The Pharmacokinetics and Hepatic Disposition of Repaglinide in Pigs

Article pubs.acs.org/molecularpharmaceutics

The Pharmacokinetics and Hepatic Disposition of Repaglinide in Pigs: Mechanistic Modeling of Metabolism and Transport Erik Sjögren,† Ulf Bredberg,‡ and Hans Lennernas̈ *,† †

Department of Pharmacy, Uppsala University, Box 580, S-751 23 Uppsala, Sweden DxDMPK, AstraZeneca R&D, Mölndal, Sweden

‡

S Supporting Information *

ABSTRACT: The predictive power of using in vitro systems in combination with physiologically based pharmacokinetic (PBPK) modeling to elucidate the relative importance of metabolism and carrier-mediated transport for the pharmacokinetics was evaluated using repaglinide as a model compound and pig as the test system. Repaglinide was chosen as model drug as previous studies in humans have shown that repaglinide is subject to both carrier-mediated influx to the liver cells and extensive hepatic metabolism. A multiple sampling site model in pig was chosen since it provides detailed in vivo information about the liver disposition. The underlying assumption was that both metabolism and carrier-mediated transport are also important for the hepatic disposition of repaglinide in pigs. Microsomes and primary hepatocytes were used for in vitro evaluation of enzyme kinetics and cellular disposition, respectively. In vitro data were generated both with and without metabolism inhibitors (ketoconazole, bezafibrate and trimethoprim) and transport inhibitors (diclofenac and quinine) providing input into a semi-PBPK model. In vivo data were also generated with and without the same enzyme and transporter inhibitors, alone and in combination. The pigs were given repaglinide as intravenous infusions with and without inhibitors in a sequential manner, i.e., a control phase and a test phase. Parameters describing the passive and carrier-mediated flux as well as metabolism were estimated in the control phase. The result from test phase was used to gain further knowledge of the findings from the control phase. The in vivo pig model enabled simultaneous sampling from plasma (pre- and postliver and peripheral) as well as from bile and urine. A semi-PBPK model consisting of 11 compartments (6 tissues + 5 sampling sites) was constructed for the mechanistic elucidation of the liver disposition, in vitro based in vivo predictions, sensitivity analyses and estimations of individual pharmacokinetic parameters. Both in vitro and in vivo results showed that carrier-mediated influx was important for the liver disposition. The in vivo findings were supported by the result from the test phase where hepatic clearance (4.3 mL min−1 kg−1) was decreased by 29% (metabolism inhibition), 43% (transport inhibition) and 57% (metabolism + transport inhibition). These effects were in good agreement with predicted levels. This study suggests that both metabolism and carrier-mediated uptake are of significant importance for the liver disposition of repaglinide in pigs. KEYWORDS: hepatic disposition, transport, metabolism, physiologically based pharmacokinetic (PBPK) modeling, drug−drug interaction, hepatocytes

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INTRODUCTION Predictions of hepatic clearance based on metabolic intrinsic clearance (CLint) determined in vitro has been a standard practice in drug discovery for many years.1,2 In recent years, attention to processes involved in the hepatic distribution mediated by membrane transporters has increased.3−6 Isolated hepatocytes are commonly used for in vitro hepatic disposition investigations as the integrity of many cellular components is maintained during isolation.7,8 Several methods have been proposed to distinguish the processes of distribution and metabolism, but these methods often include several combined assays and/or advanced assay procedures, such as oil layer separations or washing of plated cells.9−11 The typical means to acquire a value for CLint is to measure the depletion rate of parent © 2012 American Chemical Society

compound from a hepatocyte suspension and correct for the fraction unbound in the incubation (fuinc).12,13 An optional approach, the simple disposition model, using the same experimental setup has been suggested for estimation of the relative importance of distribution and metabolism on the cellular disposition of metabolized drugs.14 This information is acquired by combining enzyme kinetics, determined in cell fractions, and selective inhibition of metabolism and/or cell distribution (i.e., membrane transport). The advantage of this method, in a drug Received: Revised: Accepted: Published: 823

April 29, 2011 January 30, 2012 February 19, 2012 February 21, 2012 dx.doi.org/10.1021/mp200218p | Mol. Pharmaceutics 2012, 9, 823−841

Molecular Pharmaceutics

Article

determined to have over 75% amino acid identity to the human equivalents CYP2C8 and CYP3A4 even though lower relative expression in liver was reported (pig:human: CYP2C, 0.16:0.26; CYP3A, 0.14:0.36).31,32,34 Although low protein homology and abundance in pig liver were reported for OATP1B1, higher similarities have been reported for other transporter proteins, e.g., OATP1A2 and MRP2.29,33 Three metabolites of repaglinide, an aromatic amine (M1), a dicarboxylic acid (M2) and an acyl glucuronide (M7), were also quantified to add further information to the investigation. This combination of information made it possible to perform a comprehensive pharmacokinetic data analysis. Modeling has been applied to a wide range of pharmacokinetic analyses, from cellular models to whole body physiologically based pharmacokinetic (PBPK) models. 35−40 These approaches have been valuable in discriminating the mechanisms that contribute to the overall pharmacokinetics and for the evaluation of the importance of each of these processes. However, adjustments, e.g., scaling factors to increase metabolic capacity, to these models have in many cases been necessary to increase the precision of the predictions.9,35,37,40 The aim of this study was to evaluate whether the in vitro based disposition model is able to predict the importance of CM transport and metabolism for the in vivo disposition using repaglinide as a model drug and the pig as a model animal. A secondary aim was to develop a PBPK model, suitable for the multiple sampling site pig model, functional for both in vitro based predictions and in vivo data analysis. The development process of the PBPK model in this study pursued the following sequential steps (Figure 1): (1) preliminary in vitro and

discovery context, is the additional valuable information gained from a conventional experimental setup already well implemented and characterized. However, the predictability of the information obtained with this method has not yet been reported or evaluated. The hypoglycemic agent repaglinide (Mw = 453 g mol−1, pKa1 = 4.16, pKa2 = 6.01, log D7.4 = 2.5) is almost completely eliminated by the liver through metabolism, in humans mediated by cytochrome P450 (CYP) isoforms 3A4 and 2C8, and direct glucuronidation.15−20 Previous studies in humans have also shown that repaglinide is distributed to hepatocytes through carrier-mediated (CM) uptake by organic anion-transporting polypeptide (OATP) 1B1 (SLCO1B1).21,22 Several drug−drug interactions of clinical relevance have been reported involving both uptake and metabolism inhibition.23−25 On this basis, repaglinide was chosen as a model drug for the evaluation of the simple disposition model. A multiple sampling site model in pigs previously developed in our group was employed for the in vivo investigation, and in vitro studies were conducted with pig liver microsomes and primary hepatocytes.26−28 The in vivo model was chosen since it provides detailed in vivo information about the liver disposition. The choice of repaglinide as model drug was made under the assumption that both metabolism and CM transport are also important for the hepatic disposition of repaglinide in pigs. This assumption of comparable, albeit not exact, processes in both pigs and humans was based on previous studies showing that the pig is similar to human in several aspects, such as in physiological characteristics and protein expression.29−33 The pig CYP2C42/2C49 and CYP3A29/3A39/3A46 has been

