Binding Processes Determine the Stereoselective Intestinal and

25 Sep 2012 - First-Pass Metabolism Considerations in Pharmaceutical Product Development. Ashok K. Shakya , Belal O. Al-Najjar , Pran Kishore Deb ...
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Binding Processes Determine the Stereoselective Intestinal and Hepatic Extraction of Verapamil in Vivo Helena Anna Thörn,† Erik Sjögren,† Paul Alfred Dickinson,‡ and Hans Lennernas̈ †,* †

Department of Pharmacy, Uppsala University, Box 580, Uppsala, Sweden Clinical Pharmacology and Pharmacometrics, AstraZeneca R&D, Alderley Park, Macclesfield, United Kingdom



ABSTRACT: The aim of this study was to investigate the mechanisms that might explain the observed route-dependent stereoselective pharmacokinetics (PK) of R/S-verapamil (R/SVER) following oral and intravenous (iv) administration, by using a novel pig-specific physiologically based pharmacokinetic (PBPK) model suitable for investigations of first-pass extraction in the gut (EG) and the liver (EH). The PBPK model consisted of eight tissue compartments and was designed to simultaneously model the plasma concentration−time (PCT) profiles from three sampling sites after intrajejunal (ij) or iv administration of VER. The PBPK model successfully described the observed PCT profiles and EH over time for R- and S-VER. Extensive tissue binding to gut mucosa, liver, and lungs was an important determinant of the observed PK data. The stereoselective PK of VER was explained by a combination of several processes, including enantioselective plasma protein binding, blood-to-plasma partition, and gut mucosa and liver tissue distribution. The absence of stereoselectivity after iv dosing indicates that the first-pass tissue binding effect is an important factor in determining the steroselective PK of R/S-VER after oral administration. Additionally a combination of extensive liver tissue binding and a metabolite inhibition mechanism explained the time-dependent EH for both R- and S-VER. An in vitro−in vivo correlation of absorption needs to consider these processes because tissue binding may confound analysis of a drug’s biopharmaceutical properties when using classical deconvolution or convolution techniques. In conclusion, a combination of PK data from multiple plasma sampling sites and a PBPK modeling approach provided a mechanistic understanding of processes involved in the intestinal absorption and first-pass extraction of R- and S-VER. KEYWORDS: verapamil, PBPK, hepatic extraction, gut wall extraction, first-pass metabolism



INTRODUCTION The calcium channel blocking agent R/S-verapamil (R/S-VER) is almost completely eliminated ( R-norverapamil and > R-VER.45 In accordance with this, EH was best described with a higher kinact for S-VER compared with R-VER (Table 1). In general, EH is reported as a constant number based on AUC calculations. This study indicates that considering EH as a constant might be an overly simplified and misleading way of describing EH and the plasma concentration−time profile fluctuations following oral administration. For R/S-VER, the time-dependent EH enhances the importance of the oral first-pass effect and further explains the routedependent stereoselective PK. This group has previously reported a similar route- and time-dependent EH for finasteride in pigs with higher EH during the absorption phase.49 Finasteride was also suggested to distribute extensively within the liver. Time-dependent EH and high tissue binding to the liver during the absorption phase of a drug has implications in the assessment of in vivo bioequivalence and for establishment of in vitro−in vivo correlation of drug absorption when only drug dissolution/ absorption is assumed generally to be changing with time. It has previously been noted that gut tissue may act as a reservoir for drug partition during the first-pass after oral administration.50,51 Likewise, basic lipophilic drugs and BCS/ BDDCS class I compounds have been recognized to be highly concentrated in the liver.49,52,53 Under linear conditions, tissue binding does not affect the total plasma exposure of a drug.54 This could be a rationale to why several reported models adopt an unbound fraction in gut set to 1.40,55 However, tissue binding will have an impact on the plasma concentration−time profile observed as a delay in appearance of the drug in the blood circulation. In this study, the initial model input value of partition to the gut mucosa (KP = 5) resulted in an earlier appearance of ij administered R/S-VER in both VP and VH compared with what was observed in the pig in vivo study. This could be seen as a higher exposure during the absorption period (0−100 min) and a higher maximum concentration compared with observed data. In the same manner, the initial model input for tissue partition to the liver (KP = 5) shifted the plasma concentration−time profile in the VH. Tissue binding to gut mucosa and liver also affected the initial distribution phase immediately upon the end of the perfusion seen as a more rapid distribution with lower tissue binding. To conclude, extensive tissue binding to the gut mucosa and liver are likely important factors that account for the observed in vivo plasma concentration− time profiles and the time-dependent EH of ij administered R/S-VER. A lag time in the absorption (i.e., delayed maximum concentration) of R/S-VER, similar to the delay in appearance of R/S-VER in plasma after ij administration in pigs, has been observed after oral dosing in humans, which after PBPK simulations

