Identification and quantitation of enzyme and transporter contributions to hepatic clearance for the assessment of potential drug-drug interactions

Drug-drug interactions (DDIs) involving drug-metabolizing enzymes and membrane transporters can lead to alteration in substrate drug (victim) exposure, and can influence the pharmacological and toxicological effects. In order to predict DDI potential, it is important to quantitatively characterize the major enzyme(s) and/or transporter(s) involved in the clearance of drugs, in terms of fraction metabolized (f_m) and fraction transported (f_t). In this review, we discuss a strategy using Extended Clearance Classification System (ECCS) to identify the clearance mechanism(s) early in drug discovery, and subsequently rational staging of in vitro characterization to determine f_m and f_t. In addition, the examples of complex DDIs due to involvement of transporter-enzyme interplay in the hepatic clearance are discussed.     

Mechanistic Modeling to Predict the Transporter- and Enzyme-Mediated Drug-Drug Interactions of Repaglinide

Purpose

Quantitative prediction of complex drug-drug interactions (DDIs) is challenging. Repaglinide is mainly metabolized by cytochrome-P-450 (CYP)2C8 and CYP3A4, and is also a substrate of organic anion transporting polypeptide (OATP)1B1. The purpose is to develop a physiologically based pharmacokinetic (PBPK) model to predict the pharmacokinetics and DDIs of repaglinide.

Methods

In vitro hepatic transport of repaglinide, gemfibrozil and gemfibrozil 1-O-β-glucuronide was characterized using sandwich-culture human hepatocytes. A PBPK model, implemented in Simcyp (Sheffield, UK), was developed utilizing in vitro transport and metabolic clearance data.

Results

In vitro studies suggested significant active hepatic uptake of repaglinide. Mechanistic model adequately described repaglinide pharmacokinetics, and successfully predicted DDIs with several OATP1B1 and CYP3A4 inhibitors (<10% error). Furthermore, repaglinide-gemfibrozil interaction at therapeutic dose was closely predicted using in vitro fraction metabolism for CYP2C8 (0.71), when primarily considering reversible inhibition of OATP1B1 and mechanism-based inactivation of CYP2C8 by gemfibrozil and gemfibrozil 1-O-β-glucuronide.

Conclusions

This study demonstrated that hepatic uptake is rate-determining in the systemic clearance of repaglinide. The model quantitatively predicted several repaglinide DDIs, including the complex interactions with gemfibrozil. Both OATP1B1 and CYP2C8 inhibition contribute significantly to repaglinide-gemfibrozil interaction, and need to be considered for quantitative rationalization of DDIs with either drug.     

The evolution of the OATP hepatic uptake transport protein family in DMPK sciences: from obscure liver transporters to key determinants of hepatobiliary clearance

Over the last two decades the impact on drug pharmacokinetics of the organic anion transporting polypeptides (OATPs: OATP-1B1, 1B3 and 2B1), expressed on the sinusoidal membrane of the hepatocyte, has been increasingly recognized. OATP-mediated uptake into the hepatocyte coupled with subsequent excretion into bile via efflux proteins, such as MRP2, is often referred to as hepatobiliary excretion. OATP transporter proteins can impact some drugs in several ways including pharmacokinetic variability, pharmacodynamic response and drug-drug interactions (DDIs). The impact of transporter mediated hepatic clearance is illustrated with case examples, from the literature and also from the Pfizer portfolio. The currently available in vitro techniques to study the hepatic transporter proteins involved in the hepatobiliary clearance of drugs are reviewed herein along with recent advances in using these in vitro data to predict the human clearance of compounds recognized by hepatic uptake transporters.     

A new approach to predicting human hepatic clearance of CYP3A4 substrates using monkey pharmacokinetic data

1. Focusing on the genetic similarity of CYP3A subfamily enzymes (CYP3A4 and CYP3A5) between monkeys and humans, we have attempted to provide a single-species approach to predicting human hepatic clearance (CL_h) of CYP3A4 substrates using pharmacokinetic parameters in cynomolgus monkeys following intravenous administrations.

