Physiologically Based Pharmacokinetic Prediction of Telmisartan in Human

Li, Rui; Ghosh, Avijit; Maurer, Tristan S.; Kimoto, Emi; Barton, Hugh A.

doi:10.1124/dmd.114.058461

Cited by 42 publications

(55 citation statements)

References 38 publications

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“…The mispredictions for these relatively lipophilic compounds could be due to underestimation of permeability caused by potential low solubility and/or non-specific binding artifacts within the permeability assay. Similar to Class 1B compounds, the prediction of active hepatic uptake clearance can be achieved via in vitro hepatocyte uptake studies [109,160], whereas metabolic stability studies would underestimate the clearance of these molecules. Renal clearance can be predicted by single species scaling or physiologically based pharmacokinetic models [169].…”

Section: Class 3bmentioning

confidence: 99%

Predicting Clearance Mechanism in Drug Discovery: Extended Clearance Classification System (ECCS)

et al. 2015

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Early prediction of clearance mechanisms allows for the rapid progression of drug discovery and development programs, and facilitates risk assessment of the pharmacokinetic variability associated with drug interactions and pharmacogenomics. Here we propose a scientific framework--Extended Clearance Classification System (ECCS)--which can be used to predict the predominant clearance mechanism (rate-determining process) based on physicochemical properties and passive membrane permeability. Compounds are classified as: Class 1A--metabolism as primary systemic clearance mechanism (high permeability acids/zwitterions with molecular weight (MW) ≤400 Da), Class 1B--transporter-mediated hepatic uptake as primary systemic clearance mechanism (high permeability acids/zwitterions with MW >400 Da), Class 2--metabolism as primary clearance mechanism (high permeability bases/neutrals), Class 3A--renal clearance (low permeability acids/zwitterions with MW ≤400 Da), Class 3B--transporter mediated hepatic uptake or renal clearance (low permeability acids/zwitterions with MW >400 Da), and Class 4--renal clearance (low permeability bases/neutrals). The performance of the ECCS framework was validated using 307 compounds with single clearance mechanism contributing to ≥70% of systemic clearance. The apparent permeability across clonal cell line of Madin - Darby canine kidney cells, selected for low endogenous efflux transporter expression, with a cut-off of 5 × 10(-6) cm/s was used for permeability classification, and the ionization (at pH7) was assigned based on calculated pKa. The proposed scheme correctly predicted the rate-determining clearance mechanism to be either metabolism, hepatic uptake or renal for ~92% of total compounds. We discuss the general characteristics of each ECCS class, as well as compare and contrast the framework with the biopharmaceutics classification system (BCS) and the biopharmaceutics drug disposition classification system (BDDCS). Collectively, the ECCS framework is valuable in early prediction of clearance mechanism and can aid in choosing the right preclinical tool kit and strategy for optimizing drug exposure and evaluating clinical risk of pharmacokinetic variability caused by drug interactions and pharmacogenomics.

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Section: Class 3bmentioning

confidence: 99%

Predicting Clearance Mechanism in Drug Discovery: Extended Clearance Classification System (ECCS)

et al. 2015

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“…These models either assumed continuous enterohepatic recirculation (25,(40)(41)(42), one or multiple secretions of bile using an on/off switch (i.e., "lag-time(s)") (24,26,(43)(44)(45)(46)(47)(48)(49)(50)(51)(52)(53)(54)(55)(56)(57)(58) or implemented a sine function to describe periodic bile releases (27,28,59,60). We are not aware of published models that simultaneously quantified EHC across more than one species or described the full time-course of PK profiles after multiple dosing.…”

Section: Discussionmentioning

confidence: 99%

Population Pharmacokinetic Modeling of the Enterohepatic Recirculation of Fimasartan in Rats, Dogs, and Humans