Figure 3. The plasma concentration−time profiles of R- and Sverapamil in the portal (VP), hepatic (VH), and femoral (VF) vein following intrajejunal (ij) administration: (A) concentration of each enantiomer in the three different plasma sites; (B) the difference in concentration between the R- and S-isomer in each plasma site. Symbols represent observed mean ± SD in vivo data and dotted lines the simulated profiles.

with identical CLint values for R- and S-VER. Importantly, it was not possible to simultaneously capture the VP, VH, and EH profiles using different CLint for the two isomers (and similar KP in gut mucosa and liver for the isomers), further supporting the conclusion that the stereoselective PK is not driven by differences in CYP specificity. In this study, enantiomer differences in intestinal absorption were not considered a likely cause for the stereoselective plasma PK of R/S-VER. This assumption was based on results from the pig in vivo study where fabs was measured during perfusion and found to be similar for the two isomers.12 The results were expected since passive diffusion is the main membrane transport mechanism of VER in both intestine and liver and also reported to be high.28,29,35,43 ABCB1 (P-glycoprotein) has been reported to efflux R/S-VER across the apical membrane, but no 3040

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Figure 4. (A) The plasma concentration−time profiles of R- and S-verapamil in the portal (VP), hepatic (VH), and femoral vein (VF) following intrajejunal (ij) administration of verapamil together with a low dose (8 mg) of ketoconazole in the intestinal segment. (B) The impact of gut wall metabolism (EG) on the portal vein concentration of R- and S-verapamil after intrajejunal (ij) administration with (+Keto) or without ketoconazole (−Keto). Symbols represent observed mean ± SD in vivo data and dotted lines the simulated profiles.

Figure 5. The impact of tissue partition to the gut mucosa compartments (KP,GM) after (A) intravenous (iv) administration and (B) intrajejunal (ij) administration of R-verapamil (R-VER). Symbols represent observed mean ± SD in vivo data. Dotted lines represent simulated profiles with different values of KP,GM (KP,liv and KP,lung equal to 1). Solid line (KP final) represents the simulated profile with the chosen values of KP,GM, KP,liv, and KP,lung according to Table 1. 3041

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Figure 6. The impact of tissue partition to the liver compartments (KP,liv) on the plasma concentration−time profiles and the hepatic extraction ratio (EH) of R-verapamil (R-VER) after (A) intravenous (iv) or (B) intrajejunal (ij) administration. Symbols represent observed mean ± SD in vivo data. Dotted lines represent simulated profiles with different values of KP,liv (KP,GM and KP,lung equal to 1). Solid line (KP final) represents the simulated profile with the chosen values of KP,GM, KP,liv, and KP,lung according to Table 1.

