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Sinusoidal Uptake Determines the Hepatic Clearance of Pevonedistat (TAK-924) as Explained by Extended Clearance Model

Philip Sandoval, Bei-Ching Chuang, Lawrence Cohen, Tomoki Yoneyama, Sandeepraj Pusalkar, Robert W. Yucha, Swapan K Chowdhury and Paresh P. Chothe
Drug Metabolism and Disposition July 2022, 50 (7) 980-988; DOI: https://doi.org/10.1124/dmd.122.000836

Abstract

Quantitative assessment of hepatic clearance (CLH) of drugs is critical to accurately predict human dose and drug-drug interaction (DDI) liabilities. This is challenging for drugs that involve complex transporter-enzyme interplay. In this study, we demonstrate this interplay in the CLH and DDI effect in the presence of CYP3A4 perpetrator for pevonedistat using both the conventional clearance model (CCM) and the extended clearance model (ECM). In vitro metabolism and hepatocyte uptake data showed that pevonedistat is actively transported into the liver via multiple uptake transporters and metabolized predominantly by CYP3A4 (88%). The active uptake clearance (CLact,inf) and passive diffusion clearance (CLdiff,inf) were 21 and 8.7 ml/min/kg, respectively. The CLact,inf was underpredicted as Empirical Scaling Factor of 13 was needed to recover the in vivo plasma clearance (CLplasma). Both CCM and ECM predicted CLplasma of pevonedistat reasonably well (predicted CLplasma of 30.8 (CCM) and 32.1 (ECM) versus observed CLplasma of 32.2 ml/min/kg). However, both systemic and liver exposures in the presence of itraconazole were well predicted by ECM but not by CCM (predicted pevonedistat plasma area under the concentration-time curve ratio (AUCR) 2.73 (CCM) and 1.23 (ECM))., The ECM prediction is in accordance with the observed clinical DDI data (observed plasma AUCR of 1.14) that showed CYP3A4 inhibition did not alter pevonedistat exposure systemically, although ECM predicted liver AUCR of 2.85. Collectively, these data indicated that the hepatic uptake is the rate-determining step in the CLH of pevonedistat and are consistent with the lack of systemic clinical DDI with itraconazole.

SIGNIFICANCE STATEMENT In this study, we successfully demonstrated that the hepatic uptake is the rate-determining step in the CLH of pevonedistat. Both the conventional and extended clearance models predict CLplasma of pevonedistat well however, only the ECM accurately predicted DDI effect in the presence of itraconazole, thus providing further evidence for the lack of DDI with CYP3A4 perpetrators for drugs that involve complex transporter-enzyme interplay as there are currently not many examples in the literature except prototypical OATP substrate drugs.

Introduction

Many drugs are cleared via hepatic disposition involving phase I and phase II metabolic pathways; therefore, liver microsomes, liver S9 fractions, and primary hepatocytes are widely considered in measuring intrinsic metabolic clearance to predict human hepatic clearance of drugs. However, the liver is a complex organ involving interplay between different processes such as sinusoidal uptake, sinusoidal efflux, metabolism and biliary secretion to drive overall disposition of drugs. Thus, understanding of these individual processes is not only important to accurately predict hepatic clearance (CLH) of drugs but also to reliably assess drug-drug interaction (DDI) liabilities. With recent advances in the drug transporter field, it has become apparent that uptake transporters at the sinusoidal membrane of hepatocytes play an important role in the hepatic clearance of drugs (Giacomini et al., 2010; Hillgren et al., 2013). Of note, organic anion transporting polypeptides (OATPs), organic anion transporter 2 (OAT2) and organic cation transporter 1 (OCT1) are shown to play an important role in the hepatic clearance of their substrate drugs, such as atorvastatin (Maeda et al., 2011), fluvastatin (Watanabe et al., 2010), cerivastatin (Shitara, 2011), repaglinide (Varma et al., 2013), bosentan (Sato et al., 2018) (OATP substrates), tolbutamide (OAT2 substrate) (Bi et al., 2018b), warfarin (OAT2 substrate) (Bi et al., 2018a) and GNE1 (OCT1 substrate) (Fan et al., 2016).

Generally, hepatic clearance of compounds that are highly permeable and predominantly cleared via metabolism by enzymes is estimated by the conventional clearance model (CCM) (Pang et al., 2019). However, when a compound is a dual substrate of metabolic enzymes and uptake transporters, the extended clearance model (ECM) has been proven to be quite useful in predicting hepatic clearance as this model accounts for all the individual processes such as uptake clearance, metabolic clearance and biliary clearance that can be involved in the hepatic clearance of a compound (Fujino et al., 2018; Patilea-Vrana and Unadkat, 2018) (eq. 1). The ECM has been shown to be a useful tool in identifying the rate-determining step (RDS) in the systemic clearance of a drug and in predicting DDI liabilities (transport, metabolism or both) (Kunze et al., 2015; Liang and Lai, 2021). Recent clinical data have demonstrated OATP-mediated uptake as the RDS in the hepatic CL of many drugs that are dual substrates of CYP3A4 and OATPs, including atorvastatin, cerivastatin, repaglinide, and bosentan. The area under the curve (AUC) of atorvastatin was increased 12-fold when given with rifampicin (an OATP inhibitor), but it did not change when co-administered with itraconazole (CYP3A4 inhibitor) (Maeda et al., 2011). Similarly, rifampicin increased the AUC of bosentan (3.2-fold), repaglinide (1.9-fold), and simeprevir (7.2-fold), but itraconazole had minimal or no effect on the AUC of these drugs (Yoshikado et al., 2017). This clinical evidence clearly signifies that OATP inhibition, not CYP3A inhibition, has direct influence on the systemic CL of drugs that involve enzyme-transporter interplay where hepatic uptake becomes an RDS.