Kim

Shin

Landersdorfer

et al. 2015

AAPS J

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Abstract. Enterohepatic recirculation (EHC) can greatly enhance plasma drug exposures and therapeutic effects. This study aimed to develop a population pharmacokinetic model that can simultaneously characterize the extent and time-course of EHC in three species using fimasartan, a novel angiotensin II receptor blocker, as a model drug. All fimasartan plasma concentration profiles in 32 rats (intravenous doses, 0.3-3 mg/kg; oral doses, 1-10 mg/kg), 34 dogs (intravenous doses, 0.3-1 mg/kg; oral doses, 1-10 mg/kg), and 42 healthy volunteers (single or multiple oral doses, 20-480 mg) were determined via liquid chromatography-tandem mass spectrometry (LC-MS/MS) and simultaneously modeled in S-ADAPT. The proposed model quantitatively characterized EHC in three species after oral and intravenous dosing. The median (range) fraction of drug undergoing recirculation was 76.3% (64.9-88.7%) in rats, 33.3% (24.0-45.9%) in dogs, and 65.6% (56.5-72.0%) in humans. In the presence compared with the absence of EHC, the area under the curve in plasma was predicted to be 4.22-fold (2.85-8.85) as high in rats, 1.50-fold (1.32-1.85) in dogs, and 2.91-fold (2.30-3.57) in humans. The modeled oral bioavailability in rats (median (range), 38.7% (20.0-59.8%)) and dogs (median, 7.13% to 15.4%, depending on the formulation) matched the non-compartmental estimates well. In humans, the predicted oral bioavailability was 25.1% (15.1-43.9%) under fasting and 18.2% (12.2-31.0%) under fed conditions. The allometrically scaled area under the curve predicted from rats was 420 ng⋅h/mL for 60 mg fimasartan compared with 424±63 ng⋅h/mL observed in humans. The developed population pharmacokinetic model can be utilized to characterize the impact of EHC on plasma drug exposure in animals and humans.

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“…60 These SFs have been used in the in vitro-in vivo extrapolation of other OATP substrates such as telmisartan. 60,61 A similar approach has been applied to estimate SFs for CL int, uptake of pravastatin, repaglinide, and glyburide. 74–76 Li et al developed a single set of empirical SFs by simultaneously modeling data for the same seven OATP substrates; they reported SFs of 55 for CL int, u, uptake , 0.019 for CL int, u, bile , and 0.092 for CL int, u, pass .…”

Section: Use Of Sandwich–cultured Hepatocytes In Studying Drug Disposmentioning

confidence: 99%

Sandwich-Cultured Hepatocytes as a Tool to Study Drug Disposition and Drug-Induced Liver Injury

Yang

Guo

Woodhead

et al. 2016

Journal of Pharmaceutical Sciences

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Sandwich-cultured hepatocytes (SCH) are metabolically competent and have proper localization of basolateral and canalicular transporters with functional bile networks. Therefore, this cellular model is a unique tool that can be used to estimate biliary excretion of compounds. SCH have been used widely to assess hepatobiliary disposition of endogenous and exogenous compounds and metabolites. Mechanistic modeling based on SCH data enables estimation of metabolic and transporter-mediated clearances, which can be employed to construct physiologically-based pharmacokinetic models for prediction of drug disposition and drug-drug interactions in humans. In addition to pharmacokinetic studies, SCH also have been employed to study cytotoxicity and perturbation of biological processes by drugs and hepatically-generated metabolites. Human SCH can provide mechanistic insights underlying clinical drug-induced liver injury (DILI). In addition, data generated in SCH can be integrated into systems pharmacology models to predict potential DILI in humans. In this review, applications of SCH in studying hepatobiliary drug disposition and bile acid-mediated DILI are discussed. An example is presented to show how data generated in the SCH model was used to establish a quantitative relationship between intracellular bile acids and cytotoxicity, and how this information was incorporated into a systems pharmacology model for DILI prediction.

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Physiologically Based Pharmacokinetic Prediction of Telmisartan in Human

Cited by 42 publications

References 38 publications

Predicting Clearance Mechanism in Drug Discovery: Extended Clearance Classification System (ECCS)

Predicting Clearance Mechanism in Drug Discovery: Extended Clearance Classification System (ECCS)

Population Pharmacokinetic Modeling of the Enterohepatic Recirculation of Fimasartan in Rats, Dogs, and Humans

Sandwich-Cultured Hepatocytes as a Tool to Study Drug Disposition and Drug-Induced Liver Injury

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