Hara
- Discipline of Clinical Pharmacology, School of Medicine, University of Newcastle, Hunter Medical Research Institute Newcastle, Newcastle 2308, Australia; (J.H.M.); (J.J.S.)
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20
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Raffaeli G, Pokorna P, Allegaert K, Mosca F, Cavallaro G, Wildschut ED, Tibboel D. Drug Disposition and Pharmacotherapy in Neonatal ECMO: From Fragmented Data to Integrated Knowledge. Front Pediatr 2019; 7:360. [PMID: 31552205 PMCID: PMC6733981 DOI: 10.3389/fped.2019.00360] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Accepted: 08/16/2019] [Indexed: 12/27/2022] Open
Abstract
Extracorporeal membrane oxygenation (ECMO) is a lifesaving support technology for potentially reversible neonatal cardiac and/or respiratory failure. As the survival and the overall outcome of patients rely on the treatment and reversal of the underlying disease, effective and preferentially evidence-based pharmacotherapy is crucial to target recovery. Currently limited data exist to support the clinicians in their every-day intensive care prescribing practice with the contemporary ECMO technology. Indeed, drug dosing to optimize pharmacotherapy during neonatal ECMO is a major challenge. The impact of the maturational changes of the organ function on both pharmacokinetics (PK) and pharmacodynamics (PD) has been widely established over the last decades. Next to the developmental pharmacology, additional non-maturational factors have been recognized as key-determinants of PK/PD variability. The dynamically changing state of critical illness during the ECMO course impairs the achievement of optimal drug exposure, as a result of single or multi-organ failure, capillary leak, altered protein binding, and sometimes a hyperdynamic state, with a variable effect on both the volume of distribution (Vd) and the clearance (Cl) of drugs. Extracorporeal membrane oxygenation introduces further PK/PD perturbation due to drug sequestration and hemodilution, thus increasing the Vd and clearance (sequestration). Drug disposition depends on the characteristics of the compounds (hydrophilic vs. lipophilic, protein binding), patients (age, comorbidities, surgery, co-medications, genetic variations), and circuits (roller vs. centrifugal-based systems; silicone vs. hollow-fiber oxygenators; renal replacement therapy). Based on the potential combination of the above-mentioned drug PK/PD determinants, an integrated approach in clinical drug prescription is pivotal to limit the risks of over- and under-dosing. The understanding of the dose-exposure-response relationship in critically-ill neonates on ECMO will enable the optimization of dosing strategies to ensure safety and efficacy for the individual patient. Next to in vitro and clinical PK data collection, physiologically-based pharmacokinetic modeling (PBPK) are emerging as alternative approaches to provide bedside dosing guidance. This article provides an overview of the available evidence in the field of neonatal pharmacology during ECMO. We will identify the main determinants of altered PK and PD, elaborate on evidence-based recommendations on pharmacotherapy and highlight areas for further research.
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Affiliation(s)
- Genny Raffaeli
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, NICU, Milan, Italy
- Department of Clinical Sciences and Community Health, Università degli Studi di Milano, Milan, Italy
| | - Pavla Pokorna
- Department of Pediatrics—ICU, General University Hospital, 1st Faculty of Medicine Charles University, Prague, Czechia
- Department of Pharmacology, General University Hospital, 1st Faculty of Medicine Charles University, Prague, Czechia
- Intensive Care and Department of Pediatric Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, Netherlands
| | - Karel Allegaert
- Division of Neonatology, Department of Pediatrics, Erasmus MC Sophia Children's Hospital, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Development and Regeneration, KU Leuven, Leuven, Belgium
| | - Fabio Mosca
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, NICU, Milan, Italy
- Department of Clinical Sciences and Community Health, Università degli Studi di Milano, Milan, Italy
| | - Giacomo Cavallaro
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, NICU, Milan, Italy
| | - Enno D. Wildschut
- Intensive Care and Department of Pediatric Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, Netherlands
| | - Dick Tibboel
- Intensive Care and Department of Pediatric Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, Netherlands
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21
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Ioannidis JPA. Reproducible pharmacokinetics. J Pharmacokinet Pharmacodyn 2019; 46:111-116. [PMID: 31004315 DOI: 10.1007/s10928-019-09621-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2018] [Accepted: 02/05/2019] [Indexed: 01/31/2023]
Abstract
Reproducibility is a highly desired feature of scientific investigation in general, and it has special connotations for research in pharmacokinetics, a vibrant field with over 500,000 publications to-date. It is important to be able to differentiate between genuine heterogeneity in pharmacokinetic parameters from heterogeneity that is due to errors and biases. This overview discusses efforts and opportunities to diminish the latter type of undesirable heterogeneity. Several reporting and research guidance documents and standards have been proposed for pharmacokinetic studies, but their adoption is still rather limited. Quality problems in the methods used and model evaluations have been examined in some empirical studies of the literature. Standardization of statistical and laboratory tools and procedures can be improved in the field. Only a small fraction of pharmacokinetic studies become pre-registered and only 9995 such studies have been registered in ClinicalTrials.gov as of August 2018. It is likely that most pharmacokinetic studies remain unpublished. Publication bias affecting the results and inferences has been documented in case studies, but its exact extent is unknown for the field at-large. The use of meta-analyses in the field is still limited. Availability of raw data, detailed protocols, software and codes is hopefully improving with multiple ongoing initiatives. Several research practices can contribute to greater transparency and reproducibility for pharmacokinetic investigations.
