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Is It Time to Use Modeling of Cellular Transporter Homeostasis to Inform Drug-Drug Interaction Studies: Theoretical Considerations

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Abstract

Mathematical modeling has been an important tool in pharmaceutical research for 50 + years and there is increased emphasis over the last decade on using modeling to improve the efficiency and effectiveness of drug development. In an earlier commentary, we applied a multiscale model linking 6 scales (whole body, tumor, vasculature, cell, spatial location, time), together with literature data on nanoparticle and tumor properties, to demonstrate the effects of nanoparticle particles on systemic disposition. The current commentary used a 4-scale model (cell membrane, intracellular organelles, spatial location, time) together with literature data on the intracellular processing of membrane receptors and transporters to demonstrate disruption of transporter homeostasis can lead to drug-drug interaction (DDI) between victim drug (VD) and perpetrator drug (PD), including changes in the area-under-concentration–time-curve of VD in cells that are considered significant by the US Food and Drug Administration (FDA). The model comprised 3 computational components: (a) intracellular transporter homeostasis, (b) pharmacokinetics of extracellular and intracellular VD/PD concentrations, and (c) pharmacodynamics of PD-induced stimulation or inhibition of an intracellular kinetic process. Model-based simulations showed that (a) among the five major endocytic processes, perturbation of transporter internalization or recycling led to the highest incidence and most extensive DDI, with minor DDI for perturbing transporter synthesis and early-to-late endosome and no DDI for perturbing transporter degradation and (b) three experimental conditions (spatial transporter distribution in cells, VD/PD co-incubation time, extracellular PD concentrations) were determinants of DDI detection. We propose modeling is a useful tool for hypothesis generation and for designing experiments to identify potential DDI; its application further aligns with the model-informed drug development paradigm advocated by FDA.

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References

  1. Grymonpre RE, Mitenko PA, Sitar DS, Aoki FY, Montgomery PR. Drug-associated hospital admissions in older medical patients. J Am Geriatr Soc. 1988;36(12):1092–8.

    Article  CAS  Google Scholar 

  2. Palleria C, Di Paolo A, Giofre C, Caglioti C, Leuzzi G, Siniscalchi A, et al. Pharmacokinetic drug-drug interaction and their implication in clinical management. J Res Med Sci. 2013;18(7):601–10.

    PubMed  PubMed Central  Google Scholar 

  3. Wagner C, Zhao P, Pan Y, Hsu V, Grillo J, Huang SM, et al. Application of physiologically based pharmacokinetic (PBPK) modeling to support dose selection: report of an FDA public workshop on PBPK. CPT Pharmacometrics Syst Pharmacol. 2015;4(4):226–30. https://doi.org/10.1002/psp4.33.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Niemi M. Role of OATP transporters in the disposition of drugs. Pharmacogenomics. 2007;8(7):787–802.

    Article  CAS  Google Scholar 

  5. Tweedie D, Polli JW, Berglund EG, Huang SM, Zhang L, Poirier A, et al. Transporter studies in drug development: experience to date and follow-up on decision trees from the International Transporter Consortium. Clin Pharmacol Ther. 2013;94(1):113–25. https://doi.org/10.1038/clpt.2013.77.

    Article  CAS  PubMed  Google Scholar 

  6. Shitara Y, Itoh T, Sato H, Li AP, Sugiyama Y. Inhibition of transporter-mediated hepatic uptake as a mechanism for drug-drug interaction between cerivastatin and cyclosporin A. J Pharmacol Exp Ther. 2003;304(2):610–6. https://doi.org/10.1124/jpet.102.041921.

    Article  CAS  PubMed  Google Scholar 

  7. Shitara Y, Hirano M, Sato H, Sugiyama Y. Gemfibrozil and its glucuronide inhibit the organic anion transporting polypeptide 2 (OATP2/OATP1B1:SLC21A6)-mediated hepatic uptake and CYP2C8-mediated metabolism of cerivastatin: analysis of the mechanism of the clinically relevant drug-drug interaction between cerivastatin and gemfibrozil. J Pharmacol Exp Ther. 2004;311(1):228–36. https://doi.org/10.1124/jpet.104.068536.