2. Hepatic intrinsic clearance (CL_int,h) of six CYP3A4 substrates (alprazolam, clonazepam, diltiazem, midazolam, nifedipine, and quinidine), covering a wide range of clearance, in monkeys correlated well with that cited in literature for humans (R = 0.90) with a simple equation of Y = 0.165X (Y: human CL_int,h, X: monkey CL_int,h, represented in mL/min/kg).

3. To verify the predictability of human CL_int,h, monkey CL_int,h of a test set of CYP3A4 substrates cited in literature (dexamethasone, nifedipine, midazolam, quinidine, tacrolimus, and verapamil) was applied to the equation and human CL_int,h was calculated. The human CL_int,h of all the substrates was predicted within 3-fold error (fold error: 0.35–2.77).

4. The predictability of human CL_h by our method was superior to common in vivo prediction methods (allometry and liver blood flow method). These results suggest that human hepatic clearance of CYP3A4 substrates can be predicted by applying cynomolgus monkey CL_int,h obtained following intravenous administrations in each laboratory to the simple equation.     

Reduced Physiologically-Based Pharmacokinetic Model of Repaglinide: Impact of OATP1B1 and CYP2C8 Genotype and Source of In Vitro Data on the Prediction of Drug-Drug Interaction Risk

Purpose

To investigate the effect of OATP1B1 genotype as a covariate on repaglinide pharmacokinetics and drug-drug interaction (DDIs) risk using a reduced physiologically-based pharmacokinetic (PBPK) model.

Methods

Twenty nine mean plasma concentration-time profiles for SLCO1B1 c.521T>C were used to estimate hepatic uptake clearance (CL_uptake) in different genotype groups applying a population approach in NONMEM v.7.2.

Results

Estimated repaglinide CL_uptake corresponded to 217 and 113 μL/min/10⁶ cells for SLCO1B1 c.521TT/TC and CC, respectively. A significant effect of OATP1B1 genotype was seen on CL_uptake (48% reduction for CC relative to wild type). Sensitivity analysis highlighted the impact of CL_met and CL_diff uncertainty on the CL_uptake optimization using plasma data. Propagation of this uncertainty had a marginal effect on the prediction of repaglinide OATP1B1-mediated DDI with cyclosporine; however, sensitivity of the predicted magnitude of repaglinide metabolic DDI was high. In addition, the reduced PBPK model was used to assess the effect of both CYP2C8*3 and SLCO1B1 c.521T>C on repaglinide exposure by simulations; power calculations were performed to guide prospective DDI and pharmacogenetic studies.

Conclusions

The application of reduced PBPK model for parameter optimization and limitations of this process associated with the use of plasma rather than tissue profiles are illustrated.     

Use of uptake intrinsic clearance from attached rat hepatocytes to predict hepatic clearance for poorly permeable compounds

1. We previously reported that the accuracy of clearance (CL) prediction could be differentiated by permeability. CL was drastically under-predicted by in vitro metabolic intrinsic clearance (CL_int) for compounds with low permeability (<5?×?10^?6 cm/s).

2. We determined apparent uptake CL_int by measuring initial disappearance from medium using attached rat hepatocytes and metabolic CL_int by measuring parent depletion in suspended rat hepatocytes (cells and medium).

3. Uptake and metabolic CL_int were comparable for highly permeable metabolic marker compounds. In contrast, uptake CL_int was 3- to 40-fold higher than metabolic CL_int for rosuvastatin, bosentan, and 15 proprietary compounds, which had low permeability, suggesting that uptake could be a rate-determining step in hepatic elimination for these poorly permeable compounds.

4. The prediction of hepatic CL was improved significantly when using uptake CL_int for the compounds with low permeability. The average fold error was 2.2 and 6, as opposed to >11 and >47 by metabolic CL_int, with and without applying a scaling factor of 4, respectively.

5. Uptake CL_int from attached hepatocytes can be used as an alternative approach to predict hepatic clearance and to understand the significance of hepatic uptake in elimination in an early drug discovery setting.

