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Wang D, Hung T, Hung N, Glue P, Jackson C, Duffull S. Optimal sample selection applied to information rich, dense data. J Pharmacokinet Pharmacodyn 2024; 51:33-37. [PMID: 37561265 DOI: 10.1007/s10928-023-09883-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 07/31/2023] [Indexed: 08/11/2023]
Abstract
Dense data can be classified into superdense information-poor data (type 1 dense data) and dense information-rich data (type 2 dense data). Arbitrary, random, or optimal thinning may be applied to type 1 dense data to minimise computational burden and statistical issues (such as autocorrelation). In contrast, a prospective or retrospective optimal design can be applied to type 2 dense data to maximise information gain from limited resources (capital and/or time). Here we describe a retrospective optimal selection strategy for quantification of unbound drug concentration from a discrete set of plasma samples where the total drug concentration has been measured.
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Affiliation(s)
- David Wang
- Department of Anaesthesia, Waikato Hospital, Hamilton, New Zealand.
| | - Tak Hung
- Zenith Technology Limited, Dunedin, New Zealand
| | - Noelyn Hung
- Department of Pathology, University of Otago, Dunedin, New Zealand
| | - Paul Glue
- Department of Psychological Medicine, University of Otago, Dunedin, New Zealand
| | - Chris Jackson
- Department of Medicine, University of Otago, Dunedin, New Zealand
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2
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Fike CD, Avachat C, Birnbaum AK, Aschner JL, Sherwin CM. Pharmacokinetics of L-Citrulline in Neonates at Risk of Developing Bronchopulmonary Dysplasia-Associated Pulmonary Hypertension. Paediatr Drugs 2023; 25:87-96. [PMID: 36316628 PMCID: PMC10039462 DOI: 10.1007/s40272-022-00542-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/02/2022] [Indexed: 11/06/2022]
Abstract
BACKGROUND Options to treat pulmonary hypertension (PH) in neonates with bronchopulmonary dysplasia (BPD) are few and largely ineffective. Improving the bioavailability of nitric oxide (NO) might be an efficacious treatment for BPD-PH. When administered orally, the NO-L-arginine precursor, L-citrulline, increases NO production in children and adults, however, pharmacokinetic (PK) studies of oral L-citrulline have not been performed in infants and children. OBJECTIVES This study characterized the PK of enterally administered L-citrulline in neonates at risk of developing BPD-PH to devise a model-informed dosing strategy. METHODS AND RESULTS Ten premature neonates (≤ 28 weeks gestation) were administered a single dose of 150 mg/kg (powder form solubilized in sterile water) oral L-citrulline at 32 ± 1 weeks postmenstrual age. Due to the need to limit blood draws, time windows were used to maximize the sampling over the dosing interval by assigning neonates to one of two groups (ii) samples collected pre-dose and at 1- and 2.5-h post-dose, and (ii) pre-dose and 0.25- and 3-h post-dose. The L-arginine concentrations (µmol/L) and the L-citrulline (µmol/L) plasma concentration-time data were evaluated using non-compartmental analysis (Phoenix WinNonlin version 8.1). Optimal dosage strategies were derived using a simulation-based methodology. Simulated doses of 51.5 mg or 37.5 mg/kg given four times a day produced steady-state concentrations close to a target of 50 µmol/L. The volume of distribution (V/F) and clearance (CL/F) were 302.89 ml and 774.96 ml/h, respectively, with the drug exhibiting a half-life of 16 minutes. The AUC from the time of dosing to the time of last concentration was 1473.3 h*μmol/L, with Cmax and Tmax of 799 μmol/L and 1.55 h, respectively. CONCLUSION This is the first PK study in neonates presenting data that can be used to inform dosing strategies in future randomized controlled trials evaluating enteral L-citrulline as a potential treatment to reduce PH associated with BPD in premature neonates. REGISTRATION Clinical trials.gov Identifier: NCT03542812.
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Affiliation(s)
- Candice D Fike
- Department of Pediatrics, The University of Utah Health, Salt Lake City, UT, USA
| | - Charul Avachat
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, USA
| | - Angela K Birnbaum
- Department of Pediatrics, The University of Utah Health, Salt Lake City, UT, USA
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, USA
| | - Judy L Aschner
- Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Pediatrics, Hackensack Meridian School of Medicine, Nutley, NJ, USA
| | - Catherine M Sherwin
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, USA.
- Department of Pediatrics, Wright State University Boonshoft School of Medicine, Dayton, OH, USA.
- Dayton Children's Hospital, Dayton, OH, USA.
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Population Pharmacokinetic Evaluation with External Validation of Tacrolimus in Chinese Primary Nephrotic Syndrome Patients. Pharm Res 2022; 39:1907-1920. [PMID: 35650450 DOI: 10.1007/s11095-022-03273-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Accepted: 04/22/2022] [Indexed: 10/18/2022]
Abstract
PURPOSE The generalizability of numerous tacrolimus population pharmacokinetic (popPK) models constructed to promote optimal tacrolimus dosing in patients with primary nephrotic syndrome (PNS) is unclear. This study aimed to evaluate the predictive performance of published tacrolimus popPK models for PNS patients with an external data set. METHODS We prospectively collected 223 concentrations from 50 Chinese adult patients with PNS who were undergoing tacrolimus treatment. Data on published tacrolimus popPK models for adults and children with PNS were extracted from the literature. Model predictability was evaluated with prediction-based and simulation-based diagnostics and Bayesian forecasting. RESULTS In prediction-based evaluation, none of the 11 identified published popPK models of tacrolimus had met a predefined criteria of a mean prediction error ≤ ± 20%, and the prediction error within ± 30% of the identified models didn't exceed 50%. Simulation-based diagnostics also indicated unsatisfactory predictability. Bayesian forecasting demonstrated amelioration in the model predictability with the inclusion of 2-3 prior observations. Moreover, the predictive performance of nonlinear models was not better than that of one-compartment models. CONCLUSIONS The prediction of tacrolimus concentrations for patients with PNS remains challenging; published models are not applicable for extrapolation to other hospitals. Bayesian forecasting significantly improved model predictability and thereby helped to individualize tacrolimus dosing.
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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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Gwee A, Duffull S, Zhu X, Tong SYC, Cranswick N, McWhinney B, Ungerer J, Francis J, Steer AC. Population pharmacokinetics of ivermectin for the treatment of scabies in Indigenous Australian children. PLoS Negl Trop Dis 2020; 14:e0008886. [PMID: 33284799 PMCID: PMC7746298 DOI: 10.1371/journal.pntd.0008886] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Revised: 12/17/2020] [Accepted: 10/14/2020] [Indexed: 11/30/2022] Open
Abstract
Ivermectin is a broad-spectrum antiparasitic agent used for the treatment and control of neglected tropical diseases. In Australia, ivermectin is primarily used for scabies and is licensed in children aged ≥5 years weighing >15 kg. However, young children, aged <5 years, are particularly vulnerable to scabies and its secondary complications. Therefore, this study aimed to determine an appropriate ivermectin dose for children aged 2 to 4 years and weighing ≤15 kg. We conducted a prospective, pharmacokinetic study of ivermectin in Indigenous Australian children aged between 5 and 15 years and weighing >15 kg. Doses of 200 μg/kg rounded to the nearest whole or half 3 mg tablet were given to children with scabies and ivermectin concentrations determined at two time points after dosing. A population pharmacokinetic model was developed using non-linear mixed effects modelling. A separate covariate database of children aged 2 to 4 years and weighing <15 kg was used to generate 1000 virtual patients and simulate the dose required to achieve equivalent drug exposure in young children as those aged ≥5 years. Overall, 26 children who had 48 ivermectin concentrations determined were included, 11 (42%) were male, the median age was 10.9 years and median body weight 37.6 kg. The final model was a two-compartment model with first-order absorption and linear elimination. For simulated children aged 2 to 4 years, a dose of 3 mg in children weighing 10–15 kg produced similar drug exposures to those >5 years. The median simulated area under the concentration-time curve was 976 μg∙h/L. Using modelling, we have identified a dosing strategy for ivermectin in children aged 2 to 4 years and weighing less than 15 kg that can be prospectively evaluated for safety and efficacy. Ivermectin is an important drug for the control and treatment of neglected tropical diseases. However, despite numerous studies showing that ivermectin is safe and well tolerated in young children, it is not currently recommended in young children <5 years and <15 kg. Therefore, there are no guidelines for the dose of ivermectin in young or small children. In this study, we firstly determined how much ivermectin is present in blood in children aged 5 years and older. We then used this information to model what happens to ivermectin in childrens’ bodies allowing us to calculate the dose required in children aged less than 5 years and weighing under 15 kg. This study provides a new dosing guideline that can now be tested in clinical studies of children <5 years and <15 kg.