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Affiliation(s)
- John P A Ioannidis
- Departments of Medicine, Health Research and Policy, Biomedical Data Science, and Statistics, Stanford Prevention Research Center, Meta-Research Innovation Center at Stanford (METRICS), Stanford University, 1265 Welch Road, Medical School Office Building Room X306, Stanford, CA, 94305, USA.
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22
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Favié LMA, Groenendaal F, van den Broek MPH, Rademaker CMA, de Haan TR, van Straaten HLM, Dijk PH, van Heijst A, Simons SHP, Dijkman KP, Rijken M, Zonnenberg IA, Cools F, Zecic A, van der Lee JH, Nuytemans DHGM, van Bel F, Egberts TCG, Huitema ADR. Phenobarbital, Midazolam Pharmacokinetics, Effectiveness, and Drug-Drug Interaction in Asphyxiated Neonates Undergoing Therapeutic Hypothermia. Neonatology 2019; 116:154-162. [PMID: 31256150 PMCID: PMC6878731 DOI: 10.1159/000499330] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2018] [Accepted: 02/28/2019] [Indexed: 12/14/2022]
Abstract
BACKGROUND Phenobarbital and midazolam are commonly used drugs in (near-)term neonates treated with therapeutic hypothermia for hypoxic-ischaemic encephalopathy, for sedation, and/or as anti-epileptic drug. Phenobarbital is an inducer of cytochrome P450 (CYP) 3A, while midazolam is a CYP3A substrate. Therefore, co-treatment with phenobarbital might impact midazolam clearance. OBJECTIVES To assess pharmacokinetics and clinical anti-epileptic effectiveness of phenobarbital and midazolam in asphyxiated neonates and to develop dosing guidelines. METHODS Data were collected in the prospective multicentre PharmaCool study. In the present study, neonates treated with therapeutic hypothermia and receiving midazolam and/or phenobarbital were included. Plasma concentrations of phenobarbital and midazolam including its metabolites were determined in blood samples drawn on days 2-5 after birth. Pharmacokinetic analyses were performed using non-linear mixed effects modelling; clinical effectiveness was defined as no use of additional anti-epileptic drugs. RESULTS Data were available from 113 (phenobarbital) and 118 (midazolam) neonates; 68 were treated with both medications. Only clearance of 1-hydroxy midazolam was influenced by hypothermia. Phenobarbital co-administration increased midazolam clearance by a factor 2.3 (95% CI 1.9-2.9, p < 0.05). Anticonvulsant effectiveness was 65.5% for phenobarbital and 37.1% for add-on midazolam. CONCLUSIONS Therapeutic hypothermia does not influence clearance of phenobarbital or midazolam in (near-)term neonates with hypoxic-ischaemic encephalopathy. A phenobarbital dose of 30 mg/kg is advised to reach therapeutic concentrations. Phenobarbital co-administration significantly increased midazolam clearance. Should phenobarbital be substituted by non-CYP3A inducers as first-line anticonvulsant, a 50% lower midazolam maintenance dose might be appropriate to avoid excessive exposure during the first days after birth.