Figure 1. Outline of the workflow, visualizing the steps taken throughout the investigation of the hepatic disposition. Theoretical maximum reaction rate (Vmax) and the Michaelis constant (Km), distribution constant (D), blood flow (Q), tissue volume (VT), dissociation constant (KP), fraction unbound in plasma (fuP), blood/plasma ratio (B/P), passive diffusion (Pdif), physiological based pharmacokinetic (PBPK), multiple depletion curves method (MDCM). 824

dx.doi.org/10.1021/mp200218p | Mol. Pharmaceutics 2012, 9, 823−841


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negligible concentration change of inhibitors, i.e., constant inhibition, during the inhibition phase. In vivo predictions were done under the assumption of equal level of inhibition in vivo as measured in vitro. Preparation of Pig Liver Microsomes and Hepatocytes. Liver tissue was collected from pigs used in the educational program of physicians at Uppsala University. These domestic pigs (Yorkshire and Swedish Landrace) were from the same breeder and treated with the same anesthesia as the animals included in the in vivo study (see Animals section). Microsomes and hepatocytes were prepared as previously described.14,26 The hepatocyte suspensions were inspected microscopically, and cell yield and viability were determined using a NucleoCounter (ChemoMetec, Allerød, Denmark). The cell yield (on average 110 × 106 cells) was corrected to account for a 20% prevalence of cells with two cell nuclei. Only cell yields with a viability of >85% were used, and all experiments were conducted within 60 min of isolation. Enzyme Kinetic Assay in Pig Liver Microsomes. Microsomal incubations at a final protein concentration of 0.5 mg mL−1 with and without selected combination of inhibitors were conducted as previously described.14 Investigated starting concentrations of repaglinide were 0.01, 0.1, 5, and 50 μM. Incubations including inhibitors were performed at a repaglinide concentration of 0.1 μM. The following combinations and concentrations of inhibitors were used. In vitro treatment I (tI): ketoconazole, 1 μM; bezafibrate, 10 μM; trimethoprim, 10 μM. In vitro treatment II (tII): diclofenac, 10 μM; quinine, 10 μM. In vitro treatment III (tIII): ketoconazole, 1 μM; bezafibrate, 10 μM; trimethoprim, 10 μM; diclofenac, 10 μM; quinine 10 μM. These experiments were performed by adding the inhibitors to the incubation medium. After 5 min of preincubation, reduced β-nicotinamide adenine dinucleotide phosphate was added to a final concentration of 1 mM. Following 2 min of equilibration, the reaction was started by adding repaglinide. The final concentration of organic solvent (acetonitrile) in incubations was always 0.5%. Samples of 50 μL were consecutively removed at selected time points up to 60 min. The reactions were terminated by adding the sample to 150 μL of acetonitrile, including the internal standard at a concentration of 1 μM. After termination, samples were centrifuged for 10 min at 10000g, and an aliquot of the supernatant was drawn and stored at −20 °C until sample analysis. fuinc was determined by ultrafiltration as described previously.45 Cellular Disposition Assay in Pig Hepatocytes. Incubations were conducted by shaking at 37 °C under 5% CO2, as previously described, at the repaglinide starting concentrations of 0.05 and 5 μM. Porcine hepatocytes (final concentration 1 × 106 viable cells mL−1) and Williams medium E (pH 7.4) containing 2 mM L-glutamine and 25 mM HEPES with or without inhibitors (same combinations as described for the microsomal assay, i.e., tI, tII and tIII) were preincubated for 5 min. The reaction was initiated by the addition of repaglinide, and samples of 50 μL were removed at consecutive selected time points up to 60 min. The final concentration of organic solvent (acetonitrile) in incubations was always 0.5%. Prior to removing the samples, the incubation tubes were vortexed for 2 to 3 s to ensure that the samples contained a homogeneous cell suspension, i.e., both media and cells. The reactions were terminated by adding the samples to 150 μL of ice-cold acetonitrile containing the internal standard at a concentration of 1 μM. After termination, samples were centrifuged for 10 min at 10000g, and an aliquot of the supernatant was drawn and

literature based predictions of noninhibited pharmacokinetics; (2) analysis of noninhibited in vivo data and, if needed, adjustments of the PBPK model based on this analysis; (3) final in vitro based predictions of both noninhibited and inhibited pharmacokinetics; (4) analysis of in vivo data during inhibition; (5) evaluation of the suggested approach by comparison of in vitro base predictions and in vivo observations. The study had no intentions to use the gathered pig data for extrapolations or direct predictions of the disposition of repaglinide in humans.