     

Clinical importance of OATP1B1 and OATP1B3 in drug-drug interactions

OATP1B1 and OATP1B3 are transporters that are expressed on the sinusoidal membrane of hepatocytes; they accept a number of therapeutic reagents as their substrates. In vitro and in vivo studies have shown that some drugs inhibit these transporters and cause clinically relevant drug-drug interactions (DDIs). Among these drugs, cyclosporin A markedly increases the plasma concentrations of OATP1B1 substrates. In such cases, the area under the plasma concentration-time curve and the maximum concentration of the affected drugs are increased to a similar degree. Even for OATP1B1 substrates that are metabolized in the liver, the hepatic uptake rate is a determinant of overall hepatic clearance, and the DDIs are partly caused by the inhibition of OATP1B1. Gemfibrozil displays DDIs with some OATP1B1 substrates, although their extent is small. Rifampicin and some HIV protease inhibitors are also OATP1B1 inhibitors. Rifampicin is also an inducer of metabolic enzymes, and although its single coadministration produces an increase in the plasma concentration of the affected drugs, multiple coadministrations may result in reductions in the plasma concentrations of OATP1B1 and CYP3A4 bisubstrates. As a large number of therapeutic reagents are substrates and/or inhibitors of OATP1B1 and OATP1B3, we should be aware of DDIs caused by the inhibition of these transporters.     

The evolution of the OATP hepatic uptake transport protein family in DMPK sciences: from obscure liver transporters to key determinants of hepatobiliary clearance

1. Over the last two decades the impact on drug pharmacokinetics of the organic anion transporting polypeptides (OATPs: OATP-1B1, 1B3 and 2B1), expressed on the sinusoidal membrane of the hepatocyte, has been increasingly recognized.

2. OATP-mediated uptake into the hepatocyte coupled with subsequent excretion into bile via efflux proteins, such as MRP2, is often referred to as hepatobiliary excretion.

3. OATP transporter proteins can impact some drugs in several ways including pharmacokinetic variability, pharmacodynamic response and drug-drug interactions (DDIs).

4. The impact of transporter mediated hepatic clearance is illustrated with case examples, from the literature and also from the Pfizer portfolio.

5. The currently available in vitro techniques to study the hepatic transporter proteins involved in the hepatobiliary clearance of drugs are reviewed herein along with recent advances in using these in vitro data to predict the human clearance of compounds recognized by hepatic uptake transporters.

     

Interactions of crizotinib and gefitinib with organic anion-transporting polypeptides (OATP)1B1, OATP1B3 and OATP2B1: gefitinib shows contradictory interaction with OATP1B3

1.?The drug–drug interaction (DDI) mediated by organic anion-transporting polypeptide (OATP)1B1, OATP1B3 and OATP2B1 has a major impact on the hepatic clearance of drugs. The effects of tyrosine kinase inhibitors (TKIs) on OATPs have not been well studied. In the present study, we evaluated the contribution of OATPs to the hepatic uptake of crizotinib and gefitinib and the interaction of those TKIs with OATPs to estimate DDIs.

2.?To clarify whether crizotinib and gefitinib were substrates for OATPs, we performed uptake studies. We examined the effects of the TKIs on uptake of typical substrates and fluvastatin via OATPs. IC₅₀ and EC₅₀ values of the TKIs were calculated.

3.?OATP1B3- and OATP2B1-mediated crizotinib uptake and OATP2B1-mediated gefitinib uptake were observed. Gefitinib accelerated OATP1B3-mediated [³H]TCA uptake and inhibited OATP2B1-mediated [³H]E₃S uptake. On the other hand, gefitinib inhibited OATP1B1- and OATP2B1-mediated fluvastatin uptake.

4.?We provided basic information to estimate the DDI on OATPs caused by TKIs. The DDI on OATPs caused by gefitinib could occur in a normal clinical situation. And the uptake of crizotinib into the intrahepatocellular environment via OATPs may induce DDI and liver damage. We therefore emphasize the necessity of careful use of TKIs.     