    Article  CAS  PubMed  Google Scholar 

  8. Tirona RG, Leake BF, Wolkoff AW, Kim RB. Human organic anion transporting polypeptide-C (SLC21A6) is a major determinant of rifampin-mediated pregnane X receptor activation. J Pharmacol Exp Ther. 2003;304(1):223–8. https://doi.org/10.1124/jpet.102.043026.

    Article  CAS  PubMed  Google Scholar 

  9. Kiser JJ, Gerber JG, Predhomme JA, Wolfe P, Flynn DM, Hoody DW. Drug/drug interaction between lopinavir/ritonavir and rosuvastatin in healthy volunteers. J Acquir Immune Defic Syndr. 2008;47(5):570–8. https://doi.org/10.1097/QAI.0b013e318160a542.

    Article  CAS  PubMed  Google Scholar 

  10. Neuvonen PJ, Niemi M, Backman JT. Drug interactions with lipid-lowering drugs: mechanisms and clinical relevance. Clin Pharmacol Ther. 2006;80(6):565–81. https://doi.org/10.1016/j.clpt.2006.09.003.

    Article  CAS  PubMed  Google Scholar 

  11. Campbell SD, de Morais SM, Xu JJ. Inhibition of human organic anion transporting polypeptide OATP 1B1 as a mechanism of drug-induced hyperbilirubinemia. Chem Biol Interact. 2004;150(2):179–87. https://doi.org/10.1016/j.cbi.2004.08.008.

    Article  CAS  PubMed  Google Scholar 

  12. Umehara K, Iwai M, Adachi Y, Iwatsubo T, Usui T, Kamimura H. Hepatic uptake and excretion of (-)-N-{2-[(R)-3-(6,7-dimethoxy-1,2,3,4-tetrahydroisoquinoline-2-carbonyl)piperidi no]ethyl}-4-fluorobenzamide (YM758), a novel if channel inhibitor, in rats and humans. Drug Metab Dispos. 2008;36(6):1030–8. https://doi.org/10.1124/dmd.108.020669.

    Article  CAS  PubMed  Google Scholar 

  13. Karlgren M, Ahlin G, Bergstrom CA, Svensson R, Palm J, Artursson P. In vitro and in silico strategies to identify OATP1B1 inhibitors and predict clinical drug-drug interactions. Pharm Res. 2012;29(2):411–26. https://doi.org/10.1007/s11095-011-0564-9.

    Article  CAS  PubMed  Google Scholar 

  14. Izumi S, Nozaki Y, Maeda K, Komori T, Takenaka O, Kusuhara H, et al. Investigation of the impact of substrate selection on in vitro organic anion transporting polypeptide 1B1 inhibition profiles for the prediction of drug-drug interactions. Drug Metab Dispos. 2015;43(2):235–47. https://doi.org/10.1124/dmd.114.059105.

    Article  CAS  PubMed  Google Scholar 

  15. Vildhede A, Mateus A, Khan EK, Lai Y, Karlgren M, Artursson P, et al. Mechanistic modeling of pitavastatin disposition in sandwich-cultured human hepatocytes: a proteomics-informed bottom-up approach. Drug Metab Dispos. 2016;44(4):505–16. https://doi.org/10.1124/dmd.115.066746.

    Article  CAS  PubMed  Google Scholar 

  16. Vaidyanathan J, Yoshida K, Arya V, Zhang L. Comparing various in vitro prediction criteria to assess the potential of a new molecular entity to inhibit organic anion transporting polypeptide 1B1. J Clin Pharmacol. 2016;56(Suppl 7):S59–72. https://doi.org/10.1002/jcph.723.