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EXPERIMENTAL SECTION Chemicals. Repaglinide, 2-despiperidyl-2-amino repaglinide (M1), 2-despiperidyl-2-(5-carboxypentylamine) repaglinide (M2) and repaglinide-acyl-β-D-glucuronide (M7) were purchased from Toronto Research Chemicals (North York, Canada). Collagenase A was acquired from Roche (Mannheim, Germany). 5,5-Diethyl1,3-diphenyl-2-iminobarbituric acid (used as internal standard, IS) was a kind gift from AstraZeneca (Mölndal, Sweden). Acetonitrile, methanol and ammonium acetate of analytical grade were purchased from Merck (Darmstadt, Germany). Water was purified with a Milli-Q purification system (Millipore, Bedford, MA, USA). All other chemicals and reagents including bezafibrate, trimethoprim, diclofenac, quinine, ketoconazole, Williams medium E, trypsin inhibitor, HEPES, DNase I and EGTA were obtained from Sigma Aldrich Company Ltd. (Stockholm, Sweden). Outline of the workflow. An outline of the workflow is shown in Figure 1. Briefly, the planned progression of the work was as follows: (1) Determination of microsomal in vitro enzyme kinetics and the effect of inhibitors. (2) Investigation of the hepatocyte disposition including selective inhibition of metabolism and cell distribution, i.e., CM transport, to determine the relative contribution of these processes to the drug disposition. (3) In vivo study, using the multiple sampling site pig model, conducted in parallel with the in vitro experiment. (4) Construction of a PBPK model based on obtained in vitro information and physiological descriptors gathered from the literature. (5) Preliminary predictive simulations performed with the PBPK model on the basis of the parameters obtained in step 2. (6) Analysis of the noninhibited in vivo data. (7) If needed, refinement of the PBPK model on the basis of step 6. (8) Final in vitro based predictions of noninhibited and inhibited pharmacokinetics. (9) Analysis of inhibited in vivo data performed with the PBPK model. (10) Evaluation of the predictability of the suggested in vitro approach by comparison of the final outputs from the in vitro and in vivo investigations. Also, sensitivity simulations with the PBPK model and estimation of pharmacokinetic parameters such as terminal half-life (t1/2) and volume of distribution at steady state (Vd.ss) with a two-compartment model were performed in parallel to abovedescribed steps. Based on prior published human data, ketoconazole, bezafibrate and trimethoprim were used as inhibitors of CYP-mediated metabolism and diclofenac and quinine were used as inhibitors of CM transport.18,41−43 The specificity of chosen inhibitors to porcine enzymes/transporters could be found only for ketoconazole (CYP3A29).44 The coadministration of inhibitors in vivo was performed to support the findings in the control phase in which estimates of noninhibited parameters were acquired. No attempts were made to identify metabolizing enzymes or membrane transporters involved in repaglinide disposition for the specific animal model used. No inhibitor concentration dependency of inhibition, i.e., IC50 or Ki values, was investigated, determined or applied. Inhibition was modeled under the assumption of 825



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stored at −20 °C until sample analysis. Fraction unbound in hepatocyte incubation (fuh) was determined using the same method described for fuinc described in the microsomal assay. Animals. This study was approved by the local ethics committee for animal experiments (application number C 298/5), and the handling of animals followed national guidelines. The study included 10 male pigs of mixed breed (Yorkshire and Swedish Landrace) of which one experienced complications during surgery and did not complete the study. The animals were 10 to 12 weeks old and weighed 25.6 ± 2.1 kg (21.4− 28.0 kg). Food was withheld on the night before the experiment, but water was allowed ad libitum. The animals were delivered directly from the breeder to the laboratory on the day of the study. Anesthesia. The pigs were sedated during transport to the laboratory from the breeder by intramuscular administration of a mixture of 3 mg kg−1 tiletamine and 3 mg kg−1 zolazepam (Zoletil; Virbac S.A., Carros, France), 2.2 mg kg−1 xylazine (20 mg mL−1, Rompun Vet; Bayer AG, Leverkusen, Germany), and 0.04 mg kg−1 atropine (0.5 mg mL−1, Atropin NM Pharma; Merck NM AB, Stockholm, Sweden). To ensure that the pigs were free of pain and anesthetized throughout the whole acute experiment, they were continuously given morphine 0.5 mg kg−1 h−1 (10 mg mL−1 Morfin Meda; Meda AB, Solna, Sweden), 20 mg kg−1 h−1 ketamine (100 mg mL−1, Ketaminol Vet; Intervet, Stockholm, Sweden), and 0.25 mg kg −1 h −1 pancuronium bromide (2 mg mL−1 Pavulon; Organon AB, Gothenburg, Sweden) intravenously. To keep normal body fluid balance and retain osmotic pressure, the pigs were administered 10 mL kg−1 h−1 Rehydrex (Fresenius Kabi AB, Uppsala, Sweden), 8 mL kg−1 h−1 Ringer-acetate (Fresenius Kabi AB), and 60 mg mL−1 dextran 70 (Macrodex) in NaCl (Meda AB), in total approximately 250 mL. The Rehydrex infusion was replaced by an equal volume of Ringer-acetate 60 min following repaglinide dosing. The pigs were kept ventilated with an oxygen−air mix using a Servo 900C ventilator (SiemensElema, Solna, Sweden) introduced through an incision in the throat. Body temperature, blood pressure, blood pH and blood gases were carefully monitored by an animal technician throughout the experiment. Stable cardiac output (>4 h) in pigs anesthetized with the same drugs has earlier been reported from this laboratory.46 Surgery. The surgery was performed according to a previously reported procedure for the multiple sampling site pig model.26−28 Briefly, the abdominal cavity was opened through a midline incision. Catheters for sampling were introduced in the portal vein (VP), the hepatic vein (VH), the right femoral vein (VF) and the bile duct. A catheter was inserted to allow for urine drainage from the bladder. The body temperature of the animals was maintained by using a thermostat-controlled heating pad. Blood gases, electrocardiograms, heart rate, and arterial and central venous pressures were monitored throughout the experiment to ensure normal physiological values. The animals were allowed to stabilize after the surgery for at least 20 min before commencing the study protocol. Immediately at the end of the experiment, each pig was sacrificed by administration of 20 to 30 nmol of potassium chloride given as a bolus dose in a superior caval vein. Study Design and Treatments. In order for each animal to act as its own control, the individual animals were administered two doses of repaglinide during the day on which the study was conducted. The second dose was preceded by the administration of inhibitors. More specifically, the pigs were

