Reporting a Population Pharmacokinetic–Pharmacodynamic Study: A Journal’s Perspective

Jamsen, Kris; McLeay, Sarah; Barras, Michael; Green, Bruce

doi:10.1007/s40262-013-0114-1

Cited by 41 publications

(33 citation statements)

References 24 publications

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“…Overall, the published population analyses were assessed following the suggested guidelines. 83 The model structure largely depended on the sampling strategy ( Figure 3). A 2-compartment model with delayed absorption was found to best describe the full tacrolimus concentration-time profile and thus should be used to correctly characterize drug exposure (ie, AUC).…”

Section: Discussionmentioning

confidence: 99%

Population Pharmacokinetics of Tacrolimus in Transplant Recipients: What Did We Learn About Sources of Interindividual Variabilities?

Campagne

Mager

Tornatore

2018

The Journal of Clinical Pharma

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Tacrolimus, a calcineurin inhibitor, is a common immunosuppressant prescribed after organ transplantation and has notable inter-and intrapatient pharmacokinetic variability. The sources of variability have been investigated using population pharmacokinetic modeling over the last 2 decades. This article provides an updated synopsis on published nonlinear mixed-effects analyses developed for tacrolimus in transplant recipients. The objectives were to establish a detailed overview of the current data and to investigate covariate relationships determined by the models. Sixty-three published analyses were reviewed, and data regarding the study design, modeling approach, and resulting findings were extracted and summarized. Most of the studies investigated tacrolimus pharmacokinetics in adult and pediatric renal and liver transplants after administration of the immediate-release formulation. Model structures largely depended on the study sampling strategy, with ß50% of studies developing a 1-compartment model using trough concentrations and a 2-compartment model with delayed absorption from intensive sampling. The CYP3A5 genotype, as a covariate, consistently impacted tacrolimus clearance, and dosing adjustments were required to achieve similar drug exposure among patients. Numerous covariates were identified as sources of interindividual variability on tacrolimus pharmacokinetics with limited consistency across these studies, which may be the result of the study designs. Additional analyses are required to further evaluate the potential impact of these covariates and the clinical implementation of these models to guide tacrolimus dosing recommendations. This article may be useful for guiding the design of future population pharmacokinetic studies and provides recommendations for the selection of an existing optimal model to individualize tacrolimus therapy.

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Section: Discussionmentioning

confidence: 99%

Population Pharmacokinetics of Tacrolimus in Transplant Recipients: What Did We Learn About Sources of Interindividual Variabilities?

Campagne

Mager

Tornatore

2018

The Journal of Clinical Pharma

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“…Population PK/PD analyses enable a quantitative understanding of the time course of drug effects including the influence of subject‐specific factors, i.e. covariates such as body weight, sex, and age, and provide a key tool for in silico studying of scenarios not clinically tested . Due to its long t 1/2 , studying the effects of cenerimod under steady‐state conditions requires long treatment durations that are impractical or not ethical to study in healthy subjects.…”

Section: Introductionmentioning

confidence: 99%

“…covariates such as body weight, sex, and age, and provide a key tool for in silico studying of scenarios not clinically tested. 16 Due to its long t 1/2 , studying the effects of cenerimod under steady-state conditions requires long treatment durations that are impractical or not ethical to study in healthy subjects. Model simulations and predictions can fill some knowledge gaps (prediction of attainment of steady state, long-term extrapolation, bridging from healthy subjects to SLE patients).…”

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confidence: 99%

Modelling pharmacokinetics and pharmacodynamics of the selective S1P₁ receptor modulator cenerimod in healthy subjects and systemic lupus erythematosus patients

