Estimation of Body Fat Percentage for Clinical Pharmacokinetic Studies in Children

Abstract

Obesity is a prevalent childhood condition and the degree of adiposity appears likely to be an important covariate in the pharmacokinetics (PKs) of many drugs. We undertook these studies to facilitate the evaluation and, where appropriate, quantification of the covariate effect of body fat percentage (BF%) on PK parameters in children. We examined two large databases to determine the values and variabilities of BF% in children with healthy body weights and in those with obesity, comparing the accuracy and precision of BF% estimation by both clinical methods and demographically derived techniques. Additionally, we conducted simulation studies to evaluate the utility of the several methods for application in clinical trials. BF% was correlated with body mass index (BMI), but was highly variable among both children with healthy body weights and those with obesity. Bio-impedance and several demographically derived techniques produced mean estimates of BF% that differed from dual x-ray absorptiometry by < 1% (accuracy) and a SD of 5% or less (precision). Simulation studies confirmed that when the differences in precision among the several methods were small compared with unexplained between-subject variability of a PK parameter, the techniques were of similar value in assessing the contribution of BF%, if any, as a covariate for that PK parameter. The combination of sex and obesity stage explained 68% of the variance of BF% with BMI. The estimation of BF% from sex and obesity stage can routinely be applied to PK clinical trials to evaluate the contribution of BF% as a potential covariate. Approximately one-third of children in the United States are overweight or obese, and this proportion has continued to increase over the last decade. 1,2 Fat and nonfat tissues have many distinct physical, chemical, and metabolic characteristics, so differences in drug disposition can occur relative to a child's obesity status. Nevertheless, differences in drug pharmacokinetics (PKs) between children with and without obesity have been described for only a few drugs. 3-10 For most drugs, the effects of obesity on PKs in children are poorly characterized, 11-14 leaving clinicians with inadequate

Development and Evaluation of a Virtual Population of Children with Obesity for Physiologically Based Pharmacokinetic Modeling

“…To further evaluate the distribution of excess body weight between adipose and lean organs in virtual children with obesity after incorporating organ volume scaling factors, simulated adipose volume was compared to calculated fat mass for virtual children using previously developed fat mass equations [ 33 , 34 ]. Simulated adipose volume was similar to calculated fat mass, with some overestimation at higher weights that was also observed in the baseline population of virtual children without obesity (Fig.…”

“…Simulated fat mass was determined from the volume of the adipose organ generated for each virtual child in PK-Sim ® . Calculated fat mass was determined using each virtual child’s demographic information and the fat mass equations derived from Al-Sallami et al ( a and b ) and Green et al ( c and d ) [ 33 , 34 ]. Each point represents a single virtual child.…”

“…Although there is some evidence of obesity-related alterations in in vitro activity of key metabolic and transport [33,34]. Each point represents a single virtual child.…”

Characterizing Pharmacokinetics in Children With Obesity—Physiological, Drug, Patient, and Methodological Considerations

“…Many additional body size measures have been proposed to measure obesity, which are summarized in Table 1 . While these body size measures are often more accurate in describing fat and lean body size in children, they can be more challenging to calculate in a clinical setting ( Freedman and Sherry, 2009 ; Anderson and Holford, 2017 ; Sinha et al, 2018 ; Green et al, 2020 ).…”

“… c See ( Janmahasatian et al, 2005 ; Al-Sallami et al, 2015 ), n = 1,011 subjects. d See ( Green et al, 2020 ), n = 4,274 subjects. …”