given a 1.5 mg dose of repaglinide intravenously as a 2.5 min intravenous infusion through the central venous catheter (control phase; p1). After 140 min, the pigs were administered either metabolism inhibitors (TI, n = 3: ketoconazole, 0.1 g; bezafibrate, 0.2 g; trimethoprim, 0.3 g), transport inhibitors (TII, n = 3: diclofenac, 1 g; quinine, 0.5 g) or both metabolism and transport inhibitors (TIII, n = 3: ketoconazole, 0.1 g; bezafibrate, 0.2 g; trimethoprim, 0.3 g; diclofenac, 1 g; quinine, 0.5 g) by a 60 min infusion through the central venous catheter. At 210 min, the pigs received a second dose of repaglinide (1.5 mg) in a manner similar to administration of the first dose (test phase; p2). The animal was sacrificed after 420 min. The repaglinide injection solution was formulated in 100 mg mL−1 glucose and ethanol (5%) at a concentration of 0.6 mg mL−1. Inhibitors were dissolved in NaCl 0.9% containing ethanol (5%) and polysorbate 80 (0.5%) at respective concentrations (mg mL−1), ketoconazole, 0.5; bezafibrate, 1; trimethoprim, 0.75; diclofenac, 5; quinine, 2.5. At designated time points (0, 10, 20, 30, 45, 60, 75, 90, 105, 120, 150, 180, 200, 210, 220, 230, 240, 255, 270, 285, 300, 315, 330, 360, 390, and 420 min), 2.5 mL blood samples were collected from the VH, VP and VF and transferred to tubes spray coated with heparin lithium (BD Vacutainer, Plymouth, U.K.). The plasma fraction was obtained by centrifugation at 1000g for 10 min at 4 °C. Two blood samples per animal were also collected to be used for blood/ plasma ratio (B/P) measurements. A quantity of the collected blood was mixed with sterile water (1:3 v/v whole blood:water) for lysis of blood cells, and the rest was centrifuged to obtain the plasma. Bile was continuously collected in tubes kept on ice and gathered in 20 min fractions throughout the study. The accumulated urine was gathered after sacrifice. All samples were stored at −20 °C until analysis. Sample Analysis. Plasma and urine samples were thawed, and 50 μL was transferred to a 96 well plate and precipitated with 150 μL of ice-cold acetonitrile containing 0.8% (v/v) formic acid and 1 μM internal standard. Bile samples, after thawing but before precipitation, were diluted 10 times with water (1:9 v/v). Prior to analysis, samples were centrifuged for 20 min at 3220g at 4 °C in order to remove protein and cell debris from the sample. 75 μL of the supernatant was then transferred to a new plate and diluted with an equal volume of water. In vitro samples were thawed, and 75 μL was directly transferred to a 96 well plate and diluted with an equal volume of water. The analysis equipment consisted of an Acquity UPLC sample and solvent manager, and an Acquity TQD triple quadrupole mass spectrometer (Waters Corp., Milford, MA, USA). Instrument control and data processing were performed using Waters MassLynx 4.1 software including QuanOptimise and QuanLynx. Samples (8 μL) were injected on an Acquity UPLC BEH C18 1.7 μm 2.1 × 30 mm column (Waters Corp.) (kept at 40 °C), and chromatography was performed at a total flow rate of 1 mL min−1 using the following gradient elution design: mobile phase A (0.2% (v/v) formic acid in water) and mobile phase B (acetonitrile), t (min) = 0, 4% B; t = 0.5, 95% B; t = 0.8, 95% B; t = 0.81, 4% B; t = 0.9, 4% B. Ionization occurred by means of electrospray using positive electrospray multiple reaction monitoring mode. The system operated under the following conditions: capillary voltage, 1 kV; cone voltage, 40 V; extractor voltage, 3 V; RF lens, 0.1 V; source temperature, 140 °C; desolvation temperature, 450 °C; desolvation gas flow, 1200 L h−1; cone gas flow, 60 L h−1; collision gas flow, 0.25 mL min−1. Cone voltage and collision energy were optimized for each compound. The following mass 826



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metabolism. Hence, metabolic stable entities were assigned a D value of 1.

transitions (Da) were used: repaglinide (453.129 > 230.081), M1 (385.167 > 106.0087), M2 (485.219 > 262.16), M7 (629.266 > 230.122), IS (336.153 > 91.985). The lower limit of quantitation (LLOQ ) (relative standard deviation < 20%) was 0.5 nM in the in vitro matrices, plasma and urine and 5 nM in bile for all four entities. Every run included appropriate sets of quality controls to ensure method performance. Data Analysis of in Vitro Experiments. Enzyme kinetics in pig liver microsomes and disposition in hepatocytes were determined using the multiple depletion curves method and the simple disposition model previously described.14,45 In short, this was done by simultaneous fitting of the models to the disappearance of repaglinide and appearance of metabolites, for all the available starting concentrations. Iterative optimization of the enzyme kinetic model was performed by adding and removing metabolic pathways and compensation of loss in enzymatic activity (modeled as a monoexponential decay). Each independent reaction rate was tested for both linear kinetics (eq 1) and nonlinear kinetics (eq 2). dC = CL int × C prot × C × fu inc × e−kAC.mict dt

⎛ ⎞ Ve ⎜ ⎟ +1 dC tot V Vi = ⎜C tot × × fucell × CL int × i ⎟ ⎜ ⎛ Ve ⎞ dt Vtot ⎟ ⎜ ⎟+1 ⎜ ⎟ ⎝ DVi ⎠ ⎝ ⎠ × e−kAC.hept ⎛ ⎞ Ve ⎜ ⎟ +1 Vi ⎜V ⎟ C fu × × × tot cell ⎛ Ve ⎞ ⎜ max ⎟ ⎜ ⎟+1 ⎜ ⎝ DVi ⎠ dCtot Vi ⎟ ⎟ =⎜ × ⎛ ⎞ dt Vtot ⎟ Ve ⎜ +1 ⎜ ⎟ ⎜ ⎟ Vi × fucell⎟ ⎜ K m + ⎜C tot × ⎛ ⎞ ⎟ V ⎜⎜ ⎟⎟ ⎜⎜ ⎟⎟ ⎜ e ⎟+1 ⎝ DVi ⎠ ⎝ ⎠ ⎝ ⎠ × e−kAC.hept

(1)

(4)

where D is the distribution constant, Ctot is the total concentration in the suspension, Ve and Vi are the extra- and intracellular volumes, respectively, in the incubation, Vtot is the total incubation volume, fucell is the unbound intracellular fraction and kAC.hep is the rate constant describing potential reduction in hepatocyte activity. As no valid determination of fucell could be obtained, all calculations were performed using a value of fucell equal to fuh. At a cell concentration of 1 × 106 cells mL−1 the Ve/Vi ratio was calculated to a value of 199 on the basis on previously stated cellular parameters. Lag functions compensating for the time for intracellular and extracellular concentration of repaglinide to reach pseudo equilibrium were also evaluated in the in vitro analysis as previously described.14 Results from the microsome assay and control hepatocyte incubation were integrated in the analysis of the effect on the cell disposition of investigated inhibitors. More specifically, the cell disposition analysis of tI was performed with the distribution constants obtained in the control hepatocyte incubation assigned, while new estimation of enzyme kinetic parameters was performed. The analysis of tII was carried out with the enzyme kinetic parameters determined in the control hepatocyte incubation assigned, while a new estimation of D was performed. Finally, when analyzing tIII, the enzyme kinetic parameters were estimated while D was set to the value obtained in the tII analysis. PBPK Model Structure and Optimization. A PBPK model, suitable for pharmacokinetic analysis of data including the three plasma sites VH, VP and VF following an intravascular dose, was constructed. The model was also intended to be used for simulations of the effect of cellular influx and/or metabolism inhibition on the pharmacokinetics of repaglinide. Model Structure. The PBPK model consisted of 6 tissue compartments, 3 plasma compartments, one bile compartment and a urine compartment. The kinetics of the metabolites (M1, M2 and M7), determined using the plasma concentrations measured in the VP, were simultaneously described by one-compartment models that included metabolism and excretion to bile and urine. A schematic diagram of the complete model is shown in Figure 2. Briefly, the dose is administered to the mixed arterial compartment (MAC), described by the concentration−time

where C is the concentration and Cprot is the microsomal protein concentration used in the incubation and kAC.mic is the rate constant describing potential reduction in microsome activity. ⎛ Vmax × C prot × C × fu inc ⎞ dC ⎟ × e−kAC.mict =⎜ dt K m + (C × fu inc) ⎝ ⎠