Pevonedistat is a first-in-class, small molecule inhibitor of neural precursor cell expressed, developmentally down-regulated 8-activating enzyme and currently under investigation for the treatment of malignancies (Bhatia et al., 2016; Swords et al., 2018; Lockhart et al., 2019). The chemical structure of pevonedistat is provided in Fig. 1. Based on available in vitro and in vivo studies, the hepatic metabolism via the CYP3A4 pathway appears to be the primary route of its elimination (Zhou et al., 2021a). Given the major role of CYP3A4 in the metabolic CL of pevonedistat, a dedicated clinical DDI study was conducted with a moderate and a strong CYP3A4 inhibitor, fluconazole and itraconazole, respectively (Faessel et al., 2019). Pevonedistat was administered at 8, 15, and 20 mg/m2 intravenously in the absence (Day 1) or presence (Day 8) of itraconazole at 200 mg oral single dose (for 7 days). The results from this study indicated that there was no clinically relevant impact of CYP3A4 inhibition (either by itraconazole or fluconazole) on the plasma exposure of pevonedistat as the increase in the dose-normalized AUC was only 1.11-fold and 1.14-fold in the presence of fluconazole and itraconazole, respectively (Faessel et al., 2019). The lack of clinically relevant DDI in plasma in the presence of itraconazole suggested that the hepatic uptake may be the RDS in the hepatic CL of pevonedistat. Therefore, the objective of this study was 3-fold: 1) to comprehensively characterize the hepatic uptake of pevonedistat using cryopreserved primary human hepatocytes, 2) evaluate both the conventional and static extended clearance models to predict the hepatic CL of pevonedistat, and 3) evaluate the application of both these models in predicting DDI with CYP3A4 inhibition.

Fig. 1.
Fig. 1.

The chemical structure of pevonedistat.

Materials and Methods

Transporter-qualified cryopreserved human hepatocyte lots (1964, 8280, 8317, 8339, and 8350) were purchased from ThermoFisher Scientific (Waltham, MA USA) (Supplemental Table 1). Human cDNA-expressed rCYPs (Supersomes) were purchased from Corning (Woburn, MA, USA). Heart microsomes (single female donor), lung microsomes (smokers and non-smokers; pooled from 4 donors each [male and female]), and pooled liver microsomes (pooled from 200 donors [male and female]) were purchased from Sekisui-XenoTech (Lenexa, KS, USA). Williams’ E medium, cryopreserved hepatocyte recovery medium, hepatocyte maintenance, and plating supplement pack were purchased from ThermoFisher (Waltham, MA USA). Atorvastatin, rifamycin SV (RFV), cyclosporin A, verapamil, ketoprofen and S-(4-Nitrobenzyl)-6-thioinosine (NBMPR), sumatriptan, taurocholic acid (TCA), and uridine were obtained from Sigma-Aldrich(St. Louis, MO USA). [3H]uridine was purchased from Perkin-Elmer (Hopkinton, MA USA). [3H]atorvastatin, [3H]TCA, [3H]sumatriptan, and [14C]tolbutamide were purchased from American Radiolabeled Chemicals, Inc. (St. Louis, MO USA). Pevonedistat and [14C]pevonedistat were prepared and supplied by Millennium Pharmaceuticals, Inc. (Cambridge, MA, USA), a wholly owned subsidiary of Takeda Pharmaceutical Company Limited. All organic solvents were of the highest quality and procured from ThermoFisher (Waltham, MA USA) and Sigma-Aldrich (St. Louis, MO USA).

In Vitro Metabolism Studies

Metabolic Stability Assessment Using Human Liver Microsomes

Pevonedistat (0.1 μM) was incubated with human heart, liver, and lung (smokers and nonsmokers) microsomes (0.5 mg/ml). The incubations were conducted in triplicate in 0.1M potassium phosphate buffer supplemented with or without 2 mM of NADPH and 3 mM of MgCl2, pH 7.4, at 37°C, over 0, 3, 7, 12, 20, and 30 minutes. The reactions were terminated by addition of 90 μl of 0.1 μM of d8-pevonedistat (internal standard) in acetonitrile. The plates were kept in a freezer for a minimum of 30 minutes for maximal protein precipitation and then centrifuged at 3100 × g at 2°C for 10 minutes. A 75 μl aliquot of the supernatant was then further diluted with 150 μl of water prior to analysis by liquid chromatography and tandem mass spectrometry (LC/MS/MS). The disappearance of pevonedistat over time was monitored by LC/MS/MS.

In vitro Cytochrome P-450 Mapping and Reaction Phenotyping

To determine the CL of pevonedistat in recombinant CYPs, pevonedistat (0.1 μM) was incubated with recombinant CYP1A1, 1A2, 2B6, 2C8, 2C9, 2C19, 2D6, 2J2, 3A4, and 3A5 (20 pmol/ml). The total protein concentration was adjusted to 0.5 mg/ml with appropriate control Supersomes with either P450 oxidoreductase or with both P450 oxidoreductase and cytochrome b5. The reactions were performed using the same procedure as described above for microsomes.

