Drug Disposition in Obesity: Toward Evidence-Based Dosing

Knibbe, Catherijne A. J.; Brill, Margreke J. E.; Rongen, Anne van; Diepstraten, Jeroen; Graaf, Piet H. van der; Danhof, Meindert

doi:10.1146/annurev-pharmtox-010814-124354

Cited by 107 publications

(92 citation statements)

References 111 publications

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“…Many of these factors are known to induce substantially more variability than gender if they are distributed heterogeneously in the target population 21, 22. For instance, weight is often correlated closely with drug distribution and can vary by as much as double in Western populations, thereby giving rise to substantial differences in drug response when a similar oral dose is taken, especially in obese patients 23. Furthermore, children and the elderly are often under‐represented in registration trials, although guidelines advise that these groups are investigated 24, 25, 26.…”

Section: Discussionmentioning

confidence: 99%

Gender differences in clinical registration trials: is there a real problem?

Labots

Jones

Visser

et al. 2018

Brit J Clinical Pharma

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AimsSeveral studies have reported the under‐representation of women in clinical trials, thereby challenging the external validity of the benefit/risk assessments of launched drugs. Our aim was to determine the extent to which women have been included in clinical trials used for drug registration and to analyse the fraction of women participating in phases I, II and III.MethodsWe conducted cross‐sectional, structured research into publicly available registration dossiers of Food and Drug Administration (FDA)‐approved drugs that are prescribed frequently. Furthermore, we analysed compounds with high hepatic clearance and a known gender‐related difference in drug response. In a sensitivity analysis, we compared figures with US disease prevalence data.ResultsFor 38 of the initial 137 drugs (28%), sufficient data were reported and publicly available. For these drugs, 185 479 trial participants were included, of whom 47% were female and 44% were male; gender was not reported for 9% of participants. However, the number of female participants varied with the phase of the trial, with 22% females in phase I trials vs. 48% and 49%, respectively, in phase II and III trials. When compared with US disease prevalence data, 10 drugs (26%) had a greater than 20% difference between the proportion of females affected with the disease compared with representation in clinical trials.ConclusionsFrom these publicly available data, there was no evidence of any systematic under‐representation of women in clinical trials.

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Section: Discussionmentioning

confidence: 99%

Gender differences in clinical registration trials: is there a real problem?

Labots

Jones

Visser

et al. 2018

Brit J Clinical Pharma

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“…Furthermore, PK in obese patients might be altered due to a shift toward more fat tissue in relation to body weight, changes in plasma protein constituents, a possible change in hepatic metabolism (e.g., increased glucuronidation) and an increase in clearance [17,74,75]. PK data of echinocandins in obese patients are scarce.…”

Section: Pk In Varying Body Size Compositionmentioning

confidence: 99%

Impact of special patient populations on the pharmacokinetics of echinocandins

Muilwijk¹,

Lempers²,

Burger³

et al. 2015

Expert Review of Anti-infective Therapy

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Echinocandins belong to the class of antifungal agents. Currently, three echinocandin drugs are licensed for intravenous treatment of invasive fungal infections: anidulafungin, caspofungin and micafungin. While their antifungal activity overlaps, there are substantial differences in pharmacokinetics (PK). Numerous factors may account for variability in PK of echinocandins including age (pediatrics vs adults), body surface area and body composition (normal weight vs obesity), disease status (e.g., critically ill and burn patients) and organ dysfunction (kidney and liver impairment). Subsequent effects of altered exposure might impact efficacy and safety. Knowledge of PK behavior is crucial in optimal clinical utilization of echinocandin in a specific patient or patient population. This review provides up-to-date information on PK data of anidulafungin, caspofungin and micafungin in special patient populations. Patient populations addressed are neonates, children and adolescents, obese patients, patients with hepatic or renal impairment, critically ill patients (including burn patients) and patients with hematological diseases.

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“…These covariate models can then be used to support personalized pharmacotherapy [3]. One of the most commonly identified covariates in population pharmacokinetic models is the body weight of the patient [4][5][6][7][8]. The relationship between drug CL and weight is often described using a power function:…”

Section: Introductionmentioning

confidence: 99%

The Influence of Normalization Weight in Population Pharmacokinetic Covariate Models

et al. 2018

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In covariate (sub)models of population pharmacokinetic models, most covariates are normalized to the median value; however, for body weight, normalization to 70 kg or 1 kg is often applied. In this article, we illustrate the impact of normalization weight on the precision of population clearance (CL pop ) parameter estimates. The influence of normalization weight (70, 1 kg or median weight) on the precision of the CL pop estimate, expressed as relative standard error (RSE), was illustrated using data from a pharmacokinetic study in neonates with a median weight of 2.7 kg. In addition, a simulation study was performed to show the impact of normalization to 70 kg in pharmacokinetic studies with paediatric or obese patients. The RSE of the CL pop parameter estimate in the neonatal dataset was lowest with normalization to median weight (8.1%), compared with normalization to 1 kg (10.5%) or 70 kg (48.8%). Typical clearance (CL) predictions were independent of the normalization weight used. Simulations showed that the increase in RSE of the CL pop estimate with 70 kg normalization was highest in studies with a narrow weight range and a geometric mean weight away from 70 kg. When, instead of normalizing with median weight, a weight outside the observed range is used, the RSE of the CL pop estimate will be inflated, and should therefore not be used for model selection. Instead, established mathematical principles can be used to calculate the RSE of the typical CL (CL TV ) at a relevant weight to evaluate the precision of CL predictions. Key PointsNormalization to a weight outside the observed weight range (e.g. 70 kg normalization in a paediatric study) can increase the uncertainty of parameter estimates in pharmacokinetic covariate models.The predictive performance of pharmacokinetic models and their covariate submodels is unaffected by weight normalization.When normalizing outside the observed covariate range, the RSEs of the corresponding population estimates should generally not be used for model evaluation. The RSE of the typical parameter at a relevant covariate value can be used instead.Sebastiaan Goulooze and Swantje Völler contributed equally to this work.

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Drug Disposition in Obesity: Toward Evidence-Based Dosing

Cited by 107 publications

References 111 publications

Gender differences in clinical registration trials: is there a real problem?

Gender differences in clinical registration trials: is there a real problem?

Impact of special patient populations on the pharmacokinetics of echinocandins

The Influence of Normalization Weight in Population Pharmacokinetic Covariate Models

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