(3)

(2)

where Vmax and Km represent the theoretical maximum reaction rate (amount time−1 (mg protein)−1) and the Michaelis constant (amount volume−1), respectively. For nonlinear kinetics, CLint (volume time−1 (mg protein)−1) was calculated according to CLint = Vmax/Km. No mechanistic interpretations of investigated inhibitions (competitive, uncompetitive etc.) were performed. The effect of the inhibitors on the enzyme kinetics was modeled as a simple adaptation of noncompetitive inhibition as an unspecific reduction of CLint (for linear kinetics) or Vmax (for nonlinear kinetics) with no attempts to determine or incorporate concentration dependency (i.e., Ki values). Enzymatic parameters (Vmax and CLint) determined in the microsomal assay were scaled to the hepatocyte environment by multiplying the parameters with the microsomal protein concentration in the hepatocyte (Cprot.hep). The scaling was performed based on human values as no data could be found in the literature for pig. The value of Cprot.hep (50.8 mg mL−1) was obtained by dividing the amount of microsomal protein per hepatocyte by the hepatocyte volume (Vhep). The amount of microsomal protein per hepatocyte was calculated assuming a microsomal protein abundance of 30.5 mg (g liver)−1 and a hepatocellularity of 120 × 106 hepatocytes per g liver.47,48 A hepatocyte volume of 5 × 10−9 mL was assumed based on prior published measurements.49−52 The relation between intra- and extracellular concentration at pseudo equilibrium, representing the sum of distribution processes mediated by membrane transporters, was modeled as the constant D, giving the final equations for linear (eq 3) and nonlinear kinetics (eq 4). This approach is applicable only for molecular entities undergoing 827



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interstitial fluids etc.) was described with a KP applied to the LVC. Physiological Parameters and Tissue Distribution. Physiological parameters such as tissue volumes, blood flows, tissue composition (lipids and water) and volume fraction of extracellular space (VeisT) were gathered from the literature.46,53−55 Calculation of unbound fraction in tissues (fuT) was done according to fuT = 1/(1 + (((1 − fuP)/fuP) × 0.5)), where fuP is the unbound fraction in plasma.53 As previous studies in humans have reported a small volume of distribution for repaglinide, calculations of KP were performed considering distribution essentially to extracellular space using eq 5.

KP,T =

VeisT × fuP fuT

(5)

For the prediction of plasma profiles, fuP (=0.01) and B/P were initially gathered from the literature but later obtained from the in vivo study.56 B/P in pigs was predicted to 0.75, assuming similar partitioning between plasma and blood cells in man and pig, based on previously published values in humans (B/P = 0.6) and the hematocrit in human (0.45) and pig (0.27).16,57,58 Rates of metabolism, metabolic clearance (CLmet), were described by nonlinear kinetics whenever possible and otherwise by linear kinetics. CLmet was derived by scaling respective CLint or Vmax from the hepatocyte experiment according to eq 6 and eq 7.

Figure 2. A schematic depiction of the physiological based pharmacokinetic (PBPK) model used for simulations and analysis of porcine in vivo data. The model consisted of 9 physiologically related compartments described by their respective volume and partition coefficient. Tissues and vascular compartments were connected through physiologically relevant blood flows (dotted arrows). Elimination and distribution rates (solid arrows) were described by clearance constants obtained and derived from experiments or from the literature. The kinetics of studied metabolites were modeled using one-compartment models including elimination through metabolism, bile and urine. In all, samples were collected from 14 (colored gray) of 23 compartments. Mixed arterial compartment (MAC), portal vein (VP), hepatic vein (VH), vena femuralis (VF), lumped tissue (LT), lumped tissue associated with VF (LTVF), liver vascular compartment (LVC), liver cell compartment (LCC).

CL met = CL int × A prot.liv

(6)

Vmax × A prot.liv Km + Cu

(7)

CL met =

where Aprot.liv was calculated as Cprot.hep × VLCC (=1.14 g/kg body weight). Km, estimated in the in vitro experiments, was considered to have the same value in vivo. Assuming that passive diffusion over the hepatocyte membrane in vivo was equivalent to in vitro measurements, CLdif was obtained by scaling previously reported data of cellular passive diffusion measured in human embryonic kidney cells (Pdif = 0.019 mL min−1 (mg protein)−1) as CLdif = Pdif × the total protein amount per million hepatocytes × hepatocellularity × liver weight.21 A value of 1.06 mg of protein per 106 cells was used for the total protein amount per million hepatocytes assuming similarity to rat.38 When D determined in the hepatocyte assay is greater than 1, then CLinf is acquired by CLinf = CLdif × (D − 1). Mass Transit of Repaglinide in Perfusion Limited Tissues. The basic assumptions for perfusion limited tissue compartments were as follows: well-stirred, i.e., no concentration gradients within the compartment, instantly equilibrated to the blood and equivalent unbound concentration in the tissue and blood. For noneliminating perfusion limited tissues (LTVF, LT and lung), the change in tissue concentration was described by eq 8.

profile obtained from the VP. Drug is transferred, by physiologically related blood flows, from the MAC to the kidney, the liver vascular compartment (LVC), lumped tissue associated with the VF (LTVF) and lumped tissue (LT). VH and VF represent the outlet from the LVC and the LTVF, respectively. The lung then closes the circular system as it receives blood from the kidney, LT, VF and VH and delivers it to the MAC at a blood flow equivalent to the cardiac output (CO). The rationale for relating the MAC to the VP concentrations was that the arterial concentration entering various tissues after the administration of an intravenous dose will be equal to the concentration in the VP when the contribution of metabolism and distribution in the intestines are considered to be negligible. Both the liver and the kidney were assumed to be eliminating organs. All tissues, except the liver, were modeled assuming perfusion-limited distribution, where a partition coefficient constant (KP) was used to calculate the tissue distribution at each time point. If this assumption contributes to misspecification of the input (i.e., VP concentration) to the liver, it will affect the liver disposition analysis. However, the VP concentration−time profile was well described in this case; hence the effect of this assumption was considered negligible. The liver was modeled as two compartments: the LVC, linked to the bloodstream, and the liver cell compartment (LCC), from which elimination was assumed to occur by metabolism and biliary excretion. The access of drug from the LVC to the LCC was modeled using permeability limited distribution as membrane uptake (CLinf) and passive diffusion (CLdif) clearances. Partitioning to liver tissue components not represented by LVC or LCC (e.g., fat, connective tissue,

dC T = dt

⎛ C TQ × (B/P) ⎞ T ∑v − ⎜ ⎟ KP,T ⎝ ⎠ VT

(8)

where C T is the concentration, Q T is the blood flow, V T is the volume and KP,T is the partition coefficient constant of the observed tissue. These parameters determine the rate at which the drug is removed from the tissue, i.e., the outlet 828