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Affiliation(s)
- Amanda Gwee
- Department of General Medicine, The Royal Children’s Hospital Melbourne, Parkville, Victoria, Australia
- Department of Paediatrics, The University of Melbourne, Parkville, Victoria, Australia
- Infection and Immunity theme, Murdoch Children’s Research Institute, Parkville, Victoria, Australia
- * E-mail:
| | - Stephen Duffull
- School of Pharmacy, University of Otago, Dunedin, New Zealand
| | - Xiao Zhu
- Infection and Immunity theme, Murdoch Children’s Research Institute, Parkville, Victoria, Australia
- School of Pharmacy, University of Otago, Dunedin, New Zealand
| | - Steven Y. C. Tong
- Victorian Infectious Diseases Service, The Royal Melbourne Hospital, and Doherty Department University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Victoria, Australia
- Global and tropical health division, Menzies School of Health Research, Charles Darwin University, Darwin, Australia
| | - Noel Cranswick
- Department of General Medicine, The Royal Children’s Hospital Melbourne, Parkville, Victoria, Australia
- Department of Paediatrics, The University of Melbourne, Parkville, Victoria, Australia
- Infection and Immunity theme, Murdoch Children’s Research Institute, Parkville, Victoria, Australia
| | - Brett McWhinney
- Department of Chemical Pathology, Pathology Queensland, Brisbane, Queensland, Australia
| | - Jacobus Ungerer
- Department of Chemical Pathology, Pathology Queensland, Brisbane, Queensland, Australia
- Faculty of Biomedical Science, University of Queensland, Brisbane, Queensland, Australia
| | - Joshua Francis
- Global and tropical health division, Menzies School of Health Research, Charles Darwin University, Darwin, Australia
- Department of Paediatrics, Royal Darwin Hospital, Northern Territory, Australia
| | - Andrew C. Steer
- Department of General Medicine, The Royal Children’s Hospital Melbourne, Parkville, Victoria, Australia
- Department of Paediatrics, The University of Melbourne, Parkville, Victoria, Australia
- Infection and Immunity theme, Murdoch Children’s Research Institute, Parkville, Victoria, Australia
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Roubaud Baudron C, Legeron R, Ollivier J, Bonnet F, Greib C, Guerville F, Cazanave C, Kobeh D, Cressot V, Moneger N, Videau MN, Thiel E, Foucaud C, Lafargue A, de Thezy A, Durrieu J, Bourdel Marchasson I, Pinganaud G, Breilh D. Is the subcutaneous route an alternative for administering ertapenem to older patients? PHACINERTA study. J Antimicrob Chemother 2020; 74:3546-3554. [PMID: 31730164 DOI: 10.1093/jac/dkz385] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2019] [Revised: 08/02/2019] [Accepted: 08/06/2019] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Antibiotic administration by subcutaneous (SC) injection is common practice in French geriatric wards as an alternative to the intravenous (IV) route, but few pharmacokinetic/pharmacodynamic data are available. Ertapenem is useful for the treatment of infections with ESBL-producing enterobacteria. OBJECTIVES To report and compare ertapenem pharmacokinetic data between IV and SC routes in older persons. METHODS Patients >65 years of age receiving ertapenem (1 g once daily) for at least 48 h (IV or SC, steady-state) were prospectively enrolled. Total ertapenem concentrations [residual (C0), IV peak (C0.5) and SC peak (C2.5)] were determined by UV HPLC. Individual-predicted AUC0-24 values were calculated and population pharmacokinetic analyses were performed. Using the final model, a Monte Carlo simulation involving 10 000 patients evaluated the influence of SC or IV administration on the PTA. Tolerance to ertapenem and recovery were also monitored. ClinicalTrials.gov identifier: NCT02505386. RESULTS Ten (mean ± SD age=87±7 years) and 16 (age=88±5 years) patients were included in the IV and SC groups, respectively. The mean C0 and C2.5 values were not significantly different between the IV and SC groups (C0=12±5.9 versus 12±7.4 mg/L, P=0.97; C2.5=97±42 versus 67±41 mg/L, P=0.99). The mean C0.5 was higher in the IV group compared with the SC group (C0.5=184±90 versus 51±66 mg/L, P=0.001). The mean individual AUCs (1126.92±334.99 mg·h/L for IV versus 1005.3±266.0 mg·h/L for SC, P=0.38) and PTAs were not significantly different between groups. No severe antibiotic-related adverse effects were noted. CONCLUSIONS SC administration of ertapenem is an alternative to IV administration in older patients.
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Affiliation(s)
- Claire Roubaud Baudron
- CHU Bordeaux, Pôle de Gérontologie Clinique, F-33000 Bordeaux, France.,Univ. Bordeaux, INSERM UMR 1053, BaRITOn, F-33000 Bordeaux, France
| | - Rachel Legeron
- CHU Bordeaux, Service Pharmacie à Usage Intérieur, département de Pharmacie Clinique, F-33000 Bordeaux, France
| | - Julien Ollivier
- CHU Bordeaux, Service Pharmacie à Usage Intérieur, département de Pharmacie Clinique, F-33000 Bordeaux, France
| | - Fabrice Bonnet
- CHU Bordeaux, Service de Médecine Interne et Maladies Infectieuses, Hôpital Sain-André, F-33000 Bordeaux, France
| | - Carine Greib
- CHU Bordeaux, Service de Médecine Interne et Maladies Infectieuses, Hôpital Haut Lévêque, F-33000 Bordeaux, France
| | - Florent Guerville
- CHU Bordeaux, Pôle de Gérontologie Clinique, F-33000 Bordeaux, France
| | - Charles Cazanave
- CHU Bordeaux, Service des Maladies Infectieuses et Tropicales, Hôpital Pellegrin, F-33000 Bordeaux, France.,Univ. Bordeaux, INRA, USC EA 3671, Infections humaines à mycoplasmes et à chlamydiae, F-33000 Bordeaux, France
| | - David Kobeh
- CHU Bordeaux, Pôle de Gérontologie Clinique, F-33000 Bordeaux, France
| | - Véronique Cressot
- CHU Bordeaux, Pôle de Gérontologie Clinique, F-33000 Bordeaux, France
| | - Nicolas Moneger
- CHU Bordeaux, Pôle de Gérontologie Clinique, F-33000 Bordeaux, France
| | | | - Elise Thiel
- CHU Bordeaux, Pôle de Gérontologie Clinique, F-33000 Bordeaux, France
| | - Carine Foucaud
- CHU Bordeaux, Pôle de Gérontologie Clinique, F-33000 Bordeaux, France
| | - Aurélie Lafargue
- CHU Bordeaux, Pôle de Gérontologie Clinique, F-33000 Bordeaux, France
| | - Albane de Thezy
- CHU Bordeaux, Pôle de Gérontologie Clinique, F-33000 Bordeaux, France
| | - Jessica Durrieu
- CHU Bordeaux, Pôle de Gérontologie Clinique, F-33000 Bordeaux, France
| | - Isabelle Bourdel Marchasson
- CHU Bordeaux, Pôle de Gérontologie Clinique, F-33000 Bordeaux, France.,Univ. Bordeaux, CNRS UMR 5536 RMSB, F-33000 Bordeaux, France
| | | | - Dominique Breilh
- CHU Bordeaux, Service Pharmacie à Usage Intérieur, département de Pharmacie Clinique, F-33000 Bordeaux, France.,Univ. Bordeaux, INSERM UMR 1034, Pharmacokinetics and Pharmacodynamics (PK/PD) Group, F-33000 Bordeaux, France
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Wang YL, Guilhaumou R, Blin O, Velly L, Marsot A. External evaluation of population pharmacokinetic models for continuous administration of meropenem in critically ill adult patients. Eur J Clin Pharmacol 2020; 76:1281-1289. [PMID: 32495084 DOI: 10.1007/s00228-020-02922-z] [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] [Received: 02/27/2020] [Accepted: 05/29/2020] [Indexed: 12/30/2022]
Abstract
PURPOSE Beta-lactams (BL), the most commonly prescribed class of antibiotics, are recommended as the first-line therapy for multiple indications in infectious disease guidelines. Meropenem (MERO) is frequently used in intensive care units (ICU) to treat bacterial infections with or without sepsis. The pharmacokinetics of MERO display a large variability in patients admitted to ICUs due to altered pathophysiology. The aim of this study was to perform an external evaluation of published population pharmacokinetic models of MERO in order to test their predictive performance in a cohort of ICU adult patients. METHODS A literature search in PubMed/Medline database was made following the PRISMA statement. External evaluation was performed using NONMEM software, and the bias and inaccuracy values were calculated. RESULTS An external validation dataset from the Timone Hospital in Marseille, France, included 84 concentration samples from 27 patients. Four models of MERO were identified according to the inclusion criteria of the study. None of the models presented acceptable values of bias and inaccuracy. CONCLUSION While performing external evaluations on some populations may confirm a model's suitability to diverse groups of patients, there is still some variability that cannot be explained nor solved by the procedure. This brings to light the difficulty to develop only one model for ICU patients and the need to develop one specific model to each population of critically ill patients.
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Affiliation(s)
- Y L Wang
- Laboratoire de Suivi Thérapeutique Pharmacologique et Pharmacocinétique, Faculté de Pharmacie, Université de Montréal, Pavillon Jean-Coutu, 2940 chemin de Polytechnique, Montréal, QC, H3T 1J4, Canada.,Faculté de Pharmacie, Université de Montréal, Montréal, QC, Canada
| | - R Guilhaumou
- Service de Pharmacologie Clinique et Pharmacovigilance, Hôpital de la Timone, Assistance Publique des Hôpitaux de Marseille, Marseille, France.,Pharmacologie intégrée et interface clinique et industrielle, Institut de Neuroscience des systèmes, CNRS 7289, Aix Marseille Université, 13385, Marseille, France
| | - O Blin
- Service de Pharmacologie Clinique et Pharmacovigilance, Hôpital de la Timone, Assistance Publique des Hôpitaux de Marseille, Marseille, France.,Pharmacologie intégrée et interface clinique et industrielle, Institut de Neuroscience des systèmes, CNRS 7289, Aix Marseille Université, 13385, Marseille, France
| | - L Velly
- Service d'Anesthésie-Réanimation, Hôpital de la Timone, Assistance Publique des Hôpitaux de Marseille, Marseille, France
| | - Amélie Marsot
- Laboratoire de Suivi Thérapeutique Pharmacologique et Pharmacocinétique, Faculté de Pharmacie, Université de Montréal, Pavillon Jean-Coutu, 2940 chemin de Polytechnique, Montréal, QC, H3T 1J4, Canada. .,Faculté de Pharmacie, Université de Montréal, Montréal, QC, Canada. .,Centre de Recherche, CHU Sainte Justine, Montréal, QC, Canada.