    Article  CAS  PubMed  Google Scholar 

  17. Yoshida K, Maeda K, Sugiyama Y. Transporter-mediated drug–drug interactions involving OATP substrates: predictions based on in vitro inhibition studies. Clin Pharmacol Ther. 2012;91(6):1053–64. https://doi.org/10.1038/clpt.2011.351.

    Article  CAS  PubMed  Google Scholar 

  18. Yoshikado T, Yoshida K, Kotani N, Nakada T, Asaumi R, Toshimoto K, et al. Quantitative analyses of hepatic OATP-mediated interactions between statins and inhibitors using PBPK modeling with a parameter optimization method. Clin Pharmacol Ther. 2016;100(5):513–23. https://doi.org/10.1002/cpt.391.

    Article  CAS  PubMed  Google Scholar 

  19. Picard N, Levoir L, Lamoureux F, Yee SW, Giacomini KM, Marquet P. Interaction of sirolimus and everolimus with hepatic and intestinal organic anion-transporting polypeptide transporters. Xenobiotica. 2011;41(9):752–7. https://doi.org/10.3109/00498254.2011.573882.

    Article  CAS  PubMed  Google Scholar 

  20. Barshes NR, Goodpastor SE, Goss JA. Sirolimus-atorvastatin drug interaction in the pancreatic islet transplant recipient. Transplantation. 2003;76(11):1649–50. https://doi.org/10.1097/01.TP.0000085287.03333.FC.

    Article  PubMed  Google Scholar 

  21. Hong YA, Kim HD, Jo K, Park YK, Lee J, Sun IO, et al. Severe rhabdomyolysis associated with concurrent use of simvastatin and sirolimus after cisplatin-based chemotherapy in a kidney transplant recipient. Exp Clin Transplant. 2014;12(2):152–5. https://doi.org/10.6002/ect.2013.0003.

    Article  PubMed  Google Scholar 

  22. Kotanko P, Kirisits W, Skrabal F. Rhabdomyolysis and acute renal graft impairment in a patient treated with simvastatin, tacrolimus, and fusidic acid. Nephron. 2002;90(2):234–5.

    Article  Google Scholar 

  23. Renders L, Haas CS, Liebelt J, Oberbarnscheidt M, Schocklmann HO, Kunzendorf U. Tacrolimus and cerivastatin pharmacokinetics and adverse effects after single and multiple dosing with cerivastatin in renal transplant recipients. Br J Clin Pharmacol. 2003;56(2):214–9.

    Article  CAS  Google Scholar 

  24. Shebley M, Liu J, Kavetskaia O, Sydor J, de Morais SM, Fischer V, et al. Mechanisms and predictions of drug-drug interactions of the hepatitis C virus three direct-acting antiviral regimen: paritaprevir/ritonavir, ombitasvir, and dasabuvir. Drug Metab Dispos. 2017;45(7):755–64. https://doi.org/10.1124/dmd.116.074518.

    Article  CAS  PubMed  Google Scholar 

  25. Omar MA, Wilson JP. FDA adverse event reports on statin-associated rhabdomyolysis. Ann Pharmacother. 2002;36(2):288–95. https://doi.org/10.1345/aph.1A289.

    Article  CAS  PubMed  Google Scholar 

  26. Wagner JG. History of pharmacokinetics. Pharmacol Ther. 1981;12(3):537–62. https://doi.org/10.1016/0163-7258(81)90097-8.

    Article  CAS  PubMed  Google Scholar 

  27. Sorger PK, Allerheiligen SRB, Abernethy DR, Altman RB, Brouwer KLR, Califano A, et al. Quantitative and systems pharmacology in the post-genomic era: new approaches to discovering drugs and understanding therapeutic mechanisms. An NIH White Paper by the QSP Workshop Group, 2011. https://www.nigms.nih.gov/training/documents/systemspharmawpsorger2011.pdf. 2011

  28. Wang Y, Zhu H, Madabushi R, Liu Q, Huang SM, Zineh I. Model-informed drug development: current US regulatory practice and future considerations. Clin Pharmacol Ther. 2019;105(4):899–911. https://doi.org/10.1002/cpt.1363.

