Physiologically based pharmacokinetic model for the renal clearance of phenolsulfonphthalein and the interaction with probenecid and salicyluric acid in the dog

A Physiologically Based Pharmacokinetic (PBPK) Modeling Framework for Mixtures of Dioxin-like Compounds

Humans are exposed to persistent organic pollutants, such as dioxin-like compounds (DLCs), as mixtures. Understanding and predicting the toxicokinetics and thus internal burden of major constituents of a DLC mixture is important for assessing their contributions to health risks. PBPK models, including dioxin models, traditionally focus on one or a small number of compounds; developing new or extending existing models for mixtures often requires tedious, error-prone coding work. This lack of efficiency to scale up for multi-compound exposures is a major technical barrier toward large-scale mixture PBPK simulations. Congeners in the DLC family, including 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), share similar albeit quantitatively different toxicokinetic and toxicodynamic properties. Taking advantage of these similarities, here we reported the development of a human PBPK modeling framework for DLC mixtures that can flexibly accommodate an arbitrary number of congeners. Adapted from existing TCDD models, our mixture model contains the blood and three diffusion-limited compartments-liver, fat, and rest of the body. Depending on the number of congeners in a mixture, varying-length vectors of ordinary differential equations (ODEs) are automatically generated to track the tissue concentrations of the congeners. Shared ODEs are used to account for common variables, including the aryl hydrocarbon receptor (AHR) and CYP1A2, to which the congeners compete for binding. Binary and multi-congener mixture simulations showed that the AHR-mediated cross-induction of CYP1A2 accelerates the sequestration and metabolism of DLC congeners, resulting in consistently lower tissue burdens than in single exposure, except for the liver. Using dietary intake data to simulate lifetime exposures to DLC mixtures, the model demonstrated that the relative contributions of individual congeners to blood or tissue toxic equivalency (TEQ) values are markedly different than those to intake TEQ. In summary, we developed a mixture PBPK modeling framework for DLCs that may be utilized upon further improvement as a quantitative tool to estimate tissue dosimetry and health risks of DLC mixtures.

A critical review of adverse effects to the kidney: mechanisms, data sources, and in silico tools to assist prediction

INTRODUCTION

The kidney is a major target for toxicity elicited by pharmaceuticals and environmental pollutants. Standard testing which often does not investigate underlying mechanisms has proven not to be an adequate hazard assessment approach. As such, there is an opportunity for the application of computational approaches that utilize multiscale data based on the Adverse Outcome Pathway (AOP) paradigm, coupled with an understanding of the chemistry underpinning the molecular initiating event (MIE) to provide a deep understanding of how structural fragments of molecules relate to specific mechanisms of nephrotoxicity. Aims covered: The aim of this investigation was to review the current scientific landscape related to computational methods, including mechanistic data, AOPs, publicly available knowledge bases and current in silico models, for the assessment of pharmaceuticals and other chemicals with regard to their potential to elicit nephrotoxicity. A list of over 250 nephrotoxicants enriched with, where possible, mechanistic and AOP-derived understanding was compiled. Expert opinion: Whilst little mechanistic evidence has been translated into AOPs, this review identified a number of data sources of in vitro, in vivo, and human data that may assist in the development of in silico models which in turn may shed light on the interrelationships between nephrotoxicity mechanisms.

Key to Opening Kidney for In Vitro-In Vivo Extrapolation Entrance in Health and Disease: Part II: Mechanistic Models and In Vitro-In Vivo Extrapolation