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8
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Germovsek E, Barker CIS, Sharland M, Standing JF. Pharmacokinetic-Pharmacodynamic Modeling in Pediatric Drug Development, and the Importance of Standardized Scaling of Clearance. Clin Pharmacokinet 2020; 58:39-52. [PMID: 29675639 PMCID: PMC6325987 DOI: 10.1007/s40262-018-0659-0] [Citation(s) in RCA: 49] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Pharmacokinetic/pharmacodynamic (PKPD) modeling is important in the design and conduct of clinical pharmacology research in children. During drug development, PKPD modeling and simulation should underpin rational trial design and facilitate extrapolation to investigate efficacy and safety. The application of PKPD modeling to optimize dosing recommendations and therapeutic drug monitoring is also increasing, and PKPD model-based dose individualization will become a core feature of personalized medicine. Following extensive progress on pediatric PK modeling, a greater emphasis now needs to be placed on PD modeling to understand age-related changes in drug effects. This paper discusses the principles of PKPD modeling in the context of pediatric drug development, summarizing how important PK parameters, such as clearance (CL), are scaled with size and age, and highlights a standardized method for CL scaling in children. One standard scaling method would facilitate comparison of PK parameters across multiple studies, thus increasing the utility of existing PK models and facilitating optimal design of new studies.
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Affiliation(s)
- Eva Germovsek
- Infection, Inflammation and Rheumatology Section, UCL Great Ormond Street Institute of Child Heath, University College London, London, UK. .,Pharmacometrics Research Group, Department of Pharmaceutical Biosciences, Uppsala University, PO Box 591, 751 24, Uppsala, Sweden.
| | - Charlotte I S Barker
- Infection, Inflammation and Rheumatology Section, UCL Great Ormond Street Institute of Child Heath, University College London, London, UK.,Paediatric Infectious Diseases Research Group, Institute for Infection and Immunity, St George's, University of London, London, UK.,St George's University Hospitals NHS Foundation Trust, London, UK
| | - Mike Sharland
- Paediatric Infectious Diseases Research Group, Institute for Infection and Immunity, St George's, University of London, London, UK.,St George's University Hospitals NHS Foundation Trust, London, UK
| | - Joseph F Standing
- Infection, Inflammation and Rheumatology Section, UCL Great Ormond Street Institute of Child Heath, University College London, London, UK.,Paediatric Infectious Diseases Research Group, Institute for Infection and Immunity, St George's, University of London, London, UK
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9
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Kimathi D, Juan A, Bejon P, Grais RF, Warimwe GM. Randomized, double-blinded, controlled non-inferiority trials evaluating the immunogenicity and safety of fractional doses of Yellow Fever vaccines in Kenya and Uganda. Wellcome Open Res 2019; 4:182. [PMID: 31984244 PMCID: PMC6971842 DOI: 10.12688/wellcomeopenres.15579.1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/14/2019] [Indexed: 01/22/2023] Open
Abstract
Introduction: Yellow fever is endemic in specific regions of sub-Saharan Africa and the Americas, with recent epidemics occurring on both continents. The yellow fever vaccine is effective, affordable and safe, providing life-long immunity following a single dose vaccination. However, the vaccine production process is slow and cannot be readily scaled up during epidemics. This has led the World Health Organization (WHO) to recommend the use of fractional doses as a dose-sparing strategy during epidemics, but there are no randomized controlled trials of fractional yellow fever vaccine doses in Africa. Methods and analysis: We will recruit healthy adult volunteers, adults living with HIV, and children to a series of randomized controlled trials aiming to determine the immunogenicity and safety of fractional vaccine doses in comparison to the standard vaccine dose. The trials will be conducted across two sites; Kilifi, Kenya and Mbarara, Uganda. Recruited participants will be randomized to receive fractional or standard doses of yellow fever vaccine. Scheduled visits will include blood collection for serum and peripheral blood mononuclear cells (PBMCs) before vaccination and on various days - up to 2 years - post-vaccination. The primary outcome is the rate of seroconversion as measured by the plaque reduction neutralization test (PRNT 50) at 28 days post-vaccination. Secondary outcomes include antibody titre changes, longevity of the immune response, safety assessment using clinical data, the nature and magnitude of the cellular immune response and post-vaccination control of viremia by vaccine dose. Ethics and dissemination: The clinical trial protocols have received approval from the relevant institutional ethics and regulatory review committees in Kenya and Uganda, and the WHO Ethics Review Committee. The research findings will be disseminated through open-access publications and presented at relevant conferences and workshops. Registration: ClinicalTrials.gov NCT02991495 (registered on 13 December 2016) and NCT04059471 (registered on 15 August 2019).
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Affiliation(s)
- Derick Kimathi
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
- Centre for Tropical Medicine & Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | | | - Philip Bejon
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
- Centre for Tropical Medicine & Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | | | - George M Warimwe
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
- Centre for Tropical Medicine & Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
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10
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Generating Robust and Informative Nonclinical In Vitro and In Vivo Bacterial Infection Model Efficacy Data To Support Translation to Humans. Antimicrob Agents Chemother 2019; 63:AAC.02307-18. [PMID: 30833428 PMCID: PMC6496039 DOI: 10.1128/aac.02307-18] [Citation(s) in RCA: 120] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
In June 2017, the National Institute of Allergy and Infectious Diseases, part of the National Institutes of Health, organized a workshop entitled “Pharmacokinetics-Pharmacodynamics (PK/PD) for Development of Therapeutics against Bacterial Pathogens.” The aims were to discuss details of various PK/PD models and identify sound practices for deriving and utilizing PK/PD relationships to design optimal dosage regimens for patients. Workshop participants encompassed individuals from academia, industry, and government, including the United States Food and Drug Administration. In June 2017, the National Institute of Allergy and Infectious Diseases, part of the National Institutes of Health, organized a workshop entitled “Pharmacokinetics-Pharmacodynamics (PK/PD) for Development of Therapeutics against Bacterial Pathogens.” The aims were to discuss details of various PK/PD models and identify sound practices for deriving and utilizing PK/PD relationships to design optimal dosage regimens for patients. Workshop participants encompassed individuals from academia, industry, and government, including the United States Food and Drug Administration. This and the accompanying review on clinical PK/PD summarize the workshop discussions and recommendations. Nonclinical PK/PD models play a critical role in designing human dosage regimens and are essential tools for drug development. These include in vitro and in vivo efficacy models that provide valuable and complementary information for dose selection and translation from the laboratory to human. It is crucial that studies be designed, conducted, and interpreted appropriately. For antibacterial PK/PD, extensive published data and expertise are available. These have been leveraged to develop recommendations, identify common pitfalls, and describe the applications, strengths, and limitations of various nonclinical infection models and translational approaches. Despite these robust tools and published guidance, characterizing nonclinical PK/PD relationships may not be straightforward, especially for a new drug or new class. Antimicrobial PK/PD is an evolving discipline that needs to adapt to future research and development needs. Open communication between academia, pharmaceutical industry, government, and regulatory bodies is essential to share perspectives and collectively solve future challenges.
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Siripuram VK, Wright DFB, Barclay ML, Duffull SB. Deterministic identifiability of population pharmacokinetic and pharmacokinetic-pharmacodynamic models. J Pharmacokinet Pharmacodyn 2017; 44:415-423. [PMID: 28612141 DOI: 10.1007/s10928-017-9530-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2016] [Accepted: 06/07/2017] [Indexed: 01/05/2023]
Abstract
Identifiability is an important component of pharmacokinetic-pharmacodynamic (PKPD) model development. Structural identifiability is concerned with the uniqueness of the model parameters for a set of perfect input-output data and deterministic identifiability with the precision of parameter estimation given imperfect input-output data. We introduce two subcategories of deterministic identifiability, external and internal, and consider factors that distinguish between these forms. We define external deterministic identifiability as a function of externally controllable variables, i.e., the design, and internal deterministic identifiability as a function of the model and its parameter values. The concepts are explored using three common PK and PKPD models, and verified for their precision for the selected set of parameter values under optimal design.
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Affiliation(s)
- Vijay K Siripuram
- Otago Pharmacometrics Group, School of Pharmacy, University of Otago, Dunedin, New Zealand.