Figure 7. The impact of tissue partition to the lung compartment (KP,lung) after (A) intravenous (iv) administration and (B) intrajejunal (ij) administration of R-verapamil (R-VER). Symbols represent observed mean ± SD in vivo data. Dotted lines represent simulated profiles with different values of KP,lung (KP,GM and KP,liv equal to 1). Solid line (KP final) represent the simulated profile with the chosen values of KP,GM, KP,liv, and KP,lung according to Table 1.

also been reported.43 Because the reduction in apparent absorption rate into plasma was observed not only after oral administration but also during intestinal perfusion of a drug

was suggested to be a consequence of delayed gastric emptying.56,57 A delay in the absorption of R/S-VER during intestinal single-pass perfusion studies in human jejunum has 3042

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Table 3. Changes Made on the Parameters in the Control Group To Simulate the Verapamil + Ketoconazole Pharmacokinetic Profilesa parameter fuP CLint gut wall (mL/(min·mg)) KP,GM CLabs (L/min) kinact (min−1)

R-VER+Keto

change

S-VER+Keto

change

0.26 (0.13) 0 (0.72)

↑2 0.60 (0.23) total loss 0.08 (0.72)

↑2.2 ↓9

170 (170) 4.8 × 10−4 (4.0 × 10−4) 0.002 (0.0015)

↔ ↑1.2

↓3 ↑1.2

↑1.3

100 (300) 4.8 × 10−4 (4.0 × 10−4) 0.006 (0.005)

↑1.2

a

fuP, fraction unbound in plasma; CLint, intrinsic clearance; KP,GM, tissue partition coefficient for gut mucosa; CLabs, absorption clearance; kinact, inactivation constant; R- and S-VER, R- and S-verapamil; Keto, ketoconazole. Values in parentheses indicate the parameter values in the control group.

Even though a relatively low dose of ketoconazole was administered (0.3 mg/kg versus clinical dose of 3 mg/kg), it was shown to have large impact on the systemically available fraction of R/S-VER. PBPK modeling indicated that the increased VP concentration of R/S-VER, when the CYP3A inhibitor ketoconazole was coadministrated in the gut, was caused by selectively inhibited intestinal metabolism. In addition to the loss of gut wall metabolism, the tissue binding of S-VER to the gut mucosa compartments was decreased 3 times to cover the effect of ketoconazole on the plasma concentration−time profiles of R/S-VER. Presumably, R/SVER was partly displaced from GM binding sites by ketoconazole.59 An unexpected observation in the pig in vivo study was an increased EH in the ketoconazole group compared with control, and it was suggested that the increased VP concentration of R/S-VER and norverapamil in the ketoconazole group could have temporarily affected the fuP and thereby increased the first-pass extraction in the liver.12 The PBPK simulations in this study confirmed this hypothesis. The kinact was slightly increased to capture the EH profile in the ketoconazole group and might be due to the higher concentration of the metabolite norverapamil in this group compared with control.46−49 The absorption clearance was set to a 1.2 times higher value in the ketoconazole group compared with control. The fraction absorbed in the in vivo study was slightly higher in the ketoconazole group and was most likely due to interindividual differences between the pigs included in the study. For a BCS and BDDCS class I compound, such as R/S-VER, transporter effects are considered minimal in gut.4,5 In conclusion, a novel pig-specific PBPK model developed for mechanistic investigations of first-pass extraction of drugs following oral administration was able to successfully describe the plasma concentration time profiles of ij and iv administered R- and S-VER. The stereoselective PK of R/S-VER was explained by a combination of several processes, including enantioselective plasma protein binding, B/P partition, and gut and liver tissue distribution. The absence of stereoselective PK after iv dosing indicates that the first-pass effect is an important factor in determining the difference in isomer plasma concentration after oral administration. Additionally, a combination of extensive liver tissue binding and a metabolite inhibition mechanism created a time-dependent EH for R/S-VER with major consequences on the PK of the drug. Finally, this study demonstrated that a combination of multiple plasma sampling sites data and a PBPK modeling approach improved the mechanistic understanding of processes involved in the first-pass

Figure 8. Time-dependent hepatic extraction of R- and S-verapamil (R- and S-VER) following intravenous administration (iv), intrajejunal (ij) administration, and ij administration together with ketoconazole. Symbols represent observed mean ± SEM in vivo data and lines the simulated profiles with the chosen values of KP,GM, KP,liv, and KP,lung according to Table 1.

