Mechanistic Basis of Using Body Size and Maturation to Predict Clearance in Humans

Abstract

Growth and development are two major aspects of children not readily apparent in adults. Clearance in the paediatric population should be investigated using models that describe size, maturation and organ function influences. Size is the primary covariate and although lean body weight is argued as a better measure than total body weight, the use of different fractions of fat mass to explain how pharmacokinetic parameters vary with body composition has been proposed. Allometric scaling using an empiric power exponent of 3/4 is superior to scaling using body surface area. The sigmoid hyperbolic model has proven useful to describe maturation. An extra parameter that describes asymmetry can be incorporated into this model. These descriptors are used to illustrate creatinine, morphine and paracetamol clearance in children. Simultaneous investigation of pooled GFR, paracetamol and morphine data enabled testing for shared common features of maturation processes. Results suggest that GFR matures before paracetamol or morphine clearance, consistent with phase II conjugation processes that convert xenobiotics to water soluble forms that can subsequently be eliminated from the body through the renal system. The use of such mechanistic approaches improves understanding of paediatric pharmacokinetics; improving dosing predictions and allowing projection in exploratory drug development.

Characterization of Contributing Factors to Variability in Morphine Clearance Through PBPK Modeling Implemented With OCT1 Transporter

“…However, clinicians continue to struggle with finding the right dose due to our incomplete understanding of the factors predicting the large variability in morphine pharmacokinetics (PKs) among patients. The variability in morphine disposition is considered to result from a combination of pharmacogenetic and physiological determinants, whereas in pediatric patients the age‐dependent developmental changes also need to be considered 1, 2. Application of physiologically‐based pharmacokinetic (PBPK) modeling is recognized as an informative approach to explore the combined effects of the system parameter3 (e.g., physiology and genetics) and drug parameters (e.g., physicochemical and in vitro PK properties).…”

Drug effects on the CVS in conscious rats: separating cardiac output into heart rate and stroke volume using PKPD modelling

“…The PK does not differ between rat strains and can be scaled between rabbit and rat on the basis of an allometric function (West et al, 1999;Anderson and Holford, 2009). …”

Pharmacotherapy in pediatric epilepsy: from trial and error to rational drug and dose selection – a long way to go

“…body weight) and elimination rate has been demonstrated to be nonlinear. This implies that dosing in milligram per kilogram does not accurately correct for the underlying differences [41]. In fact, unless explicit differences have been identified in the underlying PKPD relationship, dose adjustment in children should aim at achieving comparable exposure or similar PK profile across the target population, irrespective of body weight or age.…”