| | - Daniel F B Wright
- Otago Pharmacometrics Group, School of Pharmacy, University of Otago, Dunedin, New Zealand
| | - Murray L Barclay
- Departments of Gastroenterology & Clinical Pharmacology, Christchurch Hospital, Christchurch, New Zealand
| | - Stephen B Duffull
- Otago Pharmacometrics Group, School of Pharmacy, University of Otago, Dunedin, New Zealand
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Muntau AC, Burlina A, Eyskens F, Freisinger P, De Laet C, Leuzzi V, Rutsch F, Sivri HS, Vijay S, Bal MO, Gramer G, Pazdírková R, Cleary M, Lotz-Havla AS, Munafo A, Mould DR, Moreau-Stucker F, Rogoff D. Efficacy, safety and population pharmacokinetics of sapropterin in PKU patients <4 years: results from the SPARK open-label, multicentre, randomized phase IIIb trial. Orphanet J Rare Dis 2017; 12:47. [PMID: 28274234 PMCID: PMC5343543 DOI: 10.1186/s13023-017-0600-x] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2016] [Accepted: 02/23/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Sapropterin dihydrochloride, a synthetic formulation of BH4, the cofactor for phenylalanine hydroxylase (PAH, EC 1.14.16.1), was initially approved in Europe only for patients ≥4 years with BH4-responsive phenylketonuria. The aim of the SPARK (Safety Paediatric efficAcy phaRmacokinetic with Kuvan®) trial was to assess the efficacy (improvement in daily phenylalanine tolerance, neuromotor development and growth parameters), safety and pharmacokinetics of sapropterin dihydrochloride in children <4 years. RESULTS In total, 109 male or female children <4 years with confirmed BH4-responsive phenylketonuria or mild hyperphenylalaninemia and good adherence to dietary treatment were screened. 56 patients were randomly assigned (1:1) to 10 mg/kg/day oral sapropterin plus a phenylalanine-restricted diet or to only a phenylalanine-restricted diet for 26 weeks (27 to the sapropterin and diet group and 29 to the diet-only group; intention-to-treat population). Of these, 52 patients with ≥1 pharmacokinetic sample were included in the pharmacokinetic analysis, and 54 patients were included in the safety analysis. At week 26 in the sapropterin plus diet group, mean phenylalanine tolerance was 30.5 (95% confidence interval 18.7-42.3) mg/kg/day higher than in the diet-only group (p < 0.001). The safety profile of sapropterin, measured monthly, was acceptable and consistent with that seen in studies of older children. Using non-linear mixed effect modelling, a one-compartment model with flip-flop pharmacokinetic behaviour, in which the effect of weight was substantial, best described the pharmacokinetic profile. Patients in both groups had normal neuromotor development and stable growth parameters. CONCLUSIONS The addition of sapropterin to a phenylalanine-restricted diet was well tolerated and led to a significant improvement in phenylalanine tolerance in children <4 years with BH4-responsive phenylketonuria or mild hyperphenylalaninemia. The pharmacokinetic model favours once per day dosing with adjustment for weight. Based on the SPARK trial results, sapropterin has received EU approval to treat patients <4 years with BH4-responsive phenylketonuria. TRIAL REGISTRATION ClinicalTrials.gov, NCT01376908 . Registered June 17, 2011.
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Affiliation(s)
- Ania C Muntau
- University Children's Hospital, University Medical Center Hamburg Eppendorf, Martinistrasse 52, D-20246, Hamburg, Germany.
| | | | | | | | - Corinne De Laet
- Hôpital Universitaire des Enfants Reine Fabiola, Brussels, Belgium
| | | | - Frank Rutsch
- Muenster University Children's Hospital, Muenster, Germany
| | - H Serap Sivri
- Hacettepe University School of Medicine, Ankara, Turkey
| | | | | | - Gwendolyn Gramer
- Centre for Paediatric and Adolescent Medicine, Division for Neuropaediatrics and Metabolic Medicine, University of Heidelberg, Heidelberg, Germany
| | | | | | | | - Alain Munafo
- Merck Institute for Pharmacometrics, Lausanne, Switzerland
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Phelps DL, Ward RM, Williams RL, Nolen TL, Watterberg KL, Oh W, Goedecke M, Ehrenkranz RA, Fennell T, Poindexter BB, Cotten CM, Hallman M, Frantz ID, Faix RG, Zaterka-Baxter KM, Das A, Ball MB, Lacy CB, Walsh MC, Carlo WA, Sánchez PJ, Bell EF, Shankaran S, Carlton DP, Chess PR, Higgins RD. Safety and pharmacokinetics of multiple dose myo-inositol in preterm infants. Pediatr Res 2016; 80:209-17. [PMID: 27074126 PMCID: PMC5198845 DOI: 10.1038/pr.2016.97] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2015] [Accepted: 03/03/2016] [Indexed: 01/13/2023]
Abstract
BACKGROUND Preterm infants with respiratory distress syndrome (RDS) given inositol had reduced bronchopulmonary dysplasia (BPD), death and severe retinopathy of prematurity (ROP). We assessed the safety and pharmacokinetics of daily inositol to select a dose providing serum levels previously associated with benefit, and to learn if accumulation occurred when administered throughout the normal period of retinal vascularization. METHODS Infants ≤ 29 wk GA (n = 122, 14 centers) were randomized and treated with placebo or inositol at 10, 40, or 80 mg/kg/d. Intravenous administration converted to enteral when feedings were established, and continued to the first of 10 wk, 34 wk postmenstrual age (PMA) or discharge. Serum collection employed a sparse sampling population pharmacokinetics design. Inositol urine losses and feeding intakes were measured. Safety was prospectively monitored. RESULTS At 80 mg/kg/d mean serum levels reached 140 mg/l, similar to Hallman's findings. Levels declined after 2 wk, converging in all groups by 6 wk. Analyses showed a mean volume of distribution 0.657 l/kg, clearance 0.058 l/kg/h, and half-life 7.90 h. Adverse events and comorbidities were fewer in the inositol groups, but not significantly so. CONCLUSION Multiple dose inositol at 80 mg/kg/d was not associated with increased adverse events, achieves previously effective serum levels, and is appropriate for investigation in a phase III trial.
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Affiliation(s)
- Dale L. Phelps
- Department of Pediatrics, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA
| | - Robert M. Ward
- Department of Pediatrics, and Pediatric Pharmacology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Rick L. Williams
- Social, Statistical and Environmental Sciences Unit, RTI International, Research Triangle Park, NC, USA
| | - Tracy L. Nolen
- Social, Statistical and Environmental Sciences Unit, RTI International, Research Triangle Park, NC, USA
| | - Kristi L. Watterberg
- Department of Pediatrics, University of New Mexico Health Sciences Center, Albuquerque, NM, USA
| | - William Oh
- Department of Pediatrics, Women & Infants’ Hospital Brown University, Providence, RI, USA
| | - Michael Goedecke
- Social, Statistical and Environmental Sciences Unit, RTI International, Research Triangle Park, NC, USA
| | | | - Timothy Fennell
- Pharmacology and Toxicology Division, RTI International, Research Triangle Park, NC, USA
| | - Brenda B. Poindexter
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - Mikko Hallman
- PEDEGO Research Center, and MRC Oulu, and Oulu University Hospital, Oulu, Finland
| | - Ivan D. Frantz
- Department of Pediatrics, Floating Hospital for Children, Tufts Medical Center, Boston, MA, USA
| | - Roger G. Faix
- Department of Pediatrics, and Pediatric Pharmacology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Kristin M. Zaterka-Baxter
- Social, Statistical and Environmental Sciences Unit, RTI International, Research Triangle Park, NC, USA
| | - Abhik Das
- Social, Statistical and Environmental Sciences Unit, RTI International, Rockville, MD, USA
| | - M. Bethany Ball
- Department of Pediatrics, Stanford University School of Medicine and Lucile Packard Children’s Hospital, Palo Alto, CA, USA
| | - Conra Backstrom Lacy
- Department of Pediatrics, University of New Mexico Health Sciences Center, Albuquerque, NM, USA
| | - Michele C. Walsh
- Department of Pediatrics, Rainbow Babies & Children’s Hospital, Case Western Reserve University, Cleveland, OH, USA
| | - Waldemar A. Carlo
- Division of Neonatology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Pablo J. Sánchez
- Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Edward F. Bell
- Department of Pediatrics, University of Iowa, Iowa City, IA, USA
| | - Seetha Shankaran
- Department of Pediatrics, Wayne State University, Detroit, MI, USA
| | - David P. Carlton
- Department of Pediatrics, Emory University School of Medicine and Children’s Healthcare of Atlanta, Atlanta, GA, USA
| | - Patricia R. Chess
- Department of Pediatrics, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA
| | - Rosemary D. Higgins
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
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Anderson BJ, Hannam JA. Considerations when using pharmacokinetic/pharmacodynamic modeling to determine the effectiveness of simple analgesics in children. Expert Opin Drug Metab Toxicol 2015; 11:1393-408. [PMID: 26155821 DOI: 10.1517/17425255.2015.1061505] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
INTRODUCTION Assessment of analgesic drugs includes comparative studies to other analgesics and local anesthesia blockade, number needed to treat estimates and opioid sparing descriptions. An additional methodology is to define the concentration-response relationship using pharmacokinetic/pharmacodynamic (PK/PD) modeling. AREAS COVERED A concentration-response relationship allows analgesic effect comparison between drugs for different acute pain types. Covariates such as size, age and organ function impact greatly on PK in children. The cumulative effect of confounding factors (e.g., pharmacogenetics, placebo and changes in baseline pain over time) complicates PD. Other factors (outcome measures, method of measurement, failure to account for study attrition) impact on outcome. Population PK/PD modeling approaches allow us to account for these various factors to some extent. EXPERT OPINION Nonlinear mixed effects models help interpret analgesic data and their use is increasing. The PK is relatively well understood. The next investigative step will involve investigation into covariate effects for PD. Mathematical functions for both placebo models and dropout models are well described and should be incorporated into analgesic effectiveness studies that investigate a range of doses. Improvements in pain assessment tools and a greater understanding of pharmacogenomics factors will help individualize analgesic therapy.