Uptake Assay in Plated Hepatocytes

Transporter-qualified cryopreserved human hepatocytes (Lots 1964, 8280, 8317, 8339, and 8350) were obtained from ThermoFisher Scientific (Waltham, MA, USA). Cryopreserved hepatocytes were thawed using cryopreserved hepatocyte recovery medium (Life Technologies Corporation) and centrifuged at 100×g for 10 minutes at room temperature. The cell pellets were suspended in William’s Medium E (Invitrogen [Carlsbad, CA, USA]) containing 0.1 mM of nonessential amino acids, 2 mM of L-glutamine, 4.5-g/L of glucose, 10% fetal bovine serum (FBS), insulin-transferrin-selenium (1×) (Gibco), 0.1 μM of dexamethasone, and 100 unit/ml of penicillin/streptomycin. The viability of the hepatocytes was determined by a CelloMeter (Nexcelom Bioscience) (Lawrence, MA, USA) and an acridine orange/propidium iodide (AO/PI) staining solution (Nexcelom Bioscience). The hepatocytes were seeded at a density of 0.15 to 0.2 million cells per well onto 48-well plates precoated with Collagen I (Corning Life Sciences, Corning, NY, USA). The hepatocytes were allowed to attach at 37°C for approximately 1 hour with 95% air and 5% CO2, and the medium was replaced by William’s Medium E containing 0.1 mM of nonessential amino acids, 2 mM of L-glutamine, 4.5 g/L of glucose, insulin-transferrin-selenium (1×), 0.1-μM dexamethasone, and 100 unit/mL of penicillin/streptomycin. The hepatocytes were further incubated at 37°C for an additional 3 to 4 hours before use in the assay.

To initiate the uptake assay, hepatocytes were incubated with warm Krebs-Henseleit (KH) buffer for 10 minutes at 37°C. [14C]pevonedistat was then added to hepatocytes at 1 µM. The total uptake of pevonedistat into hepatocytes was measured for 1, 2, 3, 5, 7, and 10 minutes at 37°C. Similarly, the uptake via passive diffusion into hepatocytes was measured at 1 µM for 1, 2, 3, 5, 7, and 10 minutes at 4°C. For inhibition studies, hepatocytes were pre-incubated with an inhibitor for 15 minutes and then co-incubated with an inhibitor and [14C]pevonedistat or a probe substrate for 5 minutes in KHB buffer at 37°C. Rifamycin SV (20 µM), cyclosporine A (CsA, 20 µM), verapamil (300 µM), ketoprofen (300 µM), and nitrobenzylthioinosine (NBMPR, 10 µM) were used as inhibitors for organic anion-transporting polypeptides (OATPs), Na+-taurocholate co-transporting polypeptide (NTCP) (in addition to OATPs), organic cation transporter (OCT) 1 (also inhibits P-gp), organic anion transporter (OAT) 2, and equilibrative nucleoside transporter (ENT) 1, respectively. We also included rifamycin SV at 1 mM as a pan-inhibitor, which has been shown to inhibit all six major uptake transporters (OATP1B1, OATP1B3, OATP2B1, NTCP, OCT1, and OAT2) (Chothe et al., 2018; Bi et al., 2019). For uptake kinetic experiments, hepatocytes were incubated with pevonedistat at various concentrations (0.27 to 200 µM, [14C]pevonedistat + cold pevonedistat) for 5 minutes. To investigate the effect of human serum albumin (HSA) on pevonedistat uptake, hepatocytes were incubated with pevonedistat (0.45 µM) in KHB buffer and Na+-free buffer (with and without cyclosporine A) containing 0.5% HSA for 3 minutes. At the end of the uptake period, hepatocytes were washed 3 times with ice-cold KHB buffer. The cells were lysed with Triton X-100 (Sigma-Aldrich Company, LLC, St Louis, MO, USA) (0.5%, v:v) in PBS. The samples of radiolabeled substrates were placed into a 96-well Wallac Isoplate (PerkinElmer Life Sciences [Waltham, MA, USA]) and mixed with Ultima-Flo M liquid scintillation cocktail (PerkinElmer Life Sciences [Waltham, MA, USA]). The radioactivity in the samples was measured with a 2450 MicroBeta2 TriLux microplate scintillation and luminescence counter (PerkinElmer Life Sciences [Waltham, MA, USA]). Radioactivity of the dosing solution was used to calculate the initial donor concentration of the substrate. Non-radiolabeled substrates were quantified by liquid chromatography mass spectrometry. The total protein concentration in cell lysates were quantified using the Pierce bicinchoninic acid protein assay (ThermoFisher Scientific, Inc. [Rockford, IL, USA]), with bovine serum albumin (BSA) as the reference standard. The cellular accumulation of pevonedistat and other transporter probe substrates were normalized to the total protein concentration. All experiments were conducted in triplicate (n = 3).

Measurement of Protein Abundance of Major Drug Transporter Proteins in Human Hepatocytes by Quantitative Proteomics Using nano LC-MS/MS

The absolute protein abundance of major liver drug transporters in human hepatocyte lots 8317, 8339, and 8350 was measured by targeted proteomics approach using nano LC-MS/MS by Dr. Philip Smith at the University of North Carolina, Chapel Hill. The procedure of membrane preparation, trypsin digestion, and bioanalysis by LC-MS/MS was used as described previously (Khatri et al., 2019; Chothe et al., 2021).