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biliary (CLB) clearance, giving the final equation for change in metabolite concentration (eq 12)

rate. The inlet rate is determined by the sum of outlet rates (v) from tissues, i.e., compartments, upstream in the blood circulation. The tissue concentration in the kidneys was accounted for by renal excretion according to eq 9.

dCM = [(CLCC × fucell × CL met,M) dt − (CM × fuP,M × (CLM,M + CLB,M

dCkid = {v MACKID − [(Ckid((Q K × (B/P)) dt + (CL ren × fuP)))/KP,kid]}/Vkid

+ CLR,M))]/VM

where CM is the metabolite plasma concentration in VP, V is the volume of distribution and M indicates the studied metabolite. Biliary and Renal Compartments. Elimination through renal and biliary excretion was described by fitting eqs 13−16 to cumulative excreted amount in vivo. Under the present conditions, these processes were considered unidirectional and linear. The appearance rate of unchanged repaglinide in the biliary compartment was modeled in reference to CLCC according to eq 13 and, for the metabolites, according to eq 14.

(9)

where Ckid is the concentration in the kidney, CLren is the unbound renal clearance, QK is the kidney blood flow and vMACKID is the inlet rate from MAC. Mass Transit of Repaglinide in the Liver. The drug concentration in LVC was described using the same approach as the kidney, with slight modifications related to the CM and passive distributions across the sinusoidal membrane to LCC, giving eq 10.

dMbile = CLCC × fucell × CLbile dt

dCLVC = {v MACLVC + v LCCLVC dt

dMbile,M dt

− [(CLVC((Q L × (B/P)) + ((CLdif + CL inf ) × fuP)))/KP,liver]}/VLVC

(12)

= CM × fuP,M × CLB,M

(13)

(14)

where Mbile is the amount excreted to bile. The appearance rates in the renal compartments for repaglinide and metabolites were modeled in analogy with the biliary compartment using eq 15 and eq 16, respectively.

(10)

where CLdif and CLinf represent the passive (diffusion) and CM (influx) clearance from LVC to LCC, respectively. QL represents the liver blood flow, and vMACLVC and vLCCLVC represent the inlet rates from MAC and LCC. No CM efflux from LCC back to LVC was included. Drug concentration in LCC was described by distribution clearances between LCC and LVC (CLdif and CLinf), metabolic clearances (CLM1, CLM2, CLM7), in accordance with the hepatocyte in vitro analysis, and biliary excretion clearance (CLbile). Excretion to bile was considered to occur under linear conditions, and accordingly CLbile represented the sum of involved processes, both passive and possible CM (see Biliary and Renal Compartments section). No reabsorption from bile to LCC was considered, giving the final equation (eq 11) describing the concentration in LCC.

dM urine = Ckid × fuP × CL ren dt

dM urine,M dt

= CM × fuP,M × CLR,M

(15)

(16)

where Murine is the amount excreted to urine. Biliary and renal clearance were estimated via the PBPK model from the in vivo data. No predictions of biliary or renal excretion were performed. In all subsequent predictive simulations these two elimination routes were set to zero. Strategy for Model Optimization. The volume in each of the three plasma compartments in the model (VH, VF and MAC (VP)) was designated the same value, that is, one-third of the total volume of blood. This was done to enable the differences in the concentration of the blood compartments to be related to elimination and distribution processes, and not to volume differences. The values of VT, Q and KP assigned to LTVF and LT for the initial model, used for predictive simulations, were specified by the physiology. Hence, as the VF sample was drawn from the femoral vein located in one of the hind legs, LTVF was designated the approximate VT, Q and associated KP values of a leg. Then, LT was allocated values for unspecified parts of the pig body. Also, as the renal and biliary excretion of unchanged repaglinide in humans was reported to represent only a small fraction of the total elimination, these processes were set to zero in the simulations.16 Predictive simulations of repaglinide pharmacokinetics were performed on the basis of gathered literature data (see Physiological Parameters and Tissue Distribution section) and on hepatocyte related in vitro results. The analysis of the in vivo data was then performed. During the analysis the PBPK model was allowed to estimate scaling factors for clearance processes, liver distribution processes, level of inhibition, and KP for VFLT, LT and LVC. The analysis of

dCLCC = [v LVCLCC − (CLCC × fucell dt × (∑ CL met + CLbile + CLdif ))]/VLCC (11)

where vLVCLCC represents the inlet rate (including both the passive and CM processes) from LVC to LCC, ∑CLmet represents all involved metabolic pathways and fucell is the intracellular unbound fraction. In analogy with the in vitro hepatocyte analysis, all calculations were performed using a value of fucell equal to fuh. Kinetic Modeling of Metabolites. The concentration− time profiles of the monitored metabolites (M1, M2 and M7) in VP were analyzed by one compartment models. The formation rate was described by respective metabolic clearance of repaglinide, and the elimination included metabolism (CLM) (according to the hepatocyte result) as well as renal (CLR) and 829