Lott

Juif

Dingemanse

et al. 2020

Brit J Clinical Pharma

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Aims Assessment of time to attain steady state as well as drug accumulation following long‐term treatment with the selective sphingosine‐1‐phosphate 1 receptor modulator cenerimod and prediction of the incidence of low total lymphocyte (LY) counts. Differences in pharmacokinetics and pharmacodynamics based on demographic characteristics and between healthy subjects and systemic lupus erythematosus (SLE) patients were to be identified. Methods Data from 4 Phase I studies and 1 Phase II study were pooled to develop a population pharmacokinetic/pharmacodynamic model describing cenerimod concentration and its effect on LY count. Simulations addressed the objectives. Results Simulations of 365 days of treatment indicated a time to steady state of 49 days and changes in exposure of 15% beyond 35 days. For a dose of 2 mg, the predicted incidences of LY counts below 0.5 and 0.2 × 109 cells/L were 18.2 and 0.6% for healthy subjects and 25.9 and 1.0% for SLE patients, respectively. Incidence increased with higher dose and lower baseline LY counts. For body weights of 50 and 100 kg compared to 75 kg, exposure was predicted to change by +37% and −20%, respectively. Conclusion Long‐term cenerimod administration is not expected to result in exposure and LY count reduction substantially different from results of completed studies. Low LY counts are predicted to occur more frequently in SLE patients compared to healthy subjects. Dose individualization based on the model is not considered necessary. Model‐based simulations enable benefit–risk evaluations, supporting planning of late‐phase clinical studies and scientific exchange with health authorities.

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“…The aims of this study were to identify (i) publications that have applied nonlinear mixed‐effect (NLME) modeling since its first appearance in 1979, (ii) identify and evaluate the ones published in high impact journals, and (iii) to evaluate to which degree these were published in line with reporting standards for NLME analyses, 1–3 which are in line with the recently updated US Food and Drug Administration (FDA) guideline (https://www.fda.gov/media/128793/download).…”

Section: Motivationmentioning

confidence: 99%

What “Impact” Do NLME Publications Have Outside Our Community?

Hennig

Fischer

Kloft

2020

CPT Pharmacom & Syst Pharma

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The number of publications applying nonlinear mixed-effect (NLME) modeling has increased yearly since its first appearance in 1979. Here, we evaluated articles that have used NLME modeling, were published in journals that attract a broader audience, and we discussed the standard of presentation of these to stimulate target audience-specific improvements for increased impact in the future. MOTIVATIONPharmacometrics aims to describe the quantitative aspects of disease and pharmacology dynamics, to understand drug-patient-disease interaction by connecting various fields, such as physiology, pharmacology, clinical pharmacy, mathematical modeling, statistics, systems biology, pharmacokinetics/-dynamics in a coherent framework to generate knowledge, and improve drug development and patient outcomes (www.pharm etrx.de). The mathematical nature of the models used is not easily translatable to scientists outside the pharmacometric community, we, therefore, need to endeavor to improve communication within multidisciplinary teams and convey results to clinicians, editors, other modelers, reviewers, regulators, pharmacists, healthcare decision makers, and statisticians in a translational manner for having impact on scientific advancement and drug-based decisions.The aims of this study were to identify (i) publications that have applied nonlinear mixed-effect (NLME) modeling since its first appearance in 1979, (ii) identify and evaluate the ones published in high impact journals, and (iii) to evaluate to which degree these were published in line with reporting standards for NLME analyses, 1-3 which are in line with the recently updated US Food and Drug Administration (FDA) guideline (https://www.fda.gov/media/ 12879 3/download).

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Reporting a Population Pharmacokinetic–Pharmacodynamic Study: A Journal’s Perspective

Abstract: The key purpose of performing pharmaco-

Cited by 41 publications

References 24 publications

Population Pharmacokinetics of Tacrolimus in Transplant Recipients: What Did We Learn About Sources of Interindividual Variabilities?

Population Pharmacokinetics of Tacrolimus in Transplant Recipients: What Did We Learn About Sources of Interindividual Variabilities?

Modelling pharmacokinetics and pharmacodynamics of the selective S1P₁ receptor modulator cenerimod in healthy subjects and systemic lupus erythematosus patients

What “Impact” Do NLME Publications Have Outside Our Community?

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Reporting a Population Pharmacokinetic–Pharmacodynamic Study: A Journal’s Perspective

Abstract: The key purpose of performing pharmaco-

Cited by 41 publications

References 24 publications

Population Pharmacokinetics of Tacrolimus in Transplant Recipients: What Did We Learn About Sources of Interindividual Variabilities?

Population Pharmacokinetics of Tacrolimus in Transplant Recipients: What Did We Learn About Sources of Interindividual Variabilities?

Modelling pharmacokinetics and pharmacodynamics of the selective S1P1 receptor modulator cenerimod in healthy subjects and systemic lupus erythematosus patients

What “Impact” Do NLME Publications Have Outside Our Community?

Contact Info

Product

Resources

About

Modelling pharmacokinetics and pharmacodynamics of the selective S1P₁ receptor modulator cenerimod in healthy subjects and systemic lupus erythematosus patients