Prediction of Human Drug Clearance from <Emphasis Type="Italic">in Vitro</Emphasis> and Preclinical Data Using Physiologically Based and Empirical Approaches

No HeadingPurpose. The aim of this study is to compare the accuracy of five methods for predicting in vivo intrinsic clearance (CL_int) and seven for predicting hepatic clearance (CL_h) in humans using in vitro microsomal data and/or preclinical animal data.Methods. The human CL_int was predicted for 33 drugs by five methods that used either in vitro data with a physiologic scaling factor (SF), with an empirical SF, with the physiologic and drug-specific (the ratio of in vivo and in vitro CL_int in rats) SFs, or rat CL_int directly and with allometric scaling. Using the estimated CL_int, the CL_h in humans was calculated according to the well-stirred liver model. The CL_h was also predicted using additional two methods: using direct allometric scaling or drug-specific SF and allometry.Results. Using in vitro human microsomal data with a physiologic SF resulted in consistent underestimation of both CL_int and CL_h . This bias was reduced by using either an empirical SF, a drug-specific SF, or allometry. However, for allometry, there was a substantial decrease in precision. For drug-specific SF, bias was less reduced, precision was similar to an empirical SF. Both CL_int and CL_h were best predicted using in vitro human microsomal data with empirical SF. Use of larger data set of 52 drugs with the well-stirred liver model resulted in a best-fit empirical SF that is 9-fold increase on the physiologic SF.Conclusions. Overall, the empirical SF method and the drug-specific SF method appear to be the best methods; they show lower bias than the physiologic SF and better precision than allometric approaches. The use of in vitro human microsomal data with an empirical SF may be preferable, as it does not require extra information from a preclinical study.     

Cyclosporine Inhibition of Hepatic and Intestinal CYP3A4, Uptake and Efflux Transporters: Application of PBPK Modeling in the Assessment of Drug-Drug Interaction Potential

Purpose

To apply physiologically-based pharmacokinetic (PBPK) modeling to investigate the consequences of reduction in activity of hepatic and intestinal uptake and efflux transporters by cyclosporine and its metabolite AM1.

Methods

Inhibitory potencies of cyclosporine and AM1 against OATP1B1, OATP1B3 and OATP2B1 were investigated in HEK293 cells +/? pre-incubation. Cyclosporine PBPK model implemented in Matlab was used to assess interaction potential (+/? metabolite) against different processes (uptake, efflux and metabolism) in liver and intestine and to predict quantitatively drug-drug interaction with repaglinide.

Results

Cyclosporine and AM1 were potent inhibitors of OATP1B1 and OATP1B3, IC₅₀ ranging from 0.019–0.093 μM following pre-incubation. Cyclosporine PBPK model predicted the highest interaction potential against liver uptake transporters, with a maximal reduction of >70% in OATP1B1 activity; the effect on hepatic efflux and metabolism was minimal. In contrast, 80–97% of intestinal P-gp and CYP3A4 activity was reduced due to the 50-fold higher cyclosporine enterocytic concentrations relative to unbound hepatic inlet. The inclusion of AM1 resulted in a minor increase in the predicted maximal reduction of OATP1B1/1B3 activity. Good predictability of cyclosporine-repaglinide DDI and the impact of dose staggering are illustrated.

Conclusions

This study highlights the application of PBPK modeling for quantitative prediction of transporter-mediated DDIs with concomitant consideration of P450 inhibition.     

Relative Importance of Intestinal and Hepatic Glucuronidation—Impact on the Prediction of Drug Clearance

Purpose  To assess the extent of intestinal and hepatic glucuronidation in vitro and resulting implications on glucuronidation clearance prediction. Methods  Alamethicin activated human intestinal (HIM) and hepatic (HLM) microsomes were used to obtain intrinsic glucuronidation clearance (CL_int,UGT) for nine drugs using substrate depletion. The in vitro extent of glucuronidation (fm_UGT) was determined using P450 and UGT cofactors. Utility of hepatic CL_int for the prediction of in vivo clearance was assessed. Results  fm_UGT (8–100%) was comparable between HLM and HIM with the exception of troglitazone, where a nine-fold difference was observed (8% and 74%, respectively). Scaled intestinal CL_int,UGT (per g tissue) was six- and nine-fold higher than hepatic for raloxifene and troglitazone, respectively, and comparable to hepatic for naloxone. The remaining drugs had a higher hepatic than intestinal CL_int,UGT (average five-fold). For all drugs with P450 clearance, hepatic CL_int,CYP was higher than intestinal (average 15-fold). Hepatic CL_int,UGT predicted on average 22% of observed in vivo CL_int; with the exception of raloxifene and troglitazone, where the prediction was only 3%. Conclusion  Intestinal glucuronidation should be incorporated into clearance prediction, especially for compounds metabolised by intestine specific UGTs. Alamethicin activated microsomes are useful for the assessment of intestinal glucuronidation and fm_UGT in vitro.     