Data Analysis

The time course uptake data of pevonedistat at 37°C and 4°C was fitted with linear regression in GraphPad Prism 8 software (Graphpad Corp, La Jolla, CA, USA) to determine slopes. The uptake inhibition data were analyzed by ordinary one-way ANOVA using Tukey’s multiple comparisons test. The active uptake kinetic parameters (Km and Vmax) were determined by using Michael Mentalis equation in GraphPad Prism 8 software as described in eq. 1 below. Embedded Image where V is the uptake rate, Vmax is the maximum transport velocity, Km is the affinity of a substrate, and S is the substrate concentration. The passive diffusion clearance (CLdiff,inf) was determined from the mean of passive diffusion clearance at each concentration of pevonedistat at 4°C.

The hepatic clearance was estimated by the well-stirred clearance model using the following equation: Embedded Image where CLH is plasma-based hepatic clearance, QH is liver blood flow (86 L/h), fu is fraction unbound in plasma, Rb is blood to plasma ratio and CLint is intrinsic clearance. The CLH of pevonedistat in the presence of itraconazole was determined by using the fraction inhibited by itraconazole of CYP3A4-mediated clearance of pevonedistat (0.88).

Intrinsic hepatic clearance of pevonedistat was estimated using the conventional clearance model (CCM) and extended clearance model (ECM) as described by the following equations, respectively: Embedded Image Embedded Image where CLint is intrinsic clearance, CLint,met is intrinsic metabolic clearance, CLint,bile is intrinsic biliary clearance. CLact,inf and CLdiff,inf are the uptake clearances via active and passive diffusion process, respectively, and CLact,eff and CLdiff,eff are the efflux via active and passive diffusion process, respectively. CLact,inf is estimated by Vmax/Km. Empirical scaling factors (ESF) of 4 and 13 were used to extrapolate in vitro CLint in the CCM and ECM, respectively, to fully recover the vivo plasma clearance of pevonedistat in respective clearance models.

The change in the plasma AUC of pevonedistat in the presence of itraconazole was predicted using following equation: Embedded Image where AUCR is the area under the concentration-time curve ratio of pevonedistat plasma AUC in the absence and presence of itraconazole, CLH is plasma-based hepatic clearance, CLrenal is the renal clearance, and CLH,itraconazole is the plasma-based hepatic clearance of pevonedistat in the presence of itraconazole.

The liver AUC of pevonedistat in the absence and presence of itraconazole was predicted by eqs. 6 and 7, respectively: Embedded Image Embedded Image where AUCRCCM and AUCRECM is the ratio of pevonedistat liver AUC in the absence and presence of itraconazole, using the CCM and ECM, respectively, fu is plasma unbound fraction, Qh is liver blood flow, Rb is blood to plasma partitioning ratio, CLact,inf is active uptake clearance, CLdiff,inf is passive diffusion clearance, CLint,met and CLint,met,itraconazole is metabolic CL in the absence and presence of itraconazole, CLbile is biliary clearance, and CLbile is renal clearance.

For scaling, metabolic CL of pevonedistat using HLMs following physiologic scalars were used: 40 mg microsomal protein per gram of liver, 21.4 g of liver per kg of body weight and 70 kg of bodyweight: and for the scaling of uptake, CL using human hepatocytes following physiologic scalars were used: 0.657 mg of protein per million cells (Sohlenius-Sternbeck, 2006), 139 million cells per gram of liver, 21.4 g of liver per kg of body weight, and 70 kg of body weight.

Results

In vitro Metabolic Stability of Pevonedistat using HLMs

The in vitro intrinsic metabolic CL of pevonedistat was obtained using HLMs. The CLint value of pevonedistat was 51.1 µl/min/mg protein at concentration of 0.1 µM. The measured non-specific binding (fu,mic) of pevonedistat at the protein concentration of 0.5 mg/ml was 0.49. In the same study, the depletion of pevonedistat (0.1 µM) was inhibited by 87.7% following ketoconazole treatment (1 µM). These results suggested that the contribution of CYP3A4 to the CYP-mediated metabolism of pevonedistat is 88% in vitro.

In vitro Cytochrome P-450 Mapping and Reaction Phenotyping of Pevonedistat

The CYP reaction phenotyping of pevonedistat (0.1 µM) was conducted using recombinantly expressed CYP enzymes as described under experimental section. This assessment involved the monitoring of the depletion of pevonedistat over the period of 30 minutes. In addition to hepatic enzymes (CYP1A2, 2A6, 2B6, 2C8, 2C9, 2C19, 2D6, 2E1, 3A4, 3A5, 4F2, 4F3, and 4F12), the role of extrahepatic enzymes and non-cytochrome P450 enzymes was also evaluated. CYP3A4 was found to be the primary enzyme responsible for >90% of the hepatic metabolism of pevonedistat, consistent with the percent inhibition in the presence of ketoconazole in HLM. The data also indicated that, in addition to CYP3A4/5, pevonedistat is metabolized by CYP1A1, 2J2, and 2C8, and to a lesser extent by CYP1A2, 2B6, 2C9, 2C19, and 2D6. The other CYPs, CYP2A6, 2E1, 4F3A, 4F3B, and 4F12, did not contribute to the CL of pevonedistat.

