Comparison of common methodologies for accounting for IIV for oral bioavailability (F) in the absence of intravenous data
Authors: MacDonald Alexander , Bartlette Kai , Brochot Anne , Freidy Soha 
Published: February 2025

Objectives: F is the product of drug fraction absorbed (Fa), fraction escaping gut metabolism (Fg), and fraction escaping liver extraction (Fh). Each component is influenced by factors such as the physicochemical properties of the drug or physiological issues (1). In turn, each factor contributes to potential inter-individual variability (IIV) in F. When modeling oral pharmacokinetic (PK) data using nonlinear mixed effects, two approaches are commonly used in the absence of intravenous (IV) data: Attribute IIV linked to F to apparent clearance (CL/F) and volume of distribution (V/F) parameters, estimating the correlation between the twoFix F to a relative value of 1 and estimate IIV on this parameter.While modeling oral/extravascular PK data is common, there appears to be no comparison of methods or consensus on relative merits in the literature. This work evaluates the suitability of these approaches using representative PK data.Methods: Physiologically-based pharmacokinetic models of representative drugs, from the PK-Sim® library(2), were used to simulate clinical study data with a phase 1 single ascending dose design and intensive sampling. 6 drugs of different BCS class (verapamil and fluconazole, BCS1; montelukast and felodipine, BCS2; dapagliflozin and cimetidine, BCS3) were simulated, and the PK-Sim® bioavailability was output for each simulated subject. Each simulated dataset was modeled using NONMEM V7.4. Bodyweight allometric scaling was introduced apriori on all clearance and volume terms. Model evaluation was based on goodness-of-fit, visual predictive check (pcVPC), and parameter precision. The best model without IIV on F was determined for each drug, which was then added. Correlation between post-hoc F ETA and the PK-Sim® bioavailability was evaluated.Results : Models included IIV on CL/F and V/F except fluconazole (IIV on absorption parameter) and montelukast (IIV on CL and peripheral distribution parameters). Partial/full correlation blocks were introduced where required. Predictive performance was good, except fluconazole where dose dependent absorption was suspected. All models, except verapamil, showed decreased objective function, AIC and residual unexplained variability (RUV) when IIV on F was added. pcVPCs were not enhanced, but correlation between post-hoc ETA for F and PK-Sim® bioavailability was observed in general.Conclusion: NONMEM quantified IIV on F in addition to apparent CL and V, and its presence improved the objective function and RUV in most cases, and was mostly correlated to the “true” bioavailability. The choice to use or not an IIV on F, since not necessarily improving the predictive performances, could be made based on the objective of modeling, e.g. F specific covariates are suspected or if RUV is important for simulation. Citations: Rowland and Tozer’s Clinical Pharmacokinetics and Pharmacodynamics. Concept and applications. 5th ed. Wolters Kluwer, 2020.https://www.open-systems-pharmacology.org/