Prediction of pharmacokinetic profile of valsartan in human based on in vitro uptake transport data

The aim of this study was to evaluate a strategy based on a physiologically based pharmacokinetic (PBPK) model for the prediction of PK profiles in human using in vitro data when elimination of compounds relies on active transport processes. The strategy was first applied to rat in vivo and in vitro data in order to refine the PBPK model. The model could then be applied to human in vitro uptake transport data using valsartan as a probe substrate. Plated rat and human hepatocytes, and cell lines overexpressing human OATP1B1 and OATP1B3 were used for in vitro uptake experiments. The uptake rate of valsartan was higher for rat hepatocytes (K _m,u = 28.4 ± 3.7 μM, V _max = 1318 ± 176 pmol/mg/min and P _dif = 1.21 ± 0.42 μl/mg/min) compared to human hepatocytes (K _m,u = 44.4 ± 14.6 μM, V _max = 304 ± 85 pmol/mg/min and P _dif = 0.724 ± 0.271 μl/mg/min). OATP1B1 and 1B3 parameters were correlated to human hepatocyte data using experimentally established relative activity factors (RAF). Resulting PBPK simulations using those in vitro data were compared for plasma (human and rat) and bile (rat) concentration–time profiles following i.v. bolus administration of valsartan. An uncertainty analysis indicated that the scaled in vitro uptake clearance had to be adjusted with an additional empirical scaling factor of 5 to match the plasma concentrations and biliary excretion profiles. Applying this model, plasma clearances (CL_P) for rat and human were predicted within two-fold relative to predictions based on respective in vitro data. The corrected hepatic uptake transport kinetic parameters enabled the prediction of valsartan in vivo PK profiles and plasma clearances, using PBPK modeling. Moreover, the interspecies difference in elimination rate observed in vivo was correctly reflected in the transport parameters determined in vitro. More data are needed to support more general applications of the proposed approach including its use for metabolized compounds.     

Clinical evaluation of [18F]pitavastatin for quantitative analysis of hepatobiliary transporter activity

It is widely accepted that uptake and efflux transporters on clearance organs play crucial roles in drug disposition. Although in vitro transporter assay system can identify the intrinsic properties of the target transporters, it is not so easy to precisely predict in vivo pharmacokinetic parameters from in vitro data. Positron emission tomography (PET) imaging is a useful tool to directly assess the activity of drug transporters in humans. We recently developed a practical synthetic method for fluorine-18-labeled pitavastatin ([¹⁸F]PTV) as a PET probe for quantitative evaluation of hepatobiliary transport. In the present study, we conducted clinical PET imaging with [¹⁸F]PTV and compared the pharmacokinetic properties of the probe for healthy subjects with or without rifampicin pretreatment. Rifampicin pretreatment significantly suppressed the hepatic maximum concentration and biliary excretion of the probe to 52% and 34% of the control values, respectively. Rifampicin treatment markedly decreased hepatic uptake clearance (21% of the control), and moderately canalicular efflux clearance with regard to hepatic concentration (52% of the control). These results demonstrate that [¹⁸F]PTV is a useful probe for clinical investigation of the activities of hepatobiliary uptake/efflux transporters in humans.     