To assess the relative contribution of extrahepatic enzymes (CYP1A1 and CYP2J2) to metabolism of pevonedistat, a preliminary scaling of these recombinant CYP data together with respective tissue CYP abundance values was conducted. The results showed negligible whole-organ CLint in the heart (CYP2J2) and lung (CYP1A1) tissue in comparison with liver (Table 1).

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TABLE 1

Scaling of CLint of pevonedistat from recombinent CYPs

Based on the in vivo radiolabeled absorption, distribution, metabolism, and excretion /mass balance study in cancer patients, the unchanged pevonedistat accounted for approximately 5% and 17% of the administered dose in urine and feces, respectively, following infusion of 25 mg/m2 of [14C]pevonedistat, indicating minimal contribution from renal and biliary elimination, thus supporting metabolic clearance as the predominant route of elimination of pevonedistat. This was also well supported by in vitro sandwich cultured human hepatocytes in which biliary excretion of pevonedistat was found to be low (data not shown) Pevonedistat CLIV,plasma and CLrenal were estimated to be 32.2 L/h and 0.8 L/h, respectively (Zhou et al., 2021a). Thus, based on the in vitro and in vivo metabolism and, mass balance data pevonedistat clearance appeared to be predominantly mediated via metabolism by CYP3A.

Determination of Pevonedistat Uptake in Human Hepatocytes

The uptake of pevonedistat was analyzed at 1 µM at 37°C and 4°C in plated human hepatocytes for two donors, 4317 and 8280, as described under experimental section. The uptake was linear up to 5 minutes and 10 minutes in lot 8317 and lot 8280, respectively. The uptake of pevonedistat was found to be 2- to 3.5-fold higher at 37°C compared with the uptake at 4°C (Fig. 2). The uptake clearance (CLinf) was determined from the slopes of the initial uptake rate-time profile of pevonedistat at 37°C and 4°C for both the lots. The CLinf was 13.98 and 3.98 µl/min/mg protein at 37°C and 4°C, respectively, for the lot 4317 and 16.85 and 8.64 µl/min/mg protein at 37°C and 4°C, respectively, for the lot 8280.

Fig. 2.
Fig. 2.

Time course of pevonedistat uptake in plated human hepatocytes. The uptake of [14C]pevonedistat (1µM) was measured at 37°C and 4°C for 1, 2, 3, 5, 7, and 10 minutes in plated human hepatocyte (A) lot 8317 and (B) 8280. The experiment was done in triplicates (n = 3).

Assessment of Transporter/s Involved in the Hepatic Uptake of Pevonedistat using Pre-Validated Reference Inhibitors

The time course study indicated that pevonedistat is actively transported into human hepatocytes; therefore, we further investigated its uptake to delineate the potential transporter/s involved using known transporter inhibitors in the three lots of human hepatocytes, 4317, 8339, and 8350. We first validated all the reference inhibitors for their selectivity toward respective transporters using transporter-specific probe substrates. We used atorvastatin for OATP1B1/OATP1B3/OATP2B1, taurocholic acid for NTCP, sumatriptan for OCT1, tolbutamide for OAT2, and uridine for ENT1 (Supplemental Fig. 1). As expected, rifamycin SV (20 µM) inhibited atorvastatin uptake by 59% to 94%, CsA (20 µM) inhibited taurocholic acid (TCA) uptake by 80% to 100%, verapamil (300 µM) inhibited sumatriptan uptake by 73% to 83%, ketoprofen (300 µM) inhibited tolbutamide uptake by 85% to 100%, and NBMPR (10 µM) inhibited uridine uptake by 80% to 94% in all three lots of hepatocytes. Rifamycin SV at 1 mM (pan-uptake transporter inhibitor) completely inhibited OATP-mediated atorvastatin uptake (100%), NTCP-mediated TCA uptake (100%), OCT1-mediated sumatriptan uptake (93% to 100%), OAT2-mediated tolbutamide uptake (51% to 100%), and ENT1-mediated uridine uptake (99% to 100%) in all three lots of human hepatocytes.

No significant inhibition of pevonedistat active uptake was observed in the presence of the reference inhibitors; rifamycin SV (20 µM), CsA (20 µM), verapamil (300 µM), ketoprofen (300 µM), and NBMBR (10 µM) in lots 8317, and 8350 while the active uptake of pevonedistat was inhibited 44% by rifamycin SV (20 µM), 43% by CsA (20 µM), 26% by verapamil (300 µM), 37% by ketoprofen (300 µM), and 35% by NBMPR (10 µM) in lot 8339. Additionally, 1 mM of rifamycin SV (a pan-inhibitor) inhibited pevonedistat uptake by 78% and 34% in lots 8339 and 8350, respectively. No inhibition of pevonedistat uptake was observed by 1 mM of rifamycin SV in lot 8317 (Figure 3 and Table 2).

Fig. 3.
Fig. 3.

Inhibition of pevonedistat uptake in plated human hepatocytes. The uptake of [14C]pevonedistat (3µM) was measured at 37°C in the absence and presence of rifamycin SV (20 µM), CsA (20 µM), verapamil (300 µM), ketoprofen (300 µM), NBMPR (10 µM), and rifamycin SV at 1 mM for 5 minutes in plated human hepatocyte lots (A) 8317, (B) 8339, and (C) 8350. The uptake of [14C]pevonedistat (3µM) was also measured at 37°C in the presence of choline buffer (Na+) and at 4°C in all 3 lots of human hepatocytes. The experiment was done in triplicates (n = 3). Statistical significance * p < 0.05 and ** p < 0.01.