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Affiliation(s)
- Brian J Anderson
- a University of Auckland School of Medicine, Department of Anaesthesiology , Auckland, New Zealand +64 9 3074903 ; +64 9 3098989 ;
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Nyberg J, Bazzoli C, Ogungbenro K, Aliev A, Leonov S, Duffull S, Hooker AC, Mentré F. Methods and software tools for design evaluation in population pharmacokinetics-pharmacodynamics studies. Br J Clin Pharmacol 2015; 79:6-17. [PMID: 24548174 PMCID: PMC4294071 DOI: 10.1111/bcp.12352] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2013] [Accepted: 02/09/2014] [Indexed: 11/26/2022] Open
Abstract
Population pharmacokinetic (PK)-pharmacodynamic (PKPD) models are increasingly used in drug development and in academic research; hence, designing efficient studies is an important task. Following the first theoretical work on optimal design for nonlinear mixed-effects models, this research theme has grown rapidly. There are now several different software tools that implement an evaluation of the Fisher information matrix for population PKPD. We compared and evaluated the following five software tools: PFIM, PkStaMp, PopDes, PopED and POPT. The comparisons were performed using two models, a simple-one compartment warfarin PK model and a more complex PKPD model for pegylated interferon, with data on both concentration and response of viral load of hepatitis C virus. The results of the software were compared in terms of the standard error (SE) values of the parameters predicted from the software and the empirical SE values obtained via replicated clinical trial simulation and estimation. For the warfarin PK model and the pegylated interferon PKPD model, all software gave similar results. Interestingly, it was seen, for all software, that the simpler approximation to the Fisher information matrix, using the block diagonal matrix, provided predicted SE values that were closer to the empirical SE values than when the more complicated approximation was used (the full matrix). For most PKPD models, using any of the available software tools will provide meaningful results, avoiding cumbersome simulation and allowing design optimization.
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Affiliation(s)
- Joakim Nyberg
- Department of Pharmaceutical Biosciences, Uppsala UniversityUppsala, Sweden
| | - Caroline Bazzoli
- Laboratoire Jean Kuntzmann, Département Statistique, University of GrenobleGrenoble, France
| | - Kay Ogungbenro
- Centre for Applied Pharmacokinetic Research, School of Pharmacy and Pharmaceutical Sciences, University of ManchesterManchester, UK
| | - Alexander Aliev
- Institute for Systems Analysis, Russian Academy of SciencesMoscow, Russia
| | | | | | - Andrew C Hooker
- Department of Pharmaceutical Biosciences, Uppsala UniversityUppsala, Sweden
| | - France Mentré
- INSERM U738 and University Paris DiderotParis, France
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Åsberg A, Bjerre A, Neely M. New algorithm for valganciclovir dosing in pediatric solid organ transplant recipients. Pediatr Transplant 2014; 18:103-11. [PMID: 24152053 PMCID: PMC3880615 DOI: 10.1111/petr.12179] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/17/2013] [Indexed: 11/30/2022]
Abstract
CMV infections are common after SOT. v-GCV is increasingly used in children. The aim of this study was to evaluate presently used dosing algorithms. Data from 104 pediatric SOT recipients (kidney, liver, and heart) aged 0.3-16.9 yr and receiving v-GCV once a day were used for model development and validation with the Pmetrics package for R. Monte Carlo simulations were performed to compare the probability of a GCV AUC 40-60 mg*h/L with the different algorithms across a range of ages, weights, and GFRs. GCV pharmacokinetics was well described by the non-parametric model. Clearance was dependent on GFR and Cockcroft-Gault estimates improved the model fit over Schwartz. Simulations showed that our new algorithm, where v-GCV dose is: Weight [kg]*(0.07*GFR [mL/min]+k), where k = 5 for GFR ≤ 30 mL/min, k = 10 for GFR > 30 mL/min and weight > 30 kg and k = 15 for GFR > 30 mL/min and weight ≤ 30 kg, outperformed the other algorithms. Thirty-three percent of all patients achieve an exposure above and 21% within the therapeutic window. We propose a simple algorithm for initial v-GCV dosing that standardizes plasma drug exposure better than current algorithms. Subsequent TDM is strongly suggested to achieve individual drug levels within the therapeutic window.
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Affiliation(s)
- A Åsberg
- Department of Pharmaceutical Biosciences, School of Pharmacy, University of OsloOslo, Norway
| | - A Bjerre
- Department of Pediatrics, Oslo University Hospital-RikshospitaletOslo, Norway
| | - M Neely
- Laboratory of Applied Pharmacokinetics, University of Southern CaliforniaLos Angeles, CA, USA
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Ryan EG, Drovandi CC, Thompson MH, Pettitt AN. Towards Bayesian experimental design for nonlinear models that require a large number of sampling times. Comput Stat Data Anal 2014. [DOI: 10.1016/j.csda.2013.08.017] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Phelps DL, Ward RM, Williams RL, Watterberg KL, Laptook AR, Wrage LA, Nolen TL, Fennell TR, Ehrenkranz RA, Poindexter BB, Cotten CM, Hallman MK, Frantz ID, Faix RG, Zaterka-Baxter KM, Das A, Ball MB, O’Shea TM, Lacy CB, Walsh MC, Shankaran S, Sánchez PJ, Bell EF, Higgins RD. Pharmacokinetics and safety of a single intravenous dose of myo-inositol in preterm infants of 23-29 wk. Pediatr Res 2013; 74:721-9. [PMID: 24067395 PMCID: PMC3962781 DOI: 10.1038/pr.2013.162] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2013] [Accepted: 05/13/2013] [Indexed: 11/10/2022]
Abstract
BACKGROUND Myo-inositol given to preterm infants with respiratory distress has reduced death, increased survival without bronchopulmonary dysplasia, and reduced severe retinopathy of prematurity in two randomized trials. Pharmacokinetic (PK) studies in extremely preterm infants are needed before efficacy trials. METHODS Infants born in 23-29 wk of gestation were randomized to a single intravenous (i.v.) dose of inositol at 60 or 120 mg/kg or placebo. Over 96 h, serum levels (sparse sampling population PK) and urine inositol excretion were determined. Population PK models were fit using a nonlinear mixed-effects approach. Safety outcomes were recorded. RESULTS A single-compartment model that included factors for endogenous inositol production, allometric size based on weight, gestational age strata, and creatinine clearance fit the data best. The central volume of distribution was 0.5115 l/kg, the clearance was 0.0679 l/kg/h, endogenous production was 2.67 mg/kg/h, and the half-life was 5.22 h when modeled without the covariates. During the first 12 h, renal inositol excretion quadrupled in the 120 mg/kg group, returning to near-baseline value after 48 h. There was no diuretic side effect. No significant differences in adverse events occurred among the three groups (P > 0.05). CONCLUSION A single-compartment model accounting for endogenous production satisfactorily described the PK of i.v. inositol.
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Affiliation(s)
- Dale L. Phelps
- University of Rochester School of Medicine and Dentistry, Rochester, NY, USA,Corresponding author. Dale L. Phelps, MD, Department of Pediatrics, University of Rochester School of Medicine and Dentistry, 30250 S. Highway 1, Gualala, CA, 95445, , phone: (707) 884-3930
| | - Robert M. Ward
- Department of Pediatrics, Division of Neonatology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Rick L. Williams
- Statistics and Epidemiology Unit, RTI International, Research Triangle Park, NC, USA
| | | | - Abbot R. Laptook
- Department of Pediatrics, Women & Infants’ Hospital, Brown University, Providence, RI, USA
| | - Lisa A. Wrage
- Statistics and Epidemiology Unit, RTI International, Research Triangle Park, NC, USA
| | - Tracy L. Nolen
- Statistics and Epidemiology Unit, RTI International, Research Triangle Park, NC, USA
| | - Timothy R. Fennell
- Pharmacology and Toxicology Division, RTI International, Research Triangle Park, NC, USA
| | | | - Brenda B. Poindexter
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - Mikko K. Hallman
- Department of Pediatrics, University of Oulu, and Oulu University Hospital, Oulu, Finland
| | - Ivan D. Frantz
- Department of Pediatrics, Division of Newborn Medicine, Floating Hospital for Children, Tufts Medical Center, Boston, MA, USA
| | - Roger G. Faix
- Department of Pediatrics, Division of Neonatology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | | | - Abhik Das
- Statistics and Epidemiology Unit, RTI International, Rockville, MD, USA
| | - M. Bethany Ball
- Department of Pediatrics, Division of Neonatal and Developmental Medicine, Stanford University School of Medicine and Lucile Packard Children's Hospital, Palo Alto, CA, USA
| | | | | | - Michele C. Walsh
- Department of Pediatrics, Rainbow Babies & Children’s Hospital, Case Western Reserve University, Cleveland, OH, USA
| | - Seetha Shankaran
- Department of Pediatrics, Wayne State University, Detroit, MI, USA
| | - Pablo J. Sánchez
- Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Edward F. Bell
- Department of Pediatrics, University of Iowa, Iowa City, IA, USA
| | - Rosemary D. Higgins
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
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Monitoring Salivary Melatonin Concentrations in Children With Sleep Disorders Using Liquid Chromatography–Tandem Mass Spectrometry. Ther Drug Monit 2013; 35:388-95. [DOI: 10.1097/ftd.0b013e3182885cb2] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Trial Treatment Length Optimization With an Emphasis on Disease Progression Studies. J Clin Pharmacol 2013; 49:323-35. [DOI: 10.1177/0091270008329560] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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Mallaysamy S, Johnson MG, Rao PGM, Rajakannan T, Bathala L, Arumugam K, van Hasselt JGC, Ramakrishna D. Population pharmacokinetics of lamotrigine in Indian epileptic patients. Eur J Clin Pharmacol 2012; 69:43-52. [DOI: 10.1007/s00228-012-1311-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2012] [Accepted: 05/09/2012] [Indexed: 11/28/2022]
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Fischer JH, Sarto GE, Habibi M, Kilpatrick SJ, Tuomala RE, Shier JM, Wollett L, Fischer PA, Khorana KS, Rodvold KA. Influence of body weight, ethnicity, oral contraceptives, and pregnancy on the pharmacokinetics of azithromycin in women of childbearing age. Antimicrob Agents Chemother 2012; 56:715-24. [PMID: 22106226 PMCID: PMC3264225 DOI: 10.1128/aac.00717-11] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2011] [Accepted: 11/16/2011] [Indexed: 11/20/2022] Open
Abstract
Women of childbearing age commonly receive azithromycin for the treatment of community-acquired infections, including during pregnancy. This study determined azithromycin pharmacokinetics in pregnant and nonpregnant women and identified covariates contributing to pharmacokinetic variability. Plasma samples were collected by using a sparse-sampling strategy from pregnant women at a gestational age of 12 to 40 weeks and from nonpregnant women of childbearing age receiving oral azithromycin for the treatment of an infection. Pharmacokinetic data from extensive sampling conducted on 12 healthy women were also included. Plasma samples were assayed for azithromycin by high-performance liquid chromatography. Population data were analyzed by nonlinear mixed-effects modeling. The population analysis included 53 pregnant and 25 nonpregnant women. A three-compartment model with first-order absorption and a lag time provided the best fit of the data. Lean body weight, pregnancy, ethnicity, and the coadministration of oral contraceptives were covariates identified as significantly influencing the oral clearance of azithromycin and, except for oral contraceptive use, intercompartmental clearance between the central and second peripheral compartments. No other covariate relationships were identified. Compared to nonpregnant women not receiving oral contraceptives, a 21% to 42% higher dose-adjusted azithromycin area under the plasma concentration-time curve (AUC) occurred in non-African American women who were pregnant or receiving oral contraceptives. Conversely, azithromycin AUCs were similar between pregnant African American women and nonpregnant women not receiving oral contraceptives. Although higher levels of maternal and fetal azithromycin exposure suggest that lower doses be administered to non-African American women during pregnancy, the consideration of azithromycin pharmacodynamics during pregnancy should guide any dose adjustments.