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Affiliation(s)
- Laurent M A Favié
- Department of Clinical Pharmacy, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands, .,Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands,
| | - Floris Groenendaal
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands.,Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | | | - Carin M A Rademaker
- Department of Clinical Pharmacy, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Timo R de Haan
- Department of Neonatology, Emma Children's Hospital, Academic Medical Center, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | | | - Peter H Dijk
- Department of Neonatology, Groningen University Medical Centre, Groningen, The Netherlands
| | - Arno van Heijst
- Department of Neonatology, Radboud University Medical Center-Amalia Children's Hospital, Nijmegen, The Netherlands
| | - Sinno H P Simons
- Division of Neonatology, Department of Pediatrics, Erasmus Medical Centre-Sophia Children's Hospital, Rotterdam, The Netherlands
| | - Koen P Dijkman
- Department of Neonatology, Máxima Medical Center Veldhoven, Veldhoven, The Netherlands
| | - Monique Rijken
- Department of Neonatology, Leiden University Medical Center, Leiden, The Netherlands
| | - Inge A Zonnenberg
- Department of Neonatology, VU University Medical Center, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Filip Cools
- Department of Neonatology, UZ Brussel - Vrije Universiteit Brussel, Brussels, Belgium
| | - Alexandra Zecic
- Department of Neonatology, University Hospital Gent, Gent, Belgium
| | - Johanna H van der Lee
- Paediatric Clinical Research Office, Emma Children's Hospital, Academic Medical Center, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Debbie H G M Nuytemans
- Clinical Research Coordinator PharmaCool Study, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Frank van Bel
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands.,Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Toine C G Egberts
- Department of Clinical Pharmacy, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.,Department of Pharmacoepidemiology and Clinical Pharmacology, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Alwin D R Huitema
- Department of Clinical Pharmacy, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.,Department of Pharmacy and Pharmacology, Netherlands Cancer Institute, Amsterdam, The Netherlands
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23
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Pokorná P, Šíma M, Vobruba V, Tibboel D, Slanař O. Phenobarbital pharmacokinetics in neonates and infants during extracorporeal membrane oxygenation. Perfusion 2018; 33:80-86. [PMID: 29788839 DOI: 10.1177/0267659118766444] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
INTRODUCTION The disposition of drugs is potentially changed due to extracorporeal membrane oxygenation (ECMO) in neonates and infants. METHODS The aim of the study was to evaluate the individual pharmacokinetics (PK) of phenobarbital and the effect of PK covariates in neonates and infants undergoing ECMO. Sixteen patients (7 neonates, 9 infants) treated with phenobarbital during ECMO (centrifugal-flow pump circuits) were enrolled in the PK study. Phenobarbital serum concentrations were measured using a fluorescence polarization immunoassay. Individual PK parameters - volume of distribution (Vd) and clearance (CL) were calculated in a one-compartmental pharmacokinetic model. RESULTS The mean (SD) Vd and CL values in neonates were 0.46 (0.24) L/kg and 8.0 (4.5) mL/h/kg, respectively. Respective values in infants were 0.56 (0.23) L/kg and 8.5 (3.1) mL/h/kg. PK parameters in neonates and infants were not significantly different. We observed high inter-individual variability in PK parameters (coefficients of variation [CV] were 52% and 53% for CL and Vd, respectively). Doses were adjusted based on therapeutic drug monitoring (TDM) in 87.5% patients. Only 50% of the first measured phenobarbital serum concentrations in each patient were within the therapeutic range of 10-40 mg/L, in comparison with 88.6% concentration measured after TDM implementation. Linear regression models showed that both Vd and CL are significantly related with body weight (BW) and length. Median optimal phenobarbital loading dose (LD) and maintenance dose (MD), calculated from pharmacokinetic data, were 15 mg/kg and 4 mg/kg/day, respectively. CONCLUSIONS Body weight was shown to be the main PK covariate of phenobarbital disposition. Subsequent dosing nomograms are provided for phenobarbital dosing during ECMO.