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TABLE 2

Summary of pevonedistat uptake in plated human hepatocytes

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TABLE 3

The protein abundance of drug transporters in human hepatocytes as measured by targeted proteomics

Analysis of HSA Effect on Pevonedistat Uptake in Human Hepatocytes

Recent literature has indicated that the addition of HSA in in vitro transporter studies can improve uptake of drugs that have high nonspecific binding (Miyauchi et al., 2018). Therefore, we examined the effect of 0.5% HSA on pevonedistat in human hepatocytes. The uptake of pevonedistat was measured in KHB buffer and Na+-free KHB buffer containing 0.5% HSA in the absence and presence of OATP inhibitor cyclosporine A at 37°C and 4°C in human hepatocytes lots 8280 and 8317. Pevonedistat showed active uptake; however, cyclosporine A did not inhibit pevonedistat uptake in the presence of 0.5% HSA (Fig. 4 and Table 4).

Fig. 4.
Fig. 4.

Effect of HSA on the uptake of pevonedistat in plated human hepatocytes. The uptake of [14C]pevonedistat (0.45µM) was measured at 37°C and 4°C with and without CsA (10 µM) in KHB buffer and choline buffer containing 0.5% HSA in plated human hepatocyte lots (A) 8317 and (B) 8280.

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TABLE 4

Uptake rates of pevonedistat in the presence of 0.5% HSA in plated human hepatocytes

Measurement of Uptake Kinetics Parameters of Pevonedistat Uptake in Human Hepatocytes

To investigate the concentration dependence and determine the kinetic parameters of pevonedistat uptake into human hepatocytes, the uptake of pevonedistat within the range of 0.1 to 200 µM was determined at 4°C and 37°C in hepatocyte lots 8280 and 8317. The uptake of pevonedistat was concentration-dependent (Fig. 5). The Km and Vmax for lot 8280 were 179.3±35.74 µM and 4039±446.4 pmol/min/mg protein, respectively, and the Km and Vmax for lot 8317 were 186.5±37.56 µM and 3664±414.7 pmol/min/mg protein, respectively. These parameters were used to determine the CLact,inf of pevonedistat in each lot. The mean of CLact,inf was then used for in vivo extrapolation. Similarly, the mean of CLdiff,inf at each concentration of pevonedistat was determined and used a CLdiff,inf for in vivo extrapolation (Table 5).

Fig. 5.
Fig. 5.

Uptake kinetics of pevonedistat in plated human hepatocytes. The uptake of [14C]pevonedistat was measured at 37°C and 4°C in KHB buffer at different concentrations ranging from 0.27 to 200 µM in plated human hepatocyte lots (A) 8317 and (B) 8280.

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TABLE 5

Input parameters used in predicting hepatic clearance of pevonedistat using ECM

Application of ECM to Predict Hepatic Clearance of Pevonedistat and the DDI Effect in the Presence of Itraconazole on Pevonedistat Plasma Exposure

The CLH of pevonedistat was determined by both the CCM and ECM using eqs. 3–4. The predicted CLplasma was found to be 30.8 L/h and 32.1 L/h by the CCM and ECM, respectively (Table 5). In the ECM model, the CLactive of pevonedistat was scaled using ESF of 13 as it was needed to recover the observed CLplasma of pevonedistat as indicated in Supplemental Fig. 2. Further, we used these models to predict the DDI effect on pevonedistat PK in the presence of itraconazole. The ratio of the plasma and liver AUC of pevonedistat in the absence and presence of itraconazole was predicted using eqs. 5–7. The data are shown in Table 5.

Discussion

Understanding of hepatic disposition of drugs is essential in accurate prediction of hepatic CL, human PK/dose projection, and DDI liabilities. However, this has become challenging due to dynamic interplay between different processes, such as sinusoidal uptake and efflux, metabolism and biliary excretion. Therefore, use of a physiologically relevant model which accounts for all these processes is crucial to accurately predict CLH and to identify RDS for assessing DDI liabilities during drug development. In such cases, the ECM, which accounts for enzyme-transporter interplay in the hepatic disposition, has been widely used (Kimoto et al., 2018). In this study, we evaluated the ECM in predicting the CLH of pevonedistat and DDI effect in the presence of CYP3A perpetrator, itraconazole.