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Affiliation(s)
- James H. Fischer
- Department of Pharmacy Practice, College of Pharmacy, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Gloria E. Sarto
- Department of Obstetrics and Gynecology, School of Medicine and Public Health, University of Wisconsin—Madison, and University of Wisconsin Obstetrics Service, Meriter Hospital, Madison, Wisconsin, USA
| | - Mitra Habibi
- Department of Pharmacy Practice, College of Pharmacy, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Sarah J. Kilpatrick
- Department of Obstetrics and Gynecology, College of Medicine, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Ruth E. Tuomala
- Department of Obstetrics and Gynecology, Brigham & Women's Hospital, Harvard University School of Medicine, Boston, Massachusetts, USA
| | - Janice M. Shier
- Department of Obstetrics and Gynecology, College of Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Lori Wollett
- Office of Clinical Trials, University of Wisconsin—Madison, and School of Medicine and Public Health, University of Wisconsin—Madison, Madison, Wisconsin, USA
| | - Patricia A. Fischer
- Department of Pharmacy Practice, College of Pharmacy, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Kinnari S. Khorana
- Department of Pharmacy Practice, College of Pharmacy, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Keith A. Rodvold
- Department of Pharmacy Practice, College of Pharmacy, University of Illinois at Chicago, Chicago, Illinois, USA
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van Hasselt JGC, Green B, Morrish GA. Leveraging physiological data from literature into a pharmacokinetic model to support informative clinical study design in pregnant women. Pharm Res 2012; 29:1609-17. [PMID: 22246291 DOI: 10.1007/s11095-012-0671-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2011] [Accepted: 01/03/2012] [Indexed: 12/12/2022]
Abstract
PURPOSE Physiological changes during pregnancy can effect pharmacokinetic (PK) parameters, which may lead to altered dose requirements. We aimed to leverage literature-based physiological changes during pregnancy into a PK model and compare its performance to a published reference model in pregnant women and to use the literature-based model to determine informative PK sampling times for a clinical study that aims to quantify the PK of enoxaparin throughout pregnancy. METHODS Changes in total body water (BW) and creatinine clearance (CRCL) during pregnancy were described using regression models. BW and CRCL were linked to a PK model of enoxaparin in non-pregnant women. Performance of the literature-based PK model was compared to a previously published empirical reference model. D-optimal sampling times were determined and evaluated for literature-based and reference models. RESULTS The literature-based model adequately predicted anti-Xa plasma concentrations when compared to reference model predictions. An informative sampling design was successfully developed, with parameters expected with good precision (RSE < 36.4%). CONCLUSION A literature-based model describing enoxaparin PK during pregnancy was developed and evaluated. The modelling framework could be used to support development of informative designs in pregnancy when prior models are unavailable.
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Affiliation(s)
- J G Coen van Hasselt
- Department of Pharmacy and Pharmacology, Netherlands Cancer Institute/Slotervaart Hospital, Louwesweg 6, PO Box 90440, 1006 BK, Amsterdam, The Netherlands.
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Aliev A, Fedorov V, Leonov S, McHugh B, Magee M. PkStaMp Library for Constructing Optimal Population Designs for PK/PD Studies. COMMUN STAT-SIMUL C 2012. [DOI: 10.1080/03610918.2012.625273] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
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Wang Y, Eskridge KM, Nadarajah S. Optimal design of mixed-effects PK/PD models based on differential equations. J Biopharm Stat 2011; 22:180-205. [PMID: 22204534 DOI: 10.1080/10543406.2010.513465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
Abstract
There is a vast literature on the analysis of optimal design of nonlinear mixed-effects models (NLMMs) described by ordinary differential equations (ODEs) with analytic solution. However, much less has been published on the design of trials to fit such models with nonanalytic solution. In this article, we use the "direct" method to find parameter sensitivities, which are required during the optimization of models defined as ODEs, and apply them to find D-optimal designs for various specific situations relevant to population pharmacokinetic studies using a particular model with first-order absorption and elimination. In addition, we perform two simulation studies. The first one aims to show that the criterion computed from the development of the Fisher information matrix expression is a good measure to compare and optimize population designs, thus avoiding a large number of simulations; In the second one, a sensitivity analysis with respect to parameter misspecification allows us to compare the robustness of different population designs constructed in this article.
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Affiliation(s)
- Yi Wang
- Department of Statistics, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
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Duffull SB, Graham G, Mengersen K, Eccleston J. Evaluation of the Pre-Posterior Distribution of Optimized Sampling Times for the Design of Pharmacokinetic Studies. J Biopharm Stat 2011; 22:16-29. [DOI: 10.1080/10543406.2010.500065] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
Affiliation(s)
| | | | - Kerrie Mengersen
- c Mathematical Sciences , Queensland University of Technology , Brisbane , Australia
| | - John Eccleston
- d School of Physical Sciences , University of Queensland , Brisbane , Australia
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Sherwin CMT, Ding L, Kaplan J, Spigarelli MG, Vinks AA. Optimal study design for pioglitazone in septic pediatric patients. J Pharmacokinet Pharmacodyn 2011; 38:433-47. [PMID: 21667139 DOI: 10.1007/s10928-011-9202-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2011] [Accepted: 05/26/2011] [Indexed: 01/05/2023]
Abstract
The objective was to demonstrate the methodology and process of optimal sparse sampling pharmacokinetics (PK). This utilized a single daily dose of pioglitazone for pediatric patients with severe sepsis and septic shock based upon adult and minimal adolescent data. Pioglitazone pharmacokinetics were modeled using non-compartment analysis WinNonlin Pro (version 5.1) and population kinetics using NONMEM (version 7.1) with first order conditional estimation method (FOCE) with interaction. The initial model was generated from single- and multiple-dose pioglitazone PK data (15 mg, 30 mg, and 45 mg) in 36 adolescents with diabetes. PK models were simulated and overlaid upon original data to provide a comparison best described by a single compartment, first order model. The optimal design was based on the simulated oral administration of pioglitazone to three groups of pediatric patients, age 3.8 (2-6 years), weight 14.4 (7-28 kg); age 9.6 (6.1-11.9 years), weight 36.5 (28.1-48 kg) and age 15.5 (12-17 years,) weight 61.6 (48.1-80 kg). PFIM (version 3.2) was used to evaluate sample study size. Datasets were compiled using simulation for each dose (15, 30 and 45 mg) for the potential age/weight groups. A target dose of 15 mg daily in the youngest and middle groups was considered appropriate with area under the curve exposure levels (AUC) comparable to studies in adolescents. The final optimal design suggested time points of 0.5, 2, 6 and 21 h for 24 h dosing. This methodology provides a robust method of utilizing adult and limited adolescent data to simulate allometrically scaled, pediatric data sets that allow the optimal design of a pediatric trial. The pharmacokinetics of pioglitazone were described adequately and simulated data estimates were comparable to literature values. The optimal design provided clinically attainable sample times and windows.
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Affiliation(s)
- Catherine M T Sherwin
- Division of Clinical Pharmacology, Cincinnati Children's Hospital Medical Center, OH, USA.
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Population Pharmacokinetic Modeling and Optimal Sampling Strategy for Bayesian Estimation of Amikacin Exposure in Critically Ill Septic Patients. Ther Drug Monit 2010; 32:749-56. [DOI: 10.1097/ftd.0b013e3181f675c2] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Steimer JL, Dahl SG, De Alwis DP, Gundert-Remy U, Karlsson MO, Martinkova J, Aarons L, Ahr HJ, Clairambault J, Freyer G, Friberg LE, Kern SE, Kopp-Schneider A, Ludwig WD, De Nicolao G, Rocchetti M, Troconiz IF. Modelling the genesis and treatment of cancer: the potential role of physiologically based pharmacodynamics. Eur J Cancer 2010; 46:21-32. [PMID: 19954965 DOI: 10.1016/j.ejca.2009.10.011] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2009] [Revised: 09/30/2009] [Accepted: 10/09/2009] [Indexed: 12/01/2022]
Abstract
Physiologically based modelling of pharmacodynamics/toxicodynamics requires an a priori knowledge on the underlying mechanisms causing toxicity or causing the disease. In the context of cancer, the objective of the expert meeting was to discuss the molecular understanding of the disease, modelling approaches used so far to describe the process, preclinical models of cancer treatment and to evaluate modelling approaches developed based on improved knowledge. Molecular events in cancerogenesis can be detected using 'omics' technology, a tool applied in experimental carcinogenesis, but also for diagnostics and prognosis. The molecular understanding forms the basis for new drugs, for example targeting protein kinases specifically expressed in cancer. At present, empirical preclinical models of tumour growth are in great use as the development of physiological models is cost and resource intensive. Although a major challenge in PKPD modelling in oncology patients is the complexity of the system, based in part on preclinical models, successful models have been constructed describing the mechanism of action and providing a tool to establish levels of biomarker associated with efficacy and assisting in defining biologically effective dose range selection for first dose in man. To follow the concentration in the tumour compartment enables to link kinetics and dynamics. In order to obtain a reliable model of tumour growth dynamics and drug effects, specific aspects of the modelling of the concentration-effect relationship in cancer treatment that need to be accounted for include: the physiological/circadian rhythms of the cell cycle; the treatment with combinations and the need to optimally choose appropriate combinations of the multiple agents to study; and the schedule dependence of the response in the clinical situation.
