Novel minimal physiologically-based model for the prediction of passive tubular reabsorption and renal excretion clearance

PURPOSE: Develop a minimal mechanistic model based on in vitro–in vivo extrapolation (IVIVE) principles to predict extent of passive tubular reabsorption. Assess the ability of the model developed to predict extent of passive tubular reabsorption (F(reab)) and renal excretion clearance (CL(R)) from in vitro permeability data and tubular physiological parameters. METHODS: Model system parameters were informed by physiological data collated following extensive literature analysis. A database of clinical CL(R) was collated for 157 drugs. A subset of 45 drugs was selected for model validation; for those, Caco-2 permeability (P(app)) data were measured under pH 6.5–7.4 gradient conditions and used to predict F(reab) and subsequently CL(R). An empirical calibration approach was proposed to account for the effect of inter-assay/laboratory variation in P(app) on the IVIVE of F(reab). RESULTS: The 5-compartmental model accounted for regional differences in tubular surface area and flow rates and successfully predicted the extent of tubular reabsorption of 45 drugs for which filtration and reabsorption were contributing to renal excretion. Subsequently, predicted CL(R) was within 3-fold of the observed values for 87% of drugs in this dataset, with an overall gmfe of 1.96. Consideration of the empirical calibration method improved overall prediction of CL(R) (gmfe = 1.73 for 34 drugs in the internal validation dataset), in particular for basic drugs and drugs with low extent of tubular reabsorption. CONCLUSIONS: The novel 5-compartment model represents an important addition to the IVIVE toolbox for physiologically-based prediction of renal tubular reabsorption and CL(R). Physiological basis of the model proposed allows its application in future mechanistic kidney models in preclinical species and human.