    Article  PubMed  Google Scholar 

  29. Fang L, Kim MJ, Li Z, Wang Y, DiLiberti CE, Au J, et al. Model-informed drug development and review for generic products: summary of FDA public workshop. Clin Pharmacol Ther. 2018;104(1):27–30. https://doi.org/10.1002/cpt.1065.

    Article  PubMed  Google Scholar 

  30. Au JL, Badalament RA, Wientjes MG, Young DC, Warner JA, Venema PL, et al. Methods to improve efficacy of intravesical mitomycin C: results of a randomized phase III trial. J Natl Cancer Inst. 2001;93(8):597–604.

    Article  CAS  Google Scholar 

  31. Au JL, Badalament RA, Wientjes MG, Young D, Shen T, Venema PL, et al. Optimized intravesical mitomycin C treatment for superficial bladder cancer: long-term follow-up. J Urol. 2006;175(4):268.

    Article  Google Scholar 

  32. Gao X, Au JL, Badalament RA, Wientjes MG. Bladder tissue uptake of mitomycin C during intravesical therapy is linear with drug concentration in urine. Clin Cancer Res. 1998;4(1):139–43.

    CAS  PubMed  Google Scholar 

  33. Wientjes MG, Badalament RA, Au JL. Use of pharmacologic data and computer simulations to design an efficacy trial of intravesical mitomycin C therapy for superficial bladder cancer. Cancer Chemother Pharmacol. 1993;32(4):255–62.

    Article  CAS  Google Scholar 

  34. Au JL, Wientjes MG. Intravesical chemotherapy of superficial bladder cancer: optimization and novel agents. In: Lerner SP, Schoenberg MP, Sternberg CN, editors. Textbook of bladder cancer. Taylor & Francis; 2006. p. 341–52.

  35. Au JL, Lu Z, Abbiati RA, Wientjes MG. Systemic bioequivalence is unlikely to equal target site bioequivalence for nanotechnology oncologic products. AAPS J. 2019;21(2):24. https://doi.org/10.1208/s12248-019-0296-z.

    Article  PubMed  Google Scholar 

  36. Grant BD, Donaldson JG. Pathways and mechanisms of endocytic recycling. Nat Rev Mol Cell Biol. 2009;10(9):597–608. https://doi.org/10.1038/nrm2755.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Zhou F, Lee AC, Krafczyk K, Zhu L, Murray M. Protein kinase C regulates the internalization and function of the human organic anion transporting polypeptide 1A2. Br J Pharmacol. 2011;162(6):1380–8. https://doi.org/10.1111/j.1476-5381.2010.01144.x.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Mayati A, Moreau A, Le Vee M, Stieger B, Denizot C, Parmentier Y, et al. Protein kinases C-mediated regulations of drug transporter activity, localization and expression. Int J Mol Sci. 2017;18(4):1–22. https://doi.org/10.3390/ijms18040764.

    Article  CAS  Google Scholar 

  39. Hong M, Hong W, Ni C, Huang J, Zhou C. Protein kinase C affects the internalization and recycling of organic anion transporting polypeptide 1B1. Biochim Biophys Acta. 2015;1848(10 Pt A):2022–30. https://doi.org/10.1016/j.bbamem.2015.05.011.

    Article  CAS  PubMed  Google Scholar 

  40. Takada T, Suzuki H, Gotoh Y, Sugiyama Y. Regulation of the cell surface expression of human BCRP/ABCG2 by the phosphorylation state of Akt in polarized cells. Drug Metab Dispos. 2005;33(7):905–9. https://doi.org/10.1124/dmd.104.003228.