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Standing JF, Hammer GB, Sam WJ, Drover DR. Pharmacokinetic-pharmacodynamic modeling of the hypotensive effect of remifentanil in infants undergoing cranioplasty. Paediatr Anaesth 2010; 20:7-18. [PMID: 19825011 DOI: 10.1111/j.1460-9592.2009.03174.x] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
OBJECTIVES Although remifentanil has been used to induce hypotension during surgery in infants, no pharmacokinetic-pharmacodynamic (PKPD) model exists for its quantitative analysis. Our aim was to determine the quantitative relationship between whole blood remifentanil concentration and its hypotensive effect during surgery in infants. METHODS/MATERIALS We studied seven infants (age 0.3-1 year) who underwent cranioplasty surgery and received remifentanil delivered by a computer-controlled infusion pump during the maintenance of anesthesia. Arterial blood samples to determine remifentanil concentration and mean arterial blood pressure (MAP) measurements were collected. A simultaneous PKPD mixed-effects model was built in NONMEM. RESULTS A total of 77 remifentanil concentrations and 185 MAP measurements were collected. Remifentanil pharmacokinetics was described with a two-compartment model, parameter estimates were 2.99 l x min(-1) x 70 kg(-1) for clearance and 16.23 l x 70 kg(-1) for steady state volume of distribution. Mean baseline MAP was 69.7 mmHg and was decreased as per clinical requirements. A sigmoidal E(max) model driven by an effect compartment described the decrease in MAP, with an estimated concentration to decrease MAP by half (EC(50)) being 17.1 ng x ml(-1). CONCLUSIONS Remifentanil is effective in causing hypotension. The final model predicts that a steady state remifentanil concentration of 14 ng.ml(-1) would typically achieve a 30% decrease in MAP.
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Affiliation(s)
- Joseph F Standing
- Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden
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Effects of CYP2C19 and CYP2C9 genotypes on pharmacokinetic variability of valproic acid in Chinese epileptic patients: nonlinear mixed-effect modeling. Eur J Clin Pharmacol 2009; 65:1187-93. [DOI: 10.1007/s00228-009-0712-x] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2009] [Accepted: 07/22/2009] [Indexed: 11/25/2022]
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Han PY, Kirkpatrick CMJ, Green B. Informative study designs to identify true parameter–covariate relationships. J Pharmacokinet Pharmacodyn 2009; 36:147-63. [DOI: 10.1007/s10928-009-9115-y] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2008] [Accepted: 03/16/2009] [Indexed: 10/21/2022]
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Garcia-Bournissen F, Altcheh J, Giglio N, Mastrantonio G, Della Védova CO, Koren G. Pediatric clinical pharmacology studies in Chagas disease: focus on Argentina. Paediatr Drugs 2009; 11:33-7. [PMID: 19127950 DOI: 10.2165/0148581-200911010-00012] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Chagas disease is a neglected parasitic disease endemic in the Americas. It mainly affects impoverished populations and the acute phase of the infection mostly affects children. Many cases have also been detected in nonendemic countries as a result of recent migratory trends. The chronic phase is relatively asymptomatic, but 30% of patients with chronic infection eventually develop cardiac and digestive complications that commonly lead to death or disability. Only two drugs are available for the treatment of Chagas disease, benznidazole and nifurtimox. These drugs have been shown to be effective in the treatment of both acute and early chronic phases in children, but the pharmacokinetics of these drugs have never been studied in this population. We have set out to conduct a pharmacokinetics study of benznidazole in a pediatric population with Chagas disease. The results of this study are expected to allow better estimation of the optimal doses and schedule of pharmacotherapy for Chagas disease in children.
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Affiliation(s)
- Facundo Garcia-Bournissen
- Division of Clinical Pharmacology and Toxicology, Hospital for Sick Children, University of Toronto, Ontario, Canada.
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McGree JM, Eccleston JA, Duffull SB. Simultaneous versus sequential optimal design for pharmacokinetic-pharmacodynamic models with FO and FOCE considerations. J Pharmacokinet Pharmacodyn 2009; 36:101-23. [PMID: 19224348 DOI: 10.1007/s10928-009-9113-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2007] [Accepted: 02/03/2009] [Indexed: 10/21/2022]
Abstract
We consider nested multiple response models which are used extensively in the area of pharmacometrics. Given the conditional nature of such models, differences in predicted responses are a consequence of different assumptions about how the models interact. As such, sequential versus simultaneous and First Order (FO) versus First Order Conditional Estimation (FOCE) techniques have been explored in the literature where it was found that the sequential and FO approaches can produce biased results. It is therefore of interest to determine any design consequences between the various methods and approximations. As optimal design for nonlinear mixed effects models is dependent upon initial parameter estimates and an approximation to the expected Fisher information matrix, it is necessary to incorporate any influence of nonlinearity (or parameter-effects curvature) into our exploration. Hence, sequential versus simultaneous design with FO and FOCE considerations are compared under low, typical and high degrees of nonlinearity. Additionally, predicted standard errors of parameters are also compared to empirical estimates formed via a simulation/estimation study in NONMEM. Initially, design theory for nested multiple response models is developed and approaches mentioned above are investigated by considering a pharmacokinetic-pharmacodynamic model found in the literature. We consider design for situations where all responses are continuous and extend this methodology to the case where a response may be a discrete random variable. In particular, for a binary response pharmacodynamic model, it is conjectured that such responses will offer little information about all parameters and hence a sequential optimization, in the form of product design optimality, may yield near optimal designs.
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Affiliation(s)
- J M McGree
- University of Queensland, St. Lucia, Brisbane, Australia.
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Charles B, Touitou Y, Selmaoui B. A population Pharmacokinetic Turnover and Surge‐Function Model for Describing Melatonin Biological Rhythm in Healthy Male Subjects. J Pharm Sci 2009; 98:782-90. [DOI: 10.1002/jps.21407] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
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Ogungbenro K, Aarons L. Optimisation of sampling windows design for population pharmacokinetic experiments. J Pharmacokinet Pharmacodyn 2008; 35:465-82. [PMID: 18780163 DOI: 10.1007/s10928-008-9097-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2007] [Accepted: 08/20/2008] [Indexed: 10/21/2022]
Abstract
This paper describes an approach for optimising sampling windows for population pharmacokinetic experiments. Sampling windows designs are more practical in late phase drug development where patients are enrolled in many centres and in out-patient clinic settings. Collection of samples under the uncontrolled environment at these centres at fixed times may be problematic and can result in uninformative data. Population pharmacokinetic sampling windows design provides an opportunity to control when samples are collected by allowing some flexibility and yet provide satisfactory parameter estimation. This approach uses information obtained from previous experiments about the model and parameter estimates to optimise sampling windows for population pharmacokinetic experiments within a space of admissible sampling windows sequences. The optimisation is based on a continuous design and in addition to sampling windows the structure of the population design in terms of the proportion of subjects in elementary designs, number of elementary designs in the population design and number of sampling windows per elementary design is also optimised. The results obtained showed that optimal sampling windows designs obtained using this approach are very efficient for estimating population PK parameters and provide greater flexibility in terms of when samples are collected. The results obtained also showed that the generalized equivalence theorem holds for this approach.
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Affiliation(s)
- Kayode Ogungbenro
- Centre for Applied Pharmacokinetic Research, The University of Manchester, Manchester, UK.
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Abstract
BACKGROUND There are few data describing dexmedetomidine population pharmacokinetics (PK) in children (0-15 years) despite increasing use. METHODS An open-label study was undertaken to examine the PK of i.v. dexmedetomidine 1-4 mug.kg(-1) bolus in children after cardiac surgery (n = 45). A population PK analysis of dexmedetomidine time-concentration profiles (148 observations) was undertaken using nonlinear mixed effects modeling. Estimates were standardized to a 70-kg adult using allometric size models. RESULTS Children had a mean age of 3.38 years (range 4 days to 14 years) and weight 15.1 kg (range 3.1-58.9 kg). A two-compartment disposition model with first order elimination was superior to a one-compartment model. Population parameter estimates (between subject variability) were clearance (CL) 39.2 (CV 30.36%) l.h(-1) per 70 kg, central volume of distribution (V1) 36.9 (69.49%) l per 70 kg, inter-compartment clearance (Q) 68.2 (37.6%) l.h(-1) per 70 kg and peripheral volume of distribution (V2) 69.9 (48.6%) l per 70 kg. Clearance at birth was 15.55 l.h(-1) per 70 kg and matured with a half-time of 46.5 weeks to reach 87% adult rate by 1 year of age. Simulation of an infusion of 1 mug.kg(-1) over 10 min followed by an infusion of 0.7 mug.kg(-1).h(-1) for 50 min suggested that children arouse from sedation at a plasma concentration of 0.304 mug.l(-1). CONCLUSIONS Clearance in neonates is approximately one-third of that described in adults, consistent with immature elimination pathways. Maintenance dosing, which is a function of clearance, should be reduced in neonates and infants when using a target concentration approach.