solution when gastric emptying is bypassed, this suggest that gastric emptying delay is a less likely mechanism to explain the PK after oral administration in the clinic. Plausibly, the clinical observations may be explained by high tissue binding to the gut and liver in humans in a similar manner as for the pigs in this study. To capture the iv plasma concentration−time profiles of R/SVER, tissue binding to the lungs was increased compared with the initial input. Tissue binding to the lungs also affected the plasma concentration−time profiles of R/S-VER after ij administration, mainly with impact on the distribution phase. R/SVER partitioning to lung tissue has been reported previously with 50% of an iv dose partitioning to the lungs during the first passage.58 3043

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(6) Sandstrom, R.; Knutson, T. W.; Knutson, L.; Jansson, B.; Lennernas, H. The effect of ketoconazole on the jejunal permeability and CYP3A metabolism of (R/S)-verapamil in humans. Br. J. Clin. Pharmacol. 1999, 48 (2), 180−189. (7) Nelson, W. L.; Olsen, L. D.; Beitner, D. B.; Pallow, R. J., Jr. Regiochemistry and substrate stereoselectivity of O-demethylation of verapamil in the presence of the microsomal fraction from rat and human liver. Drug Metab. Dispos. 1988, 16 (2), 184−188. (8) Kroemer, H. K.; Echizen, H.; Heidemann, H.; Eichelbaum, M. Predictability of the in vivo metabolism of verapamil from in vitro data: Contribution of individual metabolic pathways and stereoselective aspects. J. Pharmacol. Exp. Ther. 1992, 260 (3), 1052−1057. (9) Skaanild, M. T. Porcine cytochrome P450 and metabolism. Curr. Pharm. Des. 2006, 12 (11), 1421−1427. (10) Skaanild, M. T.; Friis, C. Cytochrome P450 sex differences in minipigs and conventional pigs. Pharmacol. Toxicol. 1999, 85 (4), 174−180. (11) Bogaards, J. J.; Bertrand, M.; Jackson, P.; Oudshoorn, M. J.; Weaver, R. J.; van Bladeren, P. J.; Walther, B. Determining the best animal model for human cytochrome P450 activities: a comparison of mouse, rat, rabbit, dog, micropig, monkey and man. Xenobiotica 2000, 30 (12), 1131−1152. (12) Thorn, H. A.; Hedeland, M.; Bondesson, U.; Knutson, L.; Yasin, M.; Dickinson, P.; Lennernas, H. Different effects of ketoconazole on the stereoselective first-pass metabolism of R/S-verapamil in the intestine and the liver: Important for the mechanistic understanding of first-pass drug-drug interactions. Drug Metab. Dispos. 2009, 37 (11), 2186−2196. (13) Thorn, H. A.; Lundahl, A.; Schrickx, J. A.; Dickinson, P. A.; Lennernas, H. Drug metabolism of CYP3A4, CYP2C9 and CYP2D6 substrates in pigs and humans. Eur. J. Pharm. Sci. 2011, 43 (3), 89−98. (14) Gross, A. S.; Heuer, B.; Eichelbaum, M. Stereoselective protein binding of verapamil enantiomers. Biochem. Pharmacol. 1988, 37 (24), 4623−4627. (15) Poulin, P.; Jones, R. D.; Jones, H. M.; Gibson, C. R.; Rowland, M.; Chien, J. Y.; Ring, B. J.; Adkison, K. K.; Ku, M. S.; He, H.; Vuppugalla, R.; Marathe, P.; Fischer, V.; Dutta, S.; Sinha, V. K.; Bjornsson, T.; Lave, T.; Yates, J. W. PHRMA CPCDC initiative on predictive models of human pharmacokinetics, part 5: Prediction of plasma concentration-time profiles in human by using the physiologically-based pharmacokinetic modeling approach. J. Pharm. Sci. 2011, 100 (10), 4127−4157. (16) Lave, T.; Parrott, N.; Grimm, H. P.; Fleury, A.; Reddy, M. Challenges and opportunities with modelling and simulation in drug discovery and drug development. Xenobiotica 2007, 37 (10−11), 1295−1310. (17) Rostami-Hodjegan, A.; Tucker, G. T. Simulation and prediction of in vivo drug metabolism in human populations from in vitro data. Nat. Rev. Drug Discovery 2007, 6 (2), 140−148. (18) Beaumont, K.; Smith, D. A. Does human pharmacokinetic prediction add significant value to compound selection in drug discovery research? Curr. Opin. Drug Discovery Dev. 2009, 12 (1), 61− 71. (19) Lave, T.; Chapman, K.; Goldsmith, P.; Rowland, M. Human clearance prediction: Shifting the paradigm. Expert Opin. Drug Metab. Toxicol. 2009, 5 (9), 1039−1048. (20) Obach, R. S. Predicting clearance in humans from in vitro data. Curr. Top. Med. Chem. 2011, 11 (4), 334−339. (21) Zhao, P.; Zhang, L.; Grillo, J. A.; Liu, Q.; Bullock, J. M.; Moon, Y. J.; Song, P.; Brar, S. S.; Madabushi, R.; Wu, T. C.; Booth, B. P.; Rahman, N. A.; Reynolds, K. S.; Gil Berglund, E.; Lesko, L. J.; Huang, S. M. Applications of physiologically based pharmacokinetic (PBPK) modeling and simulation during regulatory review. Clin. Pharmacol. Ther. 2011, 89 (2), 259−267. (22) Shen, D. D.; Kunze, K. L.; Thummel, K. E. Enzyme-catalyzed processes of first-pass hepatic and intestinal drug extraction. Adv. Drug Delivery Rev. 1997, 27 (2−3), 99−127.