It is envisaged that application of mechanistic models will improve prediction of changes in renal disposition due to drug-drug interactions, genetic polymorphism in enzymes and transporters and/or renal impairment. However, developing and validating mechanistic kidney models is challenging due to the number of processes that may occur (filtration, secretion, reabsorption and metabolism) in this complex organ. Prediction of human renal drug disposition from preclinical species may be hampered by species differences in the expression and activity of drug metabolising enzymes and transporters. A proposed solution is bottom-up prediction of pharmacokinetic parameters based on in vitro-in vivo extrapolation (IVIVE), mediated by recent advances in in vitro experimental techniques and application of relevant scaling factors. This review is a follow-up to the Part I of the report from the 2015 AAPS Annual Meeting and Exhibition (Orlando, FL; 25th-29th October 2015) which focuses on IVIVE and mechanistic prediction of renal drug disposition. It describes the various mechanistic kidney models that may be used to investigate renal drug disposition. Particular attention is given to efforts that have attempted to incorporate elements of IVIVE. In addition, the use of mechanistic models in prediction of renal drug-drug interactions and potential for application in determining suitable adjustment of dose in kidney disease are discussed. The need for suitable clinical pharmacokinetics data for the purposes of delineating mechanistic aspects of kidney models in various scenarios is highlighted.

Mechanistic models describing active renal reabsorption and secretion: a simulation-based study

The objective of the present study was to evaluate mechanistic pharmacokinetic models describing active renal secretion and reabsorption over a range of Michaelis-Menten parameter estimates and doses. Plasma concentration and urinary excretion profiles were simulated and renal clearance (CL(r)) was calculated for two pharmacokinetic models describing active renal reabsorption (R1/R2), two models describing active secretion (S1/S2), and a model containing both processes. A range of doses (1-1,000 mg/kg) was evaluated, and V (max) and K (m) parameter estimates were varied over a 100-fold range. Similar CL(r) values were predicted for reabsorption models (R1/R2) with variations in V (max) and K (m). Tubular secretion models (S1/S2) yielded similar relationships between Michaelis-Menten parameter perturbations and CL(r), but the predicted CL(r) values were threefold higher for model S1. For both reabsorption and secretion models, the greatest changes in CL(r) were observed with perturbations in V (max), suggesting the need for an accurate estimate of this parameter. When intrinsic clearance was substituted for Michaelis-Menten parameters, it failed to predict similar CL(r) values even within the linear range. For models S1 and S2, renal secretion was predominant at low doses, whereas renal clearance was driven by fraction unbound in plasma at high doses. Simulations demonstrated the importance of Michaelis-Menten parameter estimates (especially V (max)) for determining CL(r). K (m) estimates can easily be obtained directly from in vitro studies. However, additional scaling of in vitro V (max) estimates using in vitro/in vivo extrapolation methods are required to incorporate these parameters into pharmacokinetic models.

Analysis of contrast-enhanced MR images to assess renal function

The image analysis and kinetic modeling methods used in dynamic contrast-enhanced magnetic resonance imaging of the kidney are reviewed. Image analysis includes various techniques of coregistration and segmentation. Few methods have been completely implemented. Nevertheless, the use of coregistration may become a standard to decrease the effect of motion on abdominal images and improve the quality of the renal signals. Kinetic models are classified into three categories: enhancement-based, external and internal representations. Enhancement-based representations are limited to a basic analysis of the tracer concentration curves in the kidneys. Their relationship to the underlying physiology is complex and undefined. However, they can be used to evaluate the split renal function. External representations assess the kidney input and output. An external representation based on the up-slope of the renal enhancement to calculate the renal perfusion is commonly used because of its simplicity. In contrast, external representation based on deconvolution or identification methods remain underexploited. For glomerular filtration, an internal representation based on a two-compartmental model is mostly used. Internal representations based on multi-compartmental models describe the renal function in a more realistic way. Because of their numerical complexity, these models remain rarely used.

Influence of the infusion rate on disposition of netilmicin in the isolated rat perfused kidney

A study of the disposition of netilmicin in the isolated rat kidney was carried out in order to establish the influence of the infusion rate on the drug profile in this tissue. A dose of 800 microg administered as a bolus injection or at infusion times of 5, 7.5 and 10 min, respectively, was injected through the afferent cannula into the isolated kidney. Analysis of outflow curves was carried out using different kinetic approaches. Comparison of statistical moments and derived parameters pointed to changes in the distribution process with the infusion rate. In contrast, elimination remained constant, since the extraction coefficient and relative area under the curve values did not change with the infusion rate, although the MTT (mean transit time) and distribution volume decreased for the longest infusion times. The UDF (unit disposition function) profiles were not superimposed for the different infusion rates and combined with the results of the kinetic analysis revealed that the behaviour of netilmicin in the isolated kidney depends on infusion rate. The apparent partition coefficients in renal cortex and medulla showed higher values for the slower perfusion rates. Yet, a progressive decrease in the absolute amount of netilmicin was predicted in the tubular epithelium compartment whereas the residence time tended to increase. The latter phenomenon could account for the higher aminoglycoside nephrotoxicity reported when these drugs are administered over longer infusion times.