    Article  CAS  PubMed  Google Scholar 

  41. Chai J, Cai SY, Liu X, Lian W, Chen S, Zhang L, et al. Canalicular membrane MRP2/ABCC2 internalization is determined by Ezrin Thr567 phosphorylation in human obstructive cholestasis. J Hepatol. 2015;63(6):1440–8. https://doi.org/10.1016/j.jhep.2015.07.016.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Duan P, Li S, You G. Angiotensin II inhibits activity of human organic anion transporter 3 through activation of protein kinase Calpha: accelerating endocytosis of the transporter. Eur J Pharmacol. 2010;627(1–3):49–55. https://doi.org/10.1016/j.ejphar.2009.10.048.

    Article  CAS  PubMed  Google Scholar 

  43. Zhang Q, Hong M, Duan P, Pan Z, Ma J, You G. Organic anion transporter OAT1 undergoes constitutive and protein kinase C-regulated trafficking through a dynamin- and clathrin-dependent pathway. J Biol Chem. 2008;283(47):32570–9. https://doi.org/10.1074/jbc.M800298200.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Zhang Q, Pan Z, You G. Regulation of human organic anion transporter 4 by protein kinase C and NHERF-1: altering the endocytosis of the transporter. Pharm Res. 2010;27(4):589–96. https://doi.org/10.1007/s11095-009-9983-2.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Zhou F, Hong M, You G. Regulation of human organic anion transporter 4 by progesterone and protein kinase C in human placental BeWo cells. Am J Physiol Endocrinol Metab. 2007;293(1):E57–61. https://doi.org/10.1152/ajpendo.00696.2006.

    Article  CAS  PubMed  Google Scholar 

  46. Powell J, Farasyn T, Kock K, Meng X, Pahwa S, Brouwer KL, et al. Novel mechanism of impaired function of organic anion-transporting polypeptide 1B3 in human hepatocytes: post-translational regulation of OATP1B3 by protein kinase C activation. Drug Metab Dispos. 2014;42(11):1964–70. https://doi.org/10.1124/dmd.114.056945.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Glavy JS, Wu SM, Wang PJ, Orr GA, Wolkoff AW. Down-regulation by extracellular ATP of rat hepatocyte organic anion transport is mediated by serine phosphorylation of OATP1. J Biol Chem. 2000;275(2):1479–84.

    Article  CAS  Google Scholar 

  48. Hong WC, Amara SG. Differential targeting of the dopamine transporter to recycling or degradative pathways during amphetamine- or PKC-regulated endocytosis in dopamine neurons. FASEB J. 2013;27(8):2995–3007. https://doi.org/10.1096/fj.12-218727.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Kock K, Koenen A, Giese B, Fraunholz M, May K, Siegmund W, et al. Rapid modulation of the organic anion transporting polypeptide 2B1 (OATP2B1, SLCO2B1) function by protein kinase C-mediated internalization. J Biol Chem. 2010;285(15):11336–47. https://doi.org/10.1074/jbc.M109.056457.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Mnie-Filali O, Lau T, Matthaeus F, Abrial E, Delcourte S, El MM, et al. Protein kinases alter the allosteric modulation of the serotonin transporter in vivo and in vitro. CNS Neurosci Ther. 2016;22(8):691–9. https://doi.org/10.1111/cns.12562.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Rahbek-Clemmensen T, Bay T, Eriksen J, Gether U, Jorgensen TN. The serotonin transporter undergoes constitutive internalization and is primarily sorted to late endosomes and lysosomal degradation. J Biol Chem. 2014;289(33):23004–19. https://doi.org/10.1074/jbc.M113.495754.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Sun AQ, Ponamgi VM, Boyer JL, Suchy FJ. Membrane trafficking of the human organic anion-transporting polypeptide C (hOATPC). Pharm Res. 2008;25(2):463–74. https://doi.org/10.1007/s11095-007-9399-9.