First, we characterized the metabolism of pevonedistat using HLMs and CYP phenotyping. These data revealed the major role of CYP3A (fm = 0.88) in pevonedistat metabolism. This was further confirmed by the in vivo metabolism and mass balance studies (Zhou et al., 2021a) in which approximately 74% of the administered dose cleared via hepatic oxidative metabolism. Based on this evidence, clinical DDI was anticipated with itraconazole, a potent CYP3A4 inhibitor; interestingly however, inhibition of CYP3A4 did not result in a meaningful increase in the systemic exposure of pevonedistat. Previously, a similar phenomenon has been shown for OATP and CYP3A4 substrate drugs where OATP-mediated hepatic uptake is the RDS in their CLH. Therefore, to explain the reason for the lack of DDI in the presence of itraconazole, the uptake of pevonedistat was investigated at 37°C, 4°C and in the presence of selective inhibitors of major liver uptake transporters and a pan-inhibitor (1 mM of rifamycin SV) (Chothe et al., 2018). The uptake of pevonedistat was temperature-dependent and sodium-independent. Interestingly, no significant inhibition of pevonedistat uptake was observed in the presence of reference inhibitors in lots 8317 and 8350; however, rifamycin SV (1 mM) inhibited the uptake by 34% in lot 8350, whereas the uptake was inhibited in the range of 26–44% by OCT1, OATP, OAT2, and ENT1 inhibitors and 78% by 1 mM of rifamycin SV in lot 8339. These data indicated that lot 8339 was the most sensitive to inhibitors. The reason for the lot-to-lot variability in the inhibition of pevonedistat uptake is attributed to different expression levels of drug transporter proteins. The protein abundance data indicated that lot 8317 has significantly lower expression of OATP1B1 (3-fold), OATP1B3 (5-fold), NTCP (2- to 11-fold) and P-gp (2- to 4-fold) compared with lots 8339 and 8350 (Table 3). Therefore, the effect of the pan-inhibitor was more prominent in lots 8339 and 8350 compared with the effect in lot 8317. We also observed an increase in the uptake of pevonedistat in the presence of verapamil and ketoprofen. Verapamil is known to inhibit P-gp that is functionally expressed in plated human hepatocytes (Lundquist et al., 2014). Given pevonedistat as a substrate of efflux transporters (data not shown) it is likely that inhibition of P-gp by verapamil might have increased the uptake of pevonedistat. In 2006, Ishiguro et al. reported that the uptake of telmisartan (high non-specific binding), is greatly improved in the presence of HSA (Ishiguro et al., 2006). Similarly, we analyzed the uptake of pevonedistat with and without CsA in the presence of 0.5% HSA assuming that nonspecific binding of pevonedistat is potentially masking the effect of inhibitors. However, HSA did not improve the inhibition of pevonedistat uptake by CsA (Fig. 4), suggesting nonspecific binding is not interfering with the effects of inhibitors. The binding of CsA to 0.5% HSA is considered to be low as it has been shown to bind to only lipoproteins in human plasma (Wasan et al., 2008). Taken together, these data suggested that the hepatic uptake of pevonedistat is potentially mediated by minor contributions from multiple transporters, such as OATPs, OAT2, and ENT1. Subsequently, we determined CLact,inf and CLdiff,inf of pevonedistat using human hepatocytes as they capture all the individual transport processes. Typically, CLact,inf measured using current in vitro tools (hepatocytes and transporter cell lines) is underpredicted (Varma et al., 2014; Chothe et al., 2018). In this study, we also observed significant underprediction of CLact,inf of pevonedistat using human hepatocytes as indicated by the ESF of 13 that was needed for extrapolation to successfully recover the observed CLplasma (Supplemental Fig. 2). This ESF was comparable to the ESF of rosuvastatin (19) that was used as a control in this study (data not shown) and also with the ESF reported in the literature for typical OATP substrates (Varma et al., 2014; Chothe et al., 2018). Interestingly, CLdiff,inf measured at 4°C was found to be saturated at higher concentration (200 µM); however, the underlying reason for this effect is unknown and remains to be investigated. Nevertheless, we calculated CLact,inf and CLdiff,inf of pevonedistat, excluding the uptake at 200 µM to evaluate the possible impact on in vitro to in vivo extrapolation and DDI prediction (data not shown). The required ESF for in vitro to in vivo extrapolation and prediction of DDI effect was found to be very close to the one using original uptake data indicating minimal impact of saturation on in vitro to in vivo extrapolation and DDI predictions.

In this study, we observed that CLint,met plus CLint,bile of pevonedistat is much greater than its CLdiff,inf (CLint,met + CLint,bile of 58.9 ml/min/kg versus CLdiff,inf of 8.7 ml/min/kg); therefore, to predict CLH of pevonedistat, we used the ECM incorporating both CLinf (CLact,inf and CLdiff,inf) and CLmet. With the ESF of 13 for CLact,inf, the predicted CLplasma was in good agreement with observed CLplasma (Table 5) of pevonedistat. For comparison, CLplasma was also predicted by the CCM, providing a reasonable prediction of CLplasma (30.8) with an ESF of 4. We later evaluated both the CCM and ECM in terms of their predictivity for DDI between pevonedistat and itraconazole. Importantly, the predicted plasma AUCR of pevonedistat was more than 2-fold higher than the observed plasma AUCR by the CCM, whereas the observed plasma AUCR was closely matched with the predicted AUCR by the ECM (Table 6). In our study, the sinusoidal efflux of pevonedistat was not fully characterized, and it was assumed to be equal to CLdiff; however, when we exercised the ECM incorporating sinusoidal efflux the AUCR of pevonedistat was overpredicted (1.83 versus observed AUCR of 1.23), suggesting that sinusoidal CLeff of pevonedistat is minimal. Collectively, these data suggested that both the CCM and ECM models are good in predicting CLplasma of dual substrates of transporters and enzymes; however, the ECM is more appropriate to reliably predict DDI effect and identify RDS such as hepatic uptake.

