Prediction of human pharmacokinetics — renal metabolic and excretion clearance

Abstract

The kidneys have the capability to both excrete and metabolise drugs. An understanding of mechanisms that determine these processes is required for the prediction of pharmacokinetics, exposures, doses and interactions of candidate drugs. This is particularly important for compounds predicted to have low or negligible non-renal clearance (CL). Clinically significant interactions in drug transport occur mostly in the kidneys. The main objective was to evaluate methods for prediction of excretion and metabolic renal CL (CL R ) in humans. CL R is difficult to predict because of the involvement of bi-directional passive and active tubular transport, differences in uptake capacity, pH and residence time on luminal and blood sides of tubular cells, and limited knowledge about regional tubular residence time, permeability (P e ) and metabolic capacity. Allometry provides poor predictions of excretion CL R because of species differences in unbound fraction, urine pH and active transport. The correlation between fraction excreted unchanged in urine (f e ) in humans and animals is also poor, except for compounds with high passive P e (extensive/complete tubular reabsorption; zero/negligible f e ) and/or high non-renal CL. Physiologically based in-vitro/in-vivo methods could potentially be useful for predicting CL R . Filtration could easily be predicted. Prediction of tubular secretion CL requires an in-vitro transport model and establishment of an in-vitro/in-vivo relationship, and does not appear to have been attempted. The relationship between passive P e and tubular fraction reabsorbed (f reabs ) for compounds with and without apparent secretion has recently been established and useful equations and limits for prediction were developed. The suggestion that reabsorption has a lipophilicity cut-off does not seem to hold. Instead, compounds with passive P e that is less than or equal to that of atenolol are expected to have negligible passive f reabs . Compounds with passive P e that is equal to or higher than that of carbamazepine are expected to have complete f reabs . For compounds with intermediate P e the relationship is irregular and f reabs is difficult to predict. Tubular cells are comparably impermeable (for passive diffusion), and show regional differences in enzymatic and transporter activities. This limits the usefulness of microsome data and makes microsome-based predictions of metabolic CL R questionable. Renal concentrations and activities of CYP450s are comparably low, suggesting that CYP450 substrates have negligible metabolic CL R . The metabolic CL R of high-P e UDP-glucuronyltransferase substrates could contribute to the total CL.

Quantitative Structure-Pharmacokinetic Relationships for the Prediction of Renal Clearance in Humans

“…Benet et al (2011) reported that percent of unchanged drug excreted into urine was statistically lower for compounds belonging to classes 1 and 2 than for compounds belonging to classes 3 and 4. Although, a low CL R is not necessarily due to net reabsorption, lipophilicity of compounds is a significant determinant of extensive metabolism and distribution of compounds (Fagerholm, 2007). As well, compounds that undergo extensive metabolism are less likely to undergo biliary and renal excretion (Fagerholm, 2007;Benet et al, 2011).…”

“…Although, a low CL R is not necessarily due to net reabsorption, lipophilicity of compounds is a significant determinant of extensive metabolism and distribution of compounds (Fagerholm, 2007). As well, compounds that undergo extensive metabolism are less likely to undergo biliary and renal excretion (Fagerholm, 2007;Benet et al, 2011). Moreover, compounds undergoing net reabsorption were predominantly neutral.…”

“…Renal clearance (CL R ) is a major route of elimination for drugs with low to negligible metabolism and biliary excretion and for drug metabolites (Masereeuw and Russel, 2001;Fagerholm, 2007). Renal clearance (CL R ) is a net result of glomerular filtration, active tubular secretion and reabsorption, and passive reabsorption (Fagerholm, 2007).…”

“…Renal clearance (CL R ) is a net result of glomerular filtration, active tubular secretion and reabsorption, and passive reabsorption (Fagerholm, 2007). Active secretion and active reabsorption are transporter-mediated processes (Muller and Fromm, 2011).…”

Physiologically based pharmacokinetic (PBPK) modelling tools: how to fit with our needs?

“…These model input parameters are derived either from in silico predictions based on the chemical structure (logP, pK a , polar surface area), from in vitro experiments designed to mimic certain bodily environments, or from in vivo measurements. In 2007, Fagerholm evaluated the various methods available for the scaling of in vitro measurements for the prediction of hepatic metabolic clearance [37], renal clearance [38], intestinal metabolism [39] and absorption [40], and volume of Figure 2. Structure of the gut model [28].…”