    Article  CAS  PubMed  Google Scholar 

  53. Vina-Vilaseca A, Bender-Sigel J, Sorkina T, Closs EI, Sorkin A. Protein kinase C-dependent ubiquitination and clathrin-mediated endocytosis of the cationic amino acid transporter CAT-1. J Biol Chem. 2011;286(10):8697–706. https://doi.org/10.1074/jbc.M110.186858.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Wu S, Bellve KD, Fogarty KE, Melikian HE. Ack1 is a dopamine transporter endocytic brake that rescues a trafficking-dysregulated ADHD coding variant. Proc Natl Acad Sci U S A. 2015;112(50):15480–5. https://doi.org/10.1073/pnas.1512957112.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Taskar KS, Pilla Reddy V, Burt H, Posada MM, Varma M, Zheng M, et al. Physiologically-based pharmacokinetic models for evaluating membrane transporter mediated drug-drug interactions: current capabilities, case studies, future opportunities, and recommendations. Clin Pharmacol Ther. 2020;107(5):1082–115. https://doi.org/10.1002/cpt.1693.

    Article  PubMed  Google Scholar 

  56. Wang Q, Zheng M, Leil T. Investigating transporter-mediated drug-drug interactions using a physiologically based pharmacokinetic model of rosuvastatin. CPT Pharmacometrics Syst Pharmacol. 2017;6(4):228–38. https://doi.org/10.1002/psp4.12168.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Chen Y, Zhu R, Ma F, Mao J, Chen EC, Choo EF, et al. Assessment of OATP transporter-mediated drug-drug interaction using physiologically-based pharmacokinetic (PBPK) modeling - a case example. Biopharm Drug Dispos. 2018;39(9):420–30. https://doi.org/10.1002/bdd.2159.

    Article  CAS  PubMed  Google Scholar 

  58. Feng B, Varma MV. Evaluation and quantitative prediction of renal transporter-mediated drug-drug interactions. J Clin Pharmacol. 2016;56(Suppl 7):S110–21. https://doi.org/10.1002/jcph.702.

    Article  CAS  PubMed  Google Scholar 

  59. Yang Y, Li P, Zhang Z, Wang Z, Liu L, Liu X. Prediction of cyclosporin-mediated drug interaction using physiologically based pharmacokinetic model characterizing interplay of drug transporters and enzymes. Int J Mol Sci. 2020;21(19):7023. https://doi.org/10.3390/ijms21197023.

    Article  CAS  PubMed Central  Google Scholar 

  60. USFDA. In vitro metabolism- and transporter-mediated drug-drug interaction studies. Guidance for industry. 2017. https://www.fda.gov/media/108130/download.

  61. USFDA. Clinical drug interaction studies — study design, data analysis, and clinical implications guidance for industry. 2017. https://www.fda.gov/files/drugs/published/Clinical-Drug-Interaction-Studies-—-Study-Design--Data-Analysis--and-Clinical-Implications-Guidance-for-Industry.pdf.

  62. Maeda K. Organic anion transporting polypeptide (OATP)1B1 and OATP1B3 as important regulators of the pharmacokinetics of substrate drugs. Biol Pharm Bull. 2015;38(2):155–68. https://doi.org/10.1248/bpb.b14-00767.

    Article  CAS  PubMed  Google Scholar 

  63. Mahmutefendić H, Zagorac GB, Maćešić S, Lučin P. Rapid endosomal recycling. Peripheral membrane proteins. 2018. https://www.intechopen.com/chapters/60064. https://doi.org/10.5772/intechopen.75685.

  64. Au JL, Yeung BZ, Wientjes MG, Lu Z, Wientjes MG. Delivery of cancer therapeutics to extracellular and intracellular targets: determinants, barriers, challenges and opportunities. Adv Drug Deliv Rev. 2016;97:280–301. https://doi.org/10.1016/j.addr.2015.12.002.