View this table:
TABLE 6

Prediction of DDI effect with itraconazole on pevonedistat plasma and liver exposure

Typically, transporter substrate drugs are asymmetrically distributed into the liver due to the concentration gradient developed by uptake transporters (Zhang et al., 2019). In this scenario, any changes in drug concentration inside the liver is not truly reflected in the plasma. This has been well demonstrated in the study by Chang et al., in which OATP-mediated uptake drives the asymmetric distribution of atorvastatin into the liver while CYP3A4 inhibition by itraconazole increases the liver concentration of atorvastatin by 21-fold without any meaningful change in systemic exposure in mice (Chang et al., 2014). Similarly, in our study, the ECM predicted significant impact of itraconazole on the liver exposure (liver AUCR of 2.85) but not on the plasma exposure (plasma AUCR of 1.23) of pevonedistat. These results highlighted the application of the static ECM in characterizing systemic DDI as well as in assessing potential liver DDI risk. Meanwhile, the CCM predicted the similar degree of DDI in both plasma and liver, which is not surprising, as the CCM assumes high permeability between plasma and liver, and systemic DDI serves as a good surrogate of liver DDI.

The modulation of hepatic OATP function significantly impacts the PK of many of its substrate drugs (Giacomini et al., 2010; Yoshikado et al., 2017). For example, significant fractional contribution (ft > 0.9) of OATP1B1 to the uptake of statin drugs (Bi et al., 2019) and repaglinide has been reported and, therefore, OATP inhibition significantly increases systemic exposure of these drugs, particularly statins, to a level causing deleterious effects (Alam et al., 2018). In this study, we were not able to quantitatively estimate the contribution of individual transporters to the hepatic uptake of pevonedistat due to differential sensitivity of hepatocyte donor lots to inhibitors and the weak contribution from individual transporters, indicating lower DDI risk.

In conclusion, the present study provides an important example of the hepatic uptake as an RDS in the CLH. We demonstrated that although both the ECM and CCM predict CLH reasonably well, the DDI effect (CYP3A4 inhibition) was successfully explained by the ECM but not CCM for dual substrates of uptake transporter and CYP3A. Recently, we have also developed a physiologically-based pharmacokinetic model with a nested permeability-limited liver model using the Simcyp Population-Based Simulator to describe the hepatic disposition of pevonedistat and the DDI effects with itraconazole (CYP3A4 inhibitor) and rifampicin (OATP inhibitor and CYP3A4 inducer). The details of this model and its application in PK simulation and DDI predictions has been described in the poster presented at the American College of Clinical Pharmacology annual meeting (Zhou et al., 2021b).

Acknowledgments

The authors would like to thank Professor Yuichi Sugiyama (Josai international University) for his input in this work, especially in conducting uptake experiments in the presence of human serum albumin. The authors also extend their thanks to Drs. Philip C. Smith and John K Fallon at the University of North Carolina, Chapel Hill for their help in conducting targeted proteomics to measure the protein abundance of drug transporters in human hepatocytes.

Authorship Contributions

Participated in research design: Sandoval, Cohen, Pusalkar, Chowdhury, Chothe.

Conducted experiments: Sandoval, Chuang, Cohen, Pusalkar, Yucha.

Performed data analysis: Sandoval, Chuang, Cohen, Yoneyama, Pusalkar, Yucha, Chothe.

Wrote or contributed to the writing of the manuscript: Sandoval, Cohen, Yoneyama, Pusalkar, Chowdhury, Chothe.

Footnotes

    • Received January 20, 2021.
    • Accepted April 18, 2021.

  • This research was funded by Millennium Pharmaceuticals, Inc., Cambridge, MA, USA, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited. This work received no external funding.

  • All authors are current or former employees of Takeda Development Center Americas, Inc. (TDCA), Lexington, MA, USA. All the authors (except Sandeepraj Pusalkar) declares that they hold common stocks in Takeda Pharmaceutical Company Limited.

  • ↵1 Current affiliation: Servier Pharmaceuticals, Boston, Massachusetts.

  • ↵2 Current affiliation: Boston Pharmaceuticals, Cambridge, Massachusetts.

  • https://dx.doi.org/10.1124/dmd.122.000836.

  • ↵Embedded ImageThis article has supplemental material available at dmd.aspetjournals.org.

Abbreviations

AUC
area under the curve
AUCR
area under the concentration-time curve ratio
BSA
bovine serum albumin
CCM
conventional clearance model
CLactive,inf
active uptake clearance
CLdiff,inf
passive diffusion clearance
CLH
hepatic clearance
CLplasma
plasma clearance
CsA
cyclosporine A
DDI
drug-drug interaction
ECM
extended clearance model
ENT
equilibrative nucleoside transporter
ESF
empirical scaling factor
HLM
human liver microbiome
HSA
human serum albumin
Km
transporter affinity
LC/MS/MS
liquid chromatography tandem mass spectrometry
NBMPR
nitrobenzylthioinosine
NTCP
Na+-taurocholate co-transporting polypeptide
OATP
organic anion transporting polypeptide
OCT
organic cation transporter
PK
pharmacokinetics
RDS
rate-determining step
TCA
taurocholate

This is an open access article distributed under the CC BY-NC Attribution 4.0 International license.

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Uptake as the RDS in Pevonedistat Hepatic Clearance

Philip Sandoval, Bei-Ching Chuang, Lawrence Cohen, Tomoki Yoneyama, Sandeepraj Pusalkar, Robert W. Yucha, Swapan K Chowdhury and Paresh P. Chothe
Drug Metabolism and Disposition July 1, 2022, 50 (7) 980-988; DOI: https://doi.org/10.1124/dmd.122.000836
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