extraction of drugs like VER. It highlights the myriad of factors that contribute to the PK profile of a drug and that tissue binding may confound analysis of a drug’s biopharmaceuticals properties when classical deconvolution or convolution approaches are used.



AUTHOR INFORMATION

Corresponding Author

*Mailing address: Hans Lennernäs, PhD, Professor in Biopharmaceutics, Department of Pharmacy, Uppsala University, Box 580, SE-751 23 Uppsala, Sweden. E-mail: hans. [email protected]. Telephone: +46 18 471 4317. Fax: +46 18 471 4223. Notes

The authors declare no competing financial interest.



ABBREVIATIONS VER, verapamil; CYP, cytochrome P450; BCS, Biopharmaceutics Classification System; BDDCS, Biopharmaceutic Drug Disposition Classification System; PK, pharmacokinetic; ij, intrajejunal; iv, intravenous; CLint, intrinsic clearance; CLH, hepatic clearance; fuP, fraction unbound in plasma; B/P, bloodto-plasma ratio; PBPK, physiologically based pharmacokinetic; VP, portal vein; MAC, mixed arterial compartment; LT, lumped tissue; LTVF, lumped tissue associated with the femoral vein; GI, gastrointestinal tract; GMV, gut mucosa vascular compartment; GMVabs, gut mucosa vascular compartment associated with perfused intestinal jejunal segment; GMVrest, gut mucosa not associated with perfused intestinal jejunal segment; LVC, liver vascular compartment; VH, hepatic vein; VF, femoral vein; CO, cardiac output; LUM, single-passed perfused jejunal segment; LCC, liver cell compartment; GMC, gut mucosa cell compartment; CLdif, passive diffusion clearance; KP, partition coefficient constant; vperf, perfusion flow rate; vlum, intestinal lumen volume; CLabs, absorption clearance; fabs, fraction absorbed; Qmuc, intestinal mucosal blood flow; CLmet,H, in vivo hepatic CLint; CLmet,G, in vivo intestinal CLint; EH, hepatic extraction; kinact, inactivation parameter; AUC, area under the curve; EG, intestinal extraction; CLbile, biliary clearance; fuH, fraction unbound in the hepatocyte; fuE, fraction unbound in the enterocyte; CLren, renal clearance; vblood, blood volume



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