    Article  CAS  PubMed  Google Scholar 

  65. Jung D, Hagenbuch B, Gresh L, Pontoglio M, Meier PJ, Kullak-Ublick GA. Characterization of the human OATP-C (SLC21A6) gene promoter and regulation of liver-specific OATP genes by hepatocyte nuclear factor 1 alpha. J Biol Chem. 2001;276(40):37206–14. https://doi.org/10.1074/jbc.M103988200.

    Article  CAS  PubMed  Google Scholar 

  66. Yao J, Hong W, Huang J, Zhan K, Huang H, Hong M. N-glycosylation dictates proper processing of organic anion transporting polypeptide 1B1. PLoS ONE. 2012;7(12):e52563. https://doi.org/10.1371/journal.pone.0052563.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Murk JL, Stoorvogel W, Kleijmeer MJ, Geuze HJ. The plasticity of multivesicular bodies and the regulation of antigen presentation. Semin Cell Dev Biol. 2002;13(4):303–11. https://doi.org/10.1016/s1084952102000605.

    Article  CAS  PubMed  Google Scholar 

  68. Russell MR, Nickerson DP, Odorizzi G. Molecular mechanisms of late endosome morphology, identity and sorting. Curr Opin Cell Biol. 2006;18(4):422–8. https://doi.org/10.1016/j.ceb.2006.06.002.

    Article  CAS  PubMed  Google Scholar 

  69. Saksena S, Sun J, Chu T, Emr SD. ESCRTing proteins in the endocytic pathway. Trends Biochem Sci. 2007;32(12):561–73. https://doi.org/10.1016/j.tibs.2007.09.010.

    Article  CAS  PubMed  Google Scholar 

  70. van Meel E, Klumperman J. Imaging and imagination: understanding the endo-lysosomal system. Histochem Cell Biol. 2008;129(3):253–66. https://doi.org/10.1007/s00418-008-0384-0.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Williams RL, Urbe S. The emerging shape of the ESCRT machinery. Nat Rev Mol Cell Biol. 2007;8(5):355–68. https://doi.org/10.1038/nrm2162.

    Article  CAS  PubMed  Google Scholar 

  72. Jung D, Podvinec M, Meyer UA, Mangelsdorf DJ, Fried M, Meier PJ, et al. Human organic anion transporting polypeptide 8 promoter is transactivated by the farnesoid X receptor/bile acid receptor. Gastroenterology. 2002;122(7):1954–66.

    Article  CAS  Google Scholar 

  73. Konig J, Cui Y, Nies AT, Keppler D. A novel human organic anion transporting polypeptide localized to the basolateral hepatocyte membrane. Am J Physiol Gastrointest Liver Physiol. 2000;278(1):G156–64.

    Article  CAS  Google Scholar 

  74. Clarke JD, Novak P, Lake AD, Hardwick RN, Cherrington NJ. Impaired N-linked glycosylation of uptake and efflux transporters in human non-alcoholic fatty liver disease. Liver Int. 2017;37(7):1074–81. https://doi.org/10.1111/liv.13362.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Rothman S. How is the balance between protein synthesis and degradation achieved? Theor Biol Med Model. 2010;7:25. https://doi.org/10.1186/1742-4682-7-25.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Millward DJ, Bates PC, Rosochacki S. The extent and nature of protein degradation in the tissues during development. Reprod Nutr Dev. 1981;21(2):265–77. https://doi.org/10.1051/rnd:19810210.

    Article  CAS  PubMed  Google Scholar 

  77. Arias IM, Doyle D, Schimke RT. Studies on the synthesis and degradation of proteins of the endoplasmic reticulum of rat liver. J Biol Chem. 1969;244(12):3303–15.

    Article  CAS  Google Scholar 

  78. Barle H, Nyberg B, Essen P, Andersson K, McNurlan MA, Wernerman J, et al. The synthesis rates of total liver protein and plasma albumin determined simultaneously in vivo in humans. Hepatology. 1997;25(1):154–8. https://doi.org/10.1002/hep.510250128.