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where Vpla is the plasma volume, Very is the volume of erythrocytes, E/P is the erythrocyte/plasma concentration ratio (calculated as E/P = ((B/P) − (1 − hematocrit))/hematocrit), VT,i is the physiological volume (weight) of the ith tissue, and KP,i and Ei are the partition coefficient constant and extraction ratio, respectively. E is calculated as E = CL/(Q × (B/P)) where CL is the plasma clearance. Two-Compartment Model. Plasma profiles for repaglinide showed an apparent two-compartment behavior, and estimations of the Vd.ss, clearance (CL) and t1/2 were estimated using a two-compartment model parametrized as the sum of exponential terms (Ct = C1 × e−λ1t + C2 × e−λ2t). This analysis was performed for both simulated and observed in vivo data to enable evaluation of the simulations outcome. All parameters were calculated independently for control phase (p1) and test phase (p2) as no mechanistic interpretations can be made from data derived using this methodology. CL was calculated as CL = dose/(C1/λ1 + C2/λ2) where C1 and C2 represent the corresponding zero-time intercepts and λ1 and λ2 indicate the rate constants for the first and second exponential terms, respectively. Vd.ss was calculated as Vd.ss = dose × (C1/λ12 + C2/ λ22)/(C1/λ1 + C2/λ2)2, and t1/2 was calculated as t1/2 = ln(2)/λ2. Data Analysis. Akaike information criteria, visual examination of data, residual plots and the precision of parameter estimation were used for evaluation and comparison of the goodness of fit for the different models. All analyses of kinetic data were performed (weighted 1/ŷ2) using WinNonlin Professional software V5.2 (Pharsight Corp., CA). The number of degrees of freedom in the analysis was, depending on number of observations, equal to 160 ± 2 calculated as follows: degrees of freedom = number of observations − number of parameters. Simulations were performed with Berkeley Madonna software v8.3.18 (University of California, Berkley, CA, USA).

the control phase (p1) and the test phase (p2) for each individual was performed simultaneously. The estimated parameters were either global (with the same value being used for both p1 and p2, implying that they were phase independent) or local (in which case they were estimated individually for each phase and were phase dependent). The model considered p2 to start at 200 min. Pharmacokinetic parameters (CLM, CLR, CLB and V) describing the plasma profiles of the metabolites were also estimated. Sensitivity Simulations. The primary objective of the performed simulations was to elucidate the relative importance of oxidative metabolism and sinusoidal influx inhibition on the pharmacokinetics of repaglinide. Simulations were performed using the constructed PBPK model, corrected with the scaling factors and those KP values that were estimated by fitting from the in vivo analysis. Sensitivity to a reduction to 30% of control activities of hepatic oxidative metabolism and/or CM influx was investigated. A secondary objective of the simulations was to evaluate the predictive performance of the PBPK model including the parameters generated in the in vitro disposition model. Prediction and Calculation of Pharmacokinetic Parameters. Predictions of hepatic plasma clearance (CLH) were performed directly from hepatocyte derived in vitro clearance using the well-stirred model (eq 17) CLH =

Q H × fuP × ∑ CL met × D Q H + (∑ CL met × D × fuP/(B/P))

(17)

and using a mechanistic disposition model previously described (eq 18).36,39 CLH = [Q H × (B/P) × fuP ×

∑ CLmet

■

× (CL inf + CLdif )]/[Q H × (B/P)

RESULTS In Vitro. Typical plots from liver microsome and hepatocyte incubations and each model fit are shown in Figure 3. The metabolic schemes used for determination of the enzyme kinetics in microsomes and disposition in hepatocytes are shown in Figure 4. Parameters obtained from the in vitro microsome and hepatocyte assays are summarized in Table 1. Microsomes. Vmax and Km could accurately be determined for the biotransformation of repaglinide to M1 and M2 (M1, Vmax = 166 pmol min−1 mg−1, Km = 6.5 μM; M2, Vmax = 27.7 pmol min−1 mg−1, Km = 5.6 μM). From the available data, the metabolic reaction generating M1 from M2 could only be described with linear kinetics (CLint = 27.8 μL min−1 mg−1). M1 was formed to a higher extent (13%) than M2 (3%). However, as the combined formation rate of M1 and M2 only represented approximately 16% of the total depletion rate (CLint.tot = 190 μL min−1 mg−1) of repaglinide, the results indicated that a major part of the metabolism formed other metabolites. Selected CYP inhibitors (tI and tIII) decreased the metabolism (16% and 6% of control, respectively). Some inhibition could also be seen by tII, mainly on the biotransformation to M1 and the unknown pathways, but in relation to tI and tIII this effect was less significant. The fraction unbound in the incubation was calculated as 0.72. Data were not sufficient for accurate determination of kAC.mic for the individual reactions, and consequently one common parameter was estimated for all reactions (kAC.mic = 0.015). Hepatocytes. The proposed procedure of scaling enzyme kinetic parameters determined in the microsomal assay for incorporation in the cell disposition model was possible for the

× (∑ CL met + CLdif ) + ((CL inf + CLdif ) ×

∑ CLmet × fuP)]

(18)

Estimation of CLH from the in vivo study was made in analogy with the mechanistic disposition model involving the addition of canalicular excretion to bile using eq 19. CLH = [Q H × (B/P) × fuP × (∑ CL met + CLbile) × (CL inf + CLdif )]/[Q H × (B/P) × (∑ CL met + CLdif + CLbile) + ((CL inf + CLdif )(∑ CLmet + CLbile) × fuP)] (19)

The contribution of biliary excretion to the hepatic plasma clearance of repaglinide in vivo (i.e., CLB) was calculated by subtracting the calculated value using eq 18 from the calculated value using eq 19 (i.e., CLH.eq19 − CLH.eq18). In vivo renal clearance (CLR) was calculated using eq 17 by substituting (∑CLmet × D) with CLren and QH with QK. Estimation of the volume of distribution at steady state (Vd.ss) was calculated both for the simulated and in vivo data using eq 20.53 Vd.ss = Vpla + (Very × (E/P)) +

∑ KP,iVT,i(1 − Ei) (20) 830



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Figure 3. Typical plots from the microsome (left) and hepatocyte (right) studies including respective model fits (solid lines) showing repaglinide (triangles), M1 (diamonds), M2 (circles) and M7 (squares). The plots present microsome incubations performed at initial concentrations of 5000 (open symbols) and 100 nM (closed symbols) and hepatocyte incubations performed at 5000 (open symbols) and 50 nM (closed symbols). Data is shown as the mean with the SD (n = 3).

Figure 4. The metabolic pathways of repaglinide included in the models for analysis of in vitro assays. (A) Microsome study. (B) Hepatocyte study.