Mechanisms and clinical implications of renal drug excretion

The body defends itself against potentially harmful compounds like drugs, toxic compounds, and their metabolites by elimination, in which the kidney plays an important role. Renal clearance is used to determine renal elimination mechanisms of a drug, which is the result of glomerular filtration, active tubular secretion and reabsorption. The renal proximal tubule is the primary site of carrier-mediated transport from blood to urine. Renal secretory mechanisms exists for, anionic compounds and organic cations. Both systems comprises several transport proteins, and knowledge of the molecular identity of these transporters and their substrate specificity has increased considerably in the past decade. Due to overlapping specificities of the transport proteins, drug interactions at the level of tubular secretion is an event that may occur in clinical situation. This review describes the different processes that determine renal drug handling, the techniques that have been developed to attain more insight in the various aspects of drug excretion, the functional characteristics of the individual transport proteins, and finally the implications of drug interactions in a clinical perspective.

Capacity-limited renal glucuronidation of probenecid by humans. A pilot Vmax-finding study

Probenecid shows dose-dependent pharmacokinetics. When in one volunteer the dose is increased from 250 to 1,500 mg orally, the t1/2 increased from 3 to 6 h. The Cmax was 14 micrograms/ml with a dosage of 250 mg, 31 micrograms/ml with 500 mg, 70 micrograms/ml with 1,000 mg and 120 micrograms/ml with 1,500 mg. The tmax remained 1 h for all four dosages. The AUC/dose ratio increased with the dose, indicating nonlinear elimination. The total body clearance declined from 64.5 ml/min for 250 mg to 26.0 ml/min for 1,500 mg. The renal clearance of probenecid remained constant, 0.6-0.8 ml/min. Protein binding of probenecid is high (91%) and independent of the dose. The phase I metabolites show lower protein binding values (34-59%). The protein binding of probenecid glucuronide in vitro (spiked plasma) is 75%. Probenecid is metabolized by cytochrome P-450 to three phase I metabolites. Each of the metabolites accounts for less than 10% of the dose administered; the percentage recovered in the urine is independent of the dose. The main metabolite probenecid glucuronide is only present in urine and not in plasma. The renal excretion rate--time profile of probenecid glucuronide shows a plateau value of approximately 700 micrograms/min (46 mg/h) with acidic urine pH. The duration of this plateau value depends on the dose: 2 h at 500 mg, 10 h at 1,000 mg and 20 h at 1,500 mg. It is demonstrated that probenecid glucuronide must be formed in the kidney during its passage of the tubule. The plateau value in the renal excretion rate of probenecid value reflects its Vmax of formation.

Direct measurement of probenecid and its glucuronide conjugate by means of high pressure liquid chromatography in plasma and urine of humans

Probenecid with its phase-I metabolites, and phase-II glucuronide conjugate can be analysed by a gradient high pressure liquid chromatographic method. Probenecid glucuronide in plasma with pH 7.4 is not stable and declines to 10% of the original value within 6 h (t1/2 approximately 1 h). Probenecid glucuronide is stable in urine with pH 5.0, moderately unstable at pH 6.0 (t1/2 approximately 10 h), and unstable at pH 8.0 (t1/2 approximately 0.5 h). Probenecid glucuronide is stable in water and 0.01 mol/l phosphoric acid in the autosampler of the high pressure liquid chromatograph. The decrease in concentration in water is 5.5% during 9 h and 0% in diluted acid. Probenecid glucuronide and the phase-I metabolites were not detectable in plasma. The main compound in fresh urine is the phase-II conjugate probenecid glucuronide (62% of a 500 mg dose); the phase-I metabolites are present and only a trace of probenecid is present. The percentage of the dose of the phase-I metabolites varies between 5 and 10, while hardly any probenecid is excreted unchanged (0.33%).