    Article  CAS  PubMed  Google Scholar 

  79. Kimoto E, Yoshida K, Balogh LM, Bi YA, Maeda K, El-Kattan A, et al. Characterization of organic anion transporting polypeptide (OATP) expression and its functional contribution to the uptake of substrates in human hepatocytes. Mol Pharm. 2012;9(12):3535–42. https://doi.org/10.1021/mp300379q.

    Article  CAS  PubMed  Google Scholar 

  80. Varma MV, Lai Y, Feng B, Litchfield J, Goosen TC, Bergman A. Physiologically based modeling of pravastatin transporter-mediated hepatobiliary disposition and drug-drug interactions. Pharm Res. 2012;29(10):2860–73. https://doi.org/10.1007/s11095-012-0792-7.

    Article  CAS  PubMed  Google Scholar 

  81. Murray M, Zhou F. Trafficking and other regulatory mechanisms for organic anion transporting polypeptides and organic anion transporters that modulate cellular drug and xenobiotic influx and that are dysregulated in disease. Br J Pharmacol. 2017;174(13):1908–24. https://doi.org/10.1111/bph.13785.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Leonhardt M, Keiser M, Oswald S, Kuhn J, Jia J, Grube M, et al. Hepatic uptake of the magnetic resonance imaging contrast agent Gd-EOB-DTPA: role of human organic anion transporters. Drug Metab Dispos. 2010;38(7):1024–8. https://doi.org/10.1124/dmd.110.032862.

    Article  CAS  PubMed  Google Scholar 

  83. Sai Y, Kaneko Y, Ito S, Mitsuoka K, Kato Y, Tamai I, et al. Predominant contribution of organic anion transporting polypeptide OATP-B (OATP2B1) to apical uptake of estrone-3-sulfate by human intestinal Caco-2 cells. Drug Metab Dispos. 2006;34(8):1423–31. https://doi.org/10.1124/dmd.106.009530.

    Article  CAS  PubMed  Google Scholar 

  84. Huotari J, Helenius A. Endosome maturation. EMBO J. 2011;30(17):3481–500. https://doi.org/10.1038/emboj.2011.286.

    Article  CAS  Google Scholar 

  85. Mateus A. Intracellular unbound drug concentrations. Methodology and application for understanding cellular drug exposure. Digital comprehensive summaries of Uppsala dissertations: Upsala, Sweden; 2016. https://uu.diva-portal.org/smash/get/diva2:908586/FULLTEXT01.pdf.

  86. Eytan GD, Regev R, Oren G, Assaraf YG. The role of passive transbilayer drug movement in multidrug resistance and its modulation. J Biol Chem. 1996;271(22):12897–902. https://doi.org/10.1074/jbc.271.22.12897.

    Article  CAS  PubMed  Google Scholar 

  87. Mathieson T, Franken H, Kosinski J, Kurzawa N, Zinn N, Sweetman G, et al. Systematic analysis of protein turnover in primary cells. Nat Commun. 2018;9(1):689. https://doi.org/10.1038/s41467-018-03106-1.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Funding

Supported in part by research grants from NIH (R01CA163015, R01EB015253) and FDA (20919IPAAU, 20919IPAWIENTJES), the Mosier Endowed Chair in Pharmaceutical Sciences at University of Oklahoma Health Sciences Center, and the Chair in Systems Pharmacology at Taipei Medical University.

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J.L.-S.A. designed the scientific approach, contributed to the interpretation of simulation results, and wrote the manuscript. R.A.A. and M.G.W. formalized and implemented the model, executed simulations, contributed to the interpretation of simulation results, and contributed to manuscript writing.

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Correspondence to Jessie L.-S. Au.

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Abbiati, R.A., Wientjes, M.G. & Au, J.LS. Is It Time to Use Modeling of Cellular Transporter Homeostasis to Inform Drug-Drug Interaction Studies: Theoretical Considerations. AAPS J 23, 102 (2021). https://doi.org/10.1208/s12248-021-00635-4

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