Table 1. Summary of the Kinetic Variables, Maximum Velocity of the Reaction (Vmax), Michaelis Constant (Km), Intrinsic Clearance (CLint) and Distribution Constants (D), Obtained from Porcine Liver Microsomes and Porcine Hepatocyte Suspensiona Microsomes control

tI tII tIII

Vmax (pmol min−1 mg−1) Km (μM) CLint (μL min−1 mg−1) CLint (μL min−1 mg−1) CLint (μL min−1 mg−1) CLint (μL min−1 mg−1)

DREP DM2 CLint (REP → M1) (μL min−1 mg−1) CLint (REP → M2) μL min−1 mg−1) Vmax (REP → M7) (pmol min−1 mg−1) Km (REP → M7) (μM) CLint (REP → M7) (μL min−1 mg−1)

REP → M1

REP → M2

M2 → M1

REP →

166 ± 14 6.5 ± 0.65 25.6 ± 1.7 2.90 ± 0.22 15.7 ± 1.5 − Hepatocytes

27.7 ± 2.5 5.6 ± 0.59 4.95 ± 0.50 1.34 ± 0.23 4.00 ± 0.65 3.29 ± 2.9

−b − 27.8 ± 9.2 − 21.0 ± 10 −

− − 190 ± 14 30.2 ± 10 107 ± 11 12.2 ± 14

control

tI

tII

tIII

8.26 ± 0.78 1.42 ± 0.31 1.64 ± 0.15 4.95e 73.2 ± 7.9 6.2 ± 0.64 11.9 ± 1.1

+c + 0.126 ± 0.028 0.30 ± 0.043 −−f −− 10.7 ± 1.5

4.31 ± 0.25 0.35 ± 0.12 + + −− −− 12.1 ± 0.71

++d ++ 0.094 ± 0.017 0.205 ± 0.022 −− −− 10.2 ± 0.91

a Values are shown as means with SD. b(−) Could not be determined. c(+) Using value determined in hepatocyte control experiment. d(++) Using value determined in hepatocyte tII experiment. eUsing value determined in microsome control experiment. f(− −) Not determined.

hepatocyte specific Vmax. Direct glucuronidation to M7 represented the major (60%) metabolic pathway. Vmax (73.2 pmol min−1 mg−1) and Km (6.2 μM) for the glucuronidation were determined in the control experiment and then applied to the inhibition analysis. The unbound fraction determined in hepatocytes (fuh = 0.87) was used in the calculations of unbound Km.

formation of M2. However, this was not possible for biotransformation to M1 as this reaction in hepatocytes was considerably slower than that observed in microsomes. The in vitro model discrepancy was not believed to be caused by differences in Km, and, for this reason, determination of CLint for the M1 formation was performed by estimation of a 831



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Table 2. Estimated and Predicted Pharmacokinetic Parametersa method

control (p1)

I I I I

CLinf (mL min−1 kg−1) CLdif (mL min−1 kg−1) CLinf/CLdif ∑CLmet (mL min−1 kg−1)

I (eq 19) II I I I I I II

CLH (mL min−1 kg−1) CL (mL min−1 kg−1) EH (%) CLB (μL min−1 kg−1) CLR (μL min−1 kg−1) ER (%) Vd.ss (L kg-1) t1/2 (min)

A (eq 17) B (eq 18) C C

CLH (mL min−1 kg−1) CLH (mL min−1 kg−1) Vd.ss (L kg−1) t1/2 (min)

TI

Estimates Primary Parameters 550 ± 230 +b 100 ± 74 + 6.1 ± 3.2 + 89 ± 32 36 ± 16 (−44%) Secondary Parameters 4.3 ± 2.0 2.7 ± 0.40 (−29%) 4.6 ± 1.9 2.6 ± 0.41 (−37%) 7.5 ± 3.5 4.6 ± 0.68 4.3 ± 4.2 + 50 ± 69 + 0.3 ± 0.4 + 0.28 ± 0.14 0.37 ± 0.18 (+1.8%) 43 ± 10 56 ± 5.4 (+45%) Predictions 1.5 0.91 (−39%) 1.3 0.88 (−34%) 0.25 0.24 (−1%) 120 180 (+48%)

TII

TIII

220 ± 150 (−56%) + 2.6 ± 2.0 +

400 ± 42 (−50%) + 3.2 ± 1.4 43 ± 28 (−35%)

2.3 ± 1.0 (−43%) 2.1 ± 1.0 (−52%) 3.9 ± 1.7 + + + 0.31 ± 0.16 (+1.3%) 70 ± 16 (+60%)

1.9 ± 0.11 (−57%) 1.7 ± 0.54 (−62%) 3.2 ± 1.1 + + + 0.19 ± 0.25 (+0.67%) 74 ± 19 (+70%)

0.79 (−47%) 0.71 (−47%) 0.24 (−1%) 220 (+81%)

0.45 (−70%) 0.44 (−67%) 0.24 (−2%) 340 (+190%)

a

Values are shown as the mean with the SD. Primary parameters were estimated through analysis with the PBPK model. Determination of secondary parameters was made on parameters obtained through PBPK model analysis (I) or by a two-compartment model (II). Predictions of CLH were made directly on in vitro parameters determined in the hepatocyte assay using the well-stirred model (A) or the mechanistic disposition model (B). The PBPK model with initial set of input was used for prediction of Vd.ss as well as for generating the plasma concentration time profiles on which t1/2 was acquired by using a two-compartment model (C). Percentage in parentheses is the mean of individual change from control. b(+) Same value as in control.

Pharmacokinetic parameters are summarized in Table 2. The shape of the predicted concentration−time profile for the VF compartment did not fully agree with the observed profiles. With designated physiological parameters (Q, VT and KP) representing a hind leg (muscles), the simulated concentrations in VF demonstrated slower equilibration than that observed in vivo. These parameters were therefore adjusted to get a better fit to observed profile in the peripheral plasma. This exercise had no impact on VP and VH profiles, and consequently this did not affect the hepatic disposition analysis. In Vivo. Table 2 summarizes parameters estimated using the mechanistic PBPK model, the two-compartment model and the well-stirred model. Individual plasma concentration profiles in VH, VP and VF of repaglinide, M2 and M7 are presented in the Supporting Information. Concentrations of M1 were below limit of quantitation for the majority of the plasma samples, and for this reason, the M1 plasma data was excluded from the pharmacokinetic analysis. In addition, all measurements between the commencement of the infusion of inhibitors at 140 min up to the second administration of repaglinide at 210 min were excluded from the analysis as it was recognized that the pharmacokinetics during this period were affected by the inhibitors. Renal elimination was considered to be unaffected by the treatments in p2. fuP and B/P were determined to 0.0137 and 0.575, respectively. The value of B/P indicated that the pigs included in this study had a higher hematocrit than specified (B/P = 0.575 → hematocrit ≥0.425). All estimations and analyses based on the in vivo data were performed assuming the same partitioning between erythrocytes and plasma as in the predictions (i.e., a hematocrit of 0.45 was assumed). In Vivo Pharmacokinetics. Plasma, bile and urine concentration time profiles, including the PBPK model fit of a typical animal, are shown in Figure 6 to illustrate the performance of the PBPK model. The following estimates of

In contrast to the results obtained in the microsomal assay, only an insignificant proportion (

The Pharmacokinetics and Hepatic Disposition of Repaglinide in Pigs

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