Pharmacokinetics and excretion of phenol red in the channel catfish

1. Disposition of phenol red was examined in channel catfish (Ictalurus punctatus) after oral or intravascular (i.v.) dosing at 10 mg/kg body weight. 2. Phenol red was not detectable in plasma, urine, or bile after oral administration. 3. After i.v. dosing, plasma concentrations of phenol red were best described by a two-compartment pharmacokinetic model with distribution and elimination half-lives of 2.3 and 21 min, respectively. The apparent volume of distribution at steady state (Vss) was 225 ml/kg and total body clearance (Clb) was 658 ml/h per kg. Plasma protein binding was 19%. 4. Biliary excretion was the primary route of elimination of phenol red; in 24 h, 55% of the i.v. dose was excreted in bile compared with 24% in urine. No metabolites were detected in these fluids. 5. The use of anaesthesia during dosing had no effect on the quantitative excretion of phenol red by renal or biliary routes.

A physiological model for renal drug metabolism: enalapril esterolysis to enalaprilat in the isolated perfused rat kidney

A physiologically based kidney model was developed to describe the metabolism of enalapril and explain the observed discrepancies between generated and preformed enalaprilat (metabolite) elimination in the constant flow single-pass and recirculating isolated perfused rat kidney preparations (IPKs) as a result of the differing points of origin of the metabolite within the kidney, subsequent to the simultaneous delivery of 14C-enalapril and 3H-enalaprilat. The model incorporated clearances for diffusion/transport of drug and metabolite across the basolateral and luminal membranes of the renal cells, an intrinsic clearance for renal drug metabolism, in addition to physiological variables such as perfusate flow rate, glomerular filtration rate, and urine flow rate. Nonlinear curve fitting of single-pass and recirculating data was performed to estimate the rate-limiting step in the renal elimination of enalaprilat. Through fitting and simulation procedures, we were able to predict metabolic and excretory events for enalapril (renal extraction ratio approximately equal to 0.25-0.3; fractional excretion, FE, was less than unity) and the relatively constant pattern of urinary excretion of preformed enalaprilat (extraction ratio approximately equal to 0.07; FE approximately equal to 1). The extraction ratio of the intrarenally formed enalaprilat in single-pass IPK was about twofold that for the preformed metabolite, whereas the FEs of generated enalaprilat in recirculating IPKs were greater than 1, and tended to increase, then decrease with perfusion time. These observations were explained by the optimized parameters which indicated that efflux from cell to lumen was rate-controlling in the excretion of enalaprilat, and another small transport barrier also existed at the basolateral membrane; the lower extraction ratio of preformed enalaprilat was due to its poor transmembrane clearance at the basolateral membrane. The variable FEs for generated enalaprilat vs. the relatively constant FE for preformed metabolite in the recirculating IPK was explained by the changing contributions of both circulating and intrarenal metabolite to metabolite excretion.

Physiologically based pharmacokinetic model for the renal clearance of iodopyracet and the interaction with probenecid in the dog

Plasma kinetics and renal excretion of iodopyracet (3.0 g, administered i.v.) with and without concomitant administration of probenecid were studied in the beagle dog. Pharmacokinetic analysis revealed that tubular secretion is the predominant route of excretion, and that secretion is inhibited by probenecid. A physiologically based kidney model is proposed comprising all the functional characteristics of the kidney that determine the excretion of iodopyracet, i.e. renal plasma flow, urine flow, protein binding, glomerular filtration, tubular secretion, and tubular accumulation. The model enabled an accurate description and analysis of the measured plasma levels and renal excretion rates. Renal clearance of iodopyracet is characterized by supply-limited elimination at low plasma concentrations and capacity-limited elimination at high plasma levels. The interaction with probenecid could be adequately described with the model by competitive inhibition of the carrier-mediated uptake of iodopyracet into the tubular cells. Model calculations showed that in the control experiments tubular secretion was accompanied by a pronounced accumulation of iodopyracet within the cells, which was clearly diminished in the presence of probenecid.