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Roos JF, Kirkpatrick CMJ, Tett SE, McLachlan AJ, Duffull SB. Development of a sufficient design for estimation of fluconazole pharmacokinetics in people with HIV infection. Br J Clin Pharmacol 2008; 66:455-66. [PMID: 18699833 DOI: 10.1111/j.1365-2125.2008.03247.x] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
AIMS To assess an optimal design that is sufficient to gain precise estimates of the pharmacokinetic (PK) parameters for fluconazole in people with HIV infection. METHODS Two studies were identified, the first in healthy volunteers and the second in HIV patients. The investigators (J.F.R. and S.B.D.) were blinded to the second study results. The healthy volunteer study was modelled and a design was found to estimate the PK parameters. The design was evaluated by comparison of the standard errors of the parameters and the predictive performance of the optimal design. The predictive performance was assessed by comparing model predictions against observed concentrations for two models. The first model, termed 'sufficient design', was developed from data extracted from the HIV study that corresponded to the optimal design. The second model, termed 'HIV outcome model', by modelling all the data from the HIV study. RESULTS An optimal design HIV study was developed which had considerably fewer blood samples and dosing arms compared with the actual HIV study. The optimized design performed as well as the actual HIV study in terms of parameter precision. The performance of the design, described as the precision (mg l(-1))(2) (95% confidence interval) of the predicted concentrations to the actual concentrations for the 'sufficient design' and 'HIV outcome model' models were: 0.63 (0.40, 0.87) and 0.56 (0.32, 0.79), respectively. CONCLUSION This study demonstrates how data from healthy volunteers can be utilized via optimal design methodology to design a successful study in the target population.
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Affiliation(s)
- Juliana F Roos
- School of Pharmacy, University of Queensland, Brisbane, Australia
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An alternative method for population pharmacokinetic data analysis under noncompliance. J Pharmacokinet Pharmacodyn 2008; 35:219-33. [PMID: 18299967 DOI: 10.1007/s10928-008-9085-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2007] [Accepted: 02/11/2008] [Indexed: 10/22/2022]
Abstract
Noncompliance presents a persistent problem while analyzing PK data from outpatient clinical studies. Ignoring dose omission or making uninformed assumptions about patient drug intake history can prove detrimental to the objectives of the analysis (e.g. determining the PK model parameters or identifying covariates) and ultimately compromise the interpretation of the data. In order to overcome this problem, an alternative method of handling noncompliant data is evaluated in this report. The proposed approach is based on the principle of superposition and works by separating the estimation of the elimination rate from the model based steady-state PK concentration. Simulations implementing this method under different scenarios of noncompliance demonstrate that it performs better than the conventional method of analyzing population PK data when compared on the basis of bias and imprecision in parameter estimation and power (and type I error) for covariate detection. Overall, the new method exhibits great potential to address the issue of uncertain/unreliable dosing histories frequently encountered in clinical trials.
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Tod M, Jullien V, Pons G. Facilitation of Drug Evaluation in Children by Population Methods and Modelling†. Clin Pharmacokinet 2008; 47:231-43. [DOI: 10.2165/00003088-200847040-00002] [Citation(s) in RCA: 152] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
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Zandvliet AS, Schellens JHM, Beijnen JH, Huitema ADR. Population Pharmacokinetics and Pharmacodynamics for Treatment Optimization??in Clinical Oncology. Clin Pharmacokinet 2008; 47:487-513. [DOI: 10.2165/00003088-200847080-00001] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
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McGree JM, Duffull SB, Eccleston JA, Ward LC. Optimal designs for studying bioimpedance. Physiol Meas 2007; 28:1465-83. [DOI: 10.1088/0967-3334/28/12/002] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Jiang DC, Wang L, Wang YQ, Li L, Lu W, Bai XR. Population pharmacokinetics of valproate in Chinese children with epilepsy. Acta Pharmacol Sin 2007; 28:1677-84. [PMID: 17883957 DOI: 10.1111/j.1745-7254.2007.00704.x] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
AIM The aim of the present study is to establish a population pharmacokinetic (PPK) model of valproate (VPA) in Chinese epileptic children to promote the reasonable use of anti-epileptic drugs. METHODS Sparse data of VPA serum concentrations from 417 epileptic children were collected. These patients were divided into 2 groups: the PPK model group (n=317) and the PPK valid group (n=100). The PPK parameter values of VPA were calculated by NONMEM software using the data of the PPK model group. A basic model and a final model were set up. To validate the 2 models, the concentrations of PPK valid group were predicted by each model, respectively. The mean prediction error (MPE), mean squared prediction error (MSPE), root mean squared prediction error (RMSPE), weight residues (WRES), and the 95% confidence intervals (95% CI) were also calculated. Then, the values between the 2 models were compared. RESULTS The PPK of VPA was determined by a 1-compartment model with a first-order absorption process. The basic model was: Ka=3.09 (h(-1)), V/F=20.4 (L), CL/F=0.296 (L/h). The final model was: Ka=0.251+2.24 x (1-HS) (h(-1)), V/F=2.88+0.157 x WT (L), CL/F=0.106(0.98 x CO)+ 0.0157 x AGE (L/h). For the basic model, the MPE, MSPE, RMSPE, WRES, and the 95% CI were -23.53 (-30.36, -16.70), 3728.96 (2872.72, 4585.20), 39.62 (34.34, 44.90), and -0.06 (-0.14, 0.02), respectively. For the final model, the MPE, MSPE, RMSPE, WRES, and the 95% CI were -1.16 (-4.85, 2.53), 1002.83 (1050.64, 1143.61), 23.04 (21.12, 24.96), and 0.08 (-0.04, 0.20), respectively. The final model was more optimal than the basic model. CONCLUSION The PPK model of VPA in Chinese epileptic children was successfully established. It will be valuable to facilitate individualized dosage regimens.
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Affiliation(s)
- De-Chun Jiang
- Department of Pharmacy, Xuan-wu Hospital of Capital Medical University, Beijing 100053, China
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Hennig S, Waterhouse TH, Bell SC, France M, Wainwright CE, Miller H, Charles BG, Duffull SB. A d-optimal designed population pharmacokinetic study of oral itraconazole in adult cystic fibrosis patients. Br J Clin Pharmacol 2007; 63:438-50. [PMID: 17073891 PMCID: PMC2203246 DOI: 10.1111/j.1365-2125.2006.02778.x] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2006] [Accepted: 08/08/2006] [Indexed: 11/30/2022] Open
Abstract
AIM The primary objective of the study was to estimate the population pharmacokinetic parameters for itraconazole and hydroxy-itraconazole, in particular, the relative oral bioavailability of the capsule compared with solution in adult cystic fibrosis patients, in order to develop new dosing guidelines. A secondary objective was to evaluate the performance of a population optimal design. METHODS The blood sampling times for the population study were optimized previously using POPT v.2.0. The design was based on the administration of solution and capsules to 30 patients in a cross-over study. Prior information suggested that itraconazole is generally well described by a two-compartment disposition model with either linear or saturable elimination. The pharmacokinetics of itraconazole and the metabolite were modelled simultaneously using NONMEM. Dosing schedules were simulated to assess their ability to achieve a trough target concentration of 0.5 mg ml(-1). RESULTS Out of 241 blood samples, 94% were taken within the defined optimal sampling windows. A two-compartment model with first order absorption and elimination best described itraconazole kinetics, with first order metabolism to the hydroxy-metabolite. For itraconazole the absorption rate constants (between-subject variability) for capsule and solution were 0.0315 h(-1) (91.9%) and 0.125 h(-1) (106.3%), respectively, and the relative bioavailability of the capsule was 0.82 (62.3%) (confidence interval 0.36, 1.97), compared with the solution. There was no evidence of nonlinearity. Simulations from the final model showed that a dosing schedule of 500 mg twice daily for both formulations provided the highest chance of target success. CONCLUSION The optimal design performed well and the pharmacokinetics of itraconazole and hydroxy-itraconazole were described adequately by the model. The relative bioavailability for itraconazole capsules was 82% compared with the solution.
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Affiliation(s)
- Stefanie Hennig
- School of Pharmacy, The University of Queensland, Brisbane, Queensland, Australia.
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Anderson BJ, Allegaert K, Holford NHG. Population clinical pharmacology of children: general principles. Eur J Pediatr 2006; 165:741-6. [PMID: 16807730 DOI: 10.1007/s00431-006-0188-y] [Citation(s) in RCA: 75] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2006] [Accepted: 05/11/2006] [Indexed: 10/24/2022]
Abstract
INTRODUCTION Population modelling using mixed-effects models provides a means to study variability in drug responses among individuals representative of those for whom the drug will be used clinically. DISCUSSION The advantages of these models in paediatric studies are that they can be used to analyse sparse data, sampling times are not crucial and can be fitted around clinical procedures and individuals with missing data may still be included in the analysis. The introduction of explanatory covariates explains the predictable part of the between-individual variability. Simulations using parameter estimates and their variability can be used to investigate large numbers of children--many more than is possible in studies dealing with real children--for a fraction of the cost, which is an advantage when developing clinical trials. Paediatric population modelling has expanded greatly in the past decade and is now a routine procedure during the development and investigation of drugs. Children have benefitted and will continue to benefit from this approach.
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Affiliation(s)
- Brian J Anderson
- Department of Anaesthesiology, University of Auckland, Auckland, New Zealand.
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