Multiple Inhibition Mechanisms and Prediction of Drug–Drug Interactions: Status of Metabolism and Transporter Models as Exemplified by Gemfibrozil–Drug Interactions

Purpose To assess the consequences of multiple inhibitors and differential inhibition mechanisms on the prediction of 12 gemfibrozil drug–drug interactions (DDIs). In addition, qualitative zoning of transporter-related gemfibrozil and cyclosporine DDIs was investigated. Methods The effect of gemfibrozil and its acyl-glucuronide on different enzymes was incorporated into a metabolic prediction model. The impact of CYP2C8 time-dependent inhibition by gemfibrozil acyl-glucuronide was assessed using repaglinide, cerivastatin, loperamide, rosiglitazone and pioglitazone DDIs. Gemfibrozil and cyclosporine inhibition data obtained in human embryonic kidney cells expressing OATP1B1 and hepatic input concentration ([I]in) were used for qualitative zoning of 14 transporter-mediated DDIs. Results Incorporation of time-dependent inhibition by gemfibrozil glucuronide showed no significant improvement in the prediction, as CYP2C8 contributed <65% to the overall elimination of the victim drugs investigated. Qualitative zoning of OATP1B1 DDIs resulted in no false negative predictions; yet the magnitude of observed interactions was significantly over-predicted. Conclusions Time-dependent inhibition by gemfibrozil glucuronide is only important for victim drugs eliminated predominantly (>80%) via CYP2C8. Qualitative zoning of OATP1B1 inhibitors based on [I]in/K _i is valid in drug screening to avoid false negatives. Refinement of the transporter model by incorporating the fraction of drug transported by a particular transporter is recommended.     

Contribution of organic anion transporting polypeptide (OATP) 1B1 and OATP1B3 to hepatic uptake of nateglinide, and the prediction of drug-drug interactions via these transporters

Objectives We have investigated the contributions of organic anion transporting polypeptide (OATP) 1B1 and OATP1B3 to the hepatic uptake of nateglinide, and the possibility of drug–drug interactions via these transporters. Methods Uptake studies using transporter‐expressing HEK293 cells and cryopreserved human hepatocytes were performed to examine the contributions of each transporter. Inhibition studies using cryopreserved human hepatocytes were performed to examine the possibility of drug–drug interactions. Key findings The rate of saturable hepatic uptake of nateglinide using human hepatocytes was 47.6%. A certain increase in uptake was observed in the examination using transporter‐expressing HEK293 cells, indicating contributions of OATP1B1 and OATP1B3 to hepatic nateglinide uptake. The 50% inhibitory concentration (IC50) values of nateglinide using cryopreserved human hepatocytes for uptake of estrone 3‐sulfate (substrate of OATP1B1), and cholecystokinin octapeptide (substrate of OATP1B3) were 168 and 17.4 µmol/l, respectively. Moreover, ciclosporin inhibited saturable hepatic uptake of nateglinide with an IC50 value of 6.05 µmol/l. The calculated 1 + I_in,max,u/IC50 values for inhibition of OATP1B1 and OATP1B3 by nateglinide, and the inhibition of saturable uptake of nateglinide by ciclosporin, were all close to 1, indicating a low clinical risk of drug–drug interaction with nateglinide taken up via OATP1B1 and OATP1B3. Conclusions OATP1B1 and OATP1B3 may have contributed to the hepatic uptake of nateglinide, but the possibility of drug–drug interactions appeared to be low.     

Organic anion-transporting polypeptide (OATP) 2B1 contributes to the cellular uptake of theaflavin

Organic anion-transporting polypeptide (OATP) 2B1 has been reported in the apical membranes of the human small intestinal epithelium, where it contributes to the intestinal absorption of pharmacologically active drugs. To investigate the potential for OATP2B1-mediated drug–food interactions, the effects of several polyphenolic compounds on OATP2B1-mediated estrone-3-sulfate (E3S) transport were studied by using OATP2B1-expressing HEK293 cells. Our results showed that some compounds, especially theaflavin, were strong inhibitors of OATP2B1-mediated E3S uptake. Theaflavin showed a significantly higher uptake into the OATP2B1-expressing HEK293 cells than the control cells. The concentration dependence of the uptake of theaflavin was determined over a range of concentrations (0.5–100 μM) and the kinetic parameters (K_m and V_max) of theaflavin uptake were found to be 5.12 ± 0.67 μM and 41.6 ± 1.3 pmol/mg protein/min, respectively. The OATP2B1-mediated theaflavin uptake was inhibited by known OATP2B1 substrates such as E3S, bromsulphthalein (BSP), dehydroepiandrosterone-3-sulfate (DHEAS), and fluvastatin. Our results indicate that theaflavin is a novel substrate of OATP2B1. The results of this study might be helpful to predict the potential OATP2B1-mediated drug–theaflavin interactions and to avoid undesirable clinical consequences.     