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Affiliation(s)
- Pavla Pokorná
- 1 Department of Pediatrics - PICU/NICU, General University Hospital, 1st Faculty of Medicine Charles University, Prague 2, Czech Republic.,2 Department of Pharmacology, General University Hospital, 1st Faculty of Medicine Charles University, Prague 2, Czech Republic.,3 Intensive Care and Department of Pediatric Surgery, Erasmus MC - Sophia Childrens Hospital, Rotterdam, the Netherlands
| | - Martin Šíma
- 2 Department of Pharmacology, General University Hospital, 1st Faculty of Medicine Charles University, Prague 2, Czech Republic
| | - Václav Vobruba
- 1 Department of Pediatrics - PICU/NICU, General University Hospital, 1st Faculty of Medicine Charles University, Prague 2, Czech Republic
| | - Dick Tibboel
- 1 Department of Pediatrics - PICU/NICU, General University Hospital, 1st Faculty of Medicine Charles University, Prague 2, Czech Republic.,3 Intensive Care and Department of Pediatric Surgery, Erasmus MC - Sophia Childrens Hospital, Rotterdam, the Netherlands
| | - Ondřej Slanař
- 2 Department of Pharmacology, General University Hospital, 1st Faculty of Medicine Charles University, Prague 2, Czech Republic
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24
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Moffett BS, Weingarten MM, Galati M, Placencia JL, Rodman EA, Riviello JJ, Kayyal SY. Phenobarbital population pharmacokinetics across the pediatric age spectrum. Epilepsia 2018; 59:1327-1333. [PMID: 29897629 DOI: 10.1111/epi.14447] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/16/2018] [Indexed: 11/29/2022]
Abstract
OBJECTIVE Phenobarbital is frequently used in pediatric patients for treatment and prophylaxis of seizures. Pharmacokinetic data for this patient population is lacking and would assist in dosing decisions. METHODS A retrospective population pharmacokinetic analysis was designed for all pediatric patients <19 years of age initiated on phenobarbital at our institution from January 2011 to June 2017. Patients were included if they were initiated on intravenous or enteral phenobarbital for treatment or prophylaxis of seizures and had a serum phenobarbital concentration monitored while an inpatient. Data collection included the following: age, weight, height, gestational age, core body temperature, serum creatinine, blood urea nitrogen, aspartase aminotransferase, alanine aminotransferase, urine output over the prior 12 hours, phenobarbital doses and serum concentrations, and potential drug-drug interactions. Descriptive statistical methods were used to summarize the data. Pharmacokinetic analysis was performed with NONMEM and simulation was performed for doses of 10, 20, 30, and 40 mg kg-1 dose-1 , iv, followed by enteral doses of 3, 4, 5, and 6 mg kg-1 d-1 . RESULTS A total of 355 patients (50.3% male, median gestational age 39 weeks (interquartile range [IQR] 35, 40), median age 0.28 years (IQR 0.06, 0.82). Median phenobarbital dose was enteral = 2.6 (IQR 1.9, 3.9) mg kg-1 dose-1 ; intravenous = 2.6 (IQR 2.2, 4.9) mg kg-1 dose-1 ) and mean serum concentration was 41.1 ± 23.9 mg/L at median 6.5 (IQR 2.9, 11.1) hours after a dose. A one-compartment proportional error model best fit the data where clearance and volume of distribution were allometrically scaled using fat-free mass. Significant covariates included serum creatinine, postmenstrual age, and drug-drug interactions on clearance, and age in years on volume of distribution. SIGNIFICANCE Phenobarbital dosing of 30 mg kg-1 dose-1 ,iv, followed by 4 mg kg-1 d-1 had the highest probability of attaining a therapeutic concentration at 7 days. Postmenstrual age and drug-drug interactions should be incorporated into dosing decisions.
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Affiliation(s)
- Brady S Moffett
- Department of Pharmacy, Texas Children's Hospital, Houston, TX, USA.,Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Mindl M Weingarten
- Department of Pharmacy, Texas Children's Hospital, Houston, TX, USA.,Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | | | - Jennifer L Placencia
- Department of Pharmacy, Texas Children's Hospital, Houston, TX, USA.,Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Emily A Rodman
- Department of Pharmacy, Texas Children's Hospital, Houston, TX, USA.,Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - James J Riviello
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Simon Y Kayyal
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
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