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Review

Hepatic transporter drug-drug interactions: an evaluation of approaches and methodologies

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Pages 1237-1250 | Received 27 Aug 2017, Accepted 08 Nov 2017, Published online: 23 Nov 2017

References

  • Hay M, Thomas DW, Craighead JL, et al. Clinical development success rates for investigational drugs. Nat Biotech [Internet]. 2014;32:40–51. Available from http://www.ncbi.nlm.nih.gov/pubmed/24406927%0Ahttp://dx.doi.org/10.1038/nbt.2786%5Cn10.1038/nbt.2786%5Cnhttp://www.nature.com/nbt/journal/v32/n1/abs/nbt.2786.html#supplementary-information.
  • Waring MJ, Arrowsmith J, Leach AR, et al. An analysis of the attrition of drug candidates from four major pharmaceutical companies. Nat Rev Drug Discov. 2015;14:475–486.
  • Chung TDY, Terry DB, Smith LH. In vitro and in vivo assessment of ADME and PK properties during lead selection and lead optimization – Guidelines, Benchmarks and Rules of Thumb. 2015 Sep 9. In: Sittampalam GS, Coussens NP, Brimacombe K, et al., editors. Assay Guidance Manual [Internet]. Bethesda (MD): Eli Lilly & Company and the National Center for Advancing Translational Sciences; 2004-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK326710/
  • Riley RJ, Wilson CE. Cytochrome P450 time-dependent inhibition and induction: advances in assays, risk analysis and modelling. Expert Opin Drug Metab Toxicol. 2015;11:557–572.
  • Dumbreck S, Flynn A, Nairn M, et al. Drug-disease and drug-drug interactions: systematic examination of recommendations in 12 UK national clinical guidelines. BMJ [Internet]. 2015;350. Available from: http://www.bmj.com/content/350/bmj.h949
  • Leape LL, Bates DW, Cullen DJ, et al. Systems analysis of adverse drug events. ADE Prevention Study Group. [Internet]. JAMA. 1995;274:35–43. Available from: http://www.ncbi.nlm.nih.gov/pubmed/7791256
  • Giacomini KM, Huang S-M, Tweedie DJ, et al. Membrane transporters in drug development. Nat Rev Drug Discov. 2010;9:215–236.
  • Stieger B, Hagenbuch B. Recent advances in understanding hepatic drug transport. F1000Research. 2016;5:2465.
  • Riley RJ, Foley SA, Barton P, et al. Hepatic drug transporters: the journey so far. Expert Opin Drug Metab Toxicol. 2016;12:201–216.
  • Fahmi OA, Maurer TS, Kish M, et al. A combined model for predicting CYP3A4 clinical net drug-drug interaction based on CYP3a4 inhibition, inactivation, and induction determined in vitro. Drug Metab Dispos. 