PBPK modeling of irbesartan: incorporation of hepatic uptake

Physiological based pharmacokinetic (PBPK) modeling is now commonly used in drug development to integrate human or animal physiological data in order to predict pharmacokinetic profiles. The aim of this work was to construct and refine a PBPK model of irbesartan taking into account its active uptake via OATP1B1/B3 in order to predict more accurately its pharmacokinetic profile using Simcyp^®. The activity and expression of the human hepatocyte transporters OATP1B1 and OATP1B3 were studied. The relative activity factors (RAFs) for OATP1B1 and OATP1B3 transporters were calculated from intrinsic clearances obtained by concentration dependent uptake experiments in human hepatocytes and HEK overexpressing cells: RAF_1B1 using estrone‐3‐sulfate and pitavastatine clearances, and RAF_1B3 using cholecystokinine octapeptide (CCK‐8) clearances. The relative expression factor (REF) was calculated by comparing immunoblotting of hepatocytes (REF_HH) or tissues (REF_tissue) with those of overexpressing HEK cells for each transporter. These scaling factors were applied in a PBPK model of irbesartan using the Simcyp® simulator. Pharmacokinetic simulation using REF_HH (1.82 for OATP1B1, 8.03 for OATP1B3) as an extrapolation factor was the closest to the human clinical pharmacokinetic profile of irbesartan. These investigations show the importance of integrating the contribution of the active uptake of a drug in the liver to improve PBPK modeling. Copyright © 2015 John Wiley & Sons, Ltd.     

Current understanding of hepatic and intestinal OATP-mediated drug-drug interactions

At present, many patients are medicated with various drugs, which are, at the same time, associated with an increased risk of drug-drug interactions (DDIs). Detailed analysis of mechanisms underlying DDIs is the basis of a better prediction of adverse drug events caused by drug interactions. In the last few decades, an involvement of transporters in such processes has been more and more recognized. Indeed, uptake transporters belonging to the organic anion-transporting polypeptide (OATP) family have been shown to interact with a variety of drugs in clinical use. Particularly, the subfamily of OATP1B transporters has been extensively studied, identifying several clinical significant DDIs based on those hepatic uptake transporters. By contrast, the role of OATP2B1 in this context is rather underestimated. Therefore, in addition to known interactions based on OATP1B transporters, we have focused on DDIs probably based on OATP2B1 inhibition in the liver and those possibly owing to the inhibition of OATP2B1-mediated drug absorption in the intestine.     

Physiologically Based Modeling of Pravastatin Transporter-Mediated Hepatobiliary Disposition and Drug-Drug Interactions

Purpose

To develop physiologically based pharmacokinetic (PBPK) model to predict the pharmacokinetics and drug-drug interactions (DDI) of pravastatin, using the in vitro transport parameters.

Methods

In vitro hepatic sinusoidal active uptake, passive diffusion and canalicular efflux intrinsic clearance values were determined using sandwich-culture human hepatocytes (SCHH) model. PBPK modeling and simulations were implemented in Simcyp (Sheffield, UK). DDI with OATP1B1 inhibitors, cyclosporine, gemfibrozil and rifampin, was also simulated using inhibition constant (Ki) values.

Results

SCHH studies suggested active uptake, passive diffusion and efflux intrinsic clearance values of 1.9, 0.5 and 1.2?μL/min/10⁶cells, respectively, for pravastatin. PBPK model developed, using transport kinetics and scaling factors, adequately described pravastatin oral plasma concentration-time profiles at different doses (within 20% error). Model based prediction of DDIs with gemfibrozil and rifampin was similar to that observed. However, pravastatin-cyclosporine DDI was underpredicted (AUC ratio 4.4 Vs ~10). Static (R-value) model predicted higher magnitude of DDI compared to the AUC ratio predicted by the PBPK modeling.

Conclusions

PBPK model of pravastatin, based on in vitro transport parameters and scaling factors, was developed. The approach described can be used to predict the pharmacokinetics and DDIs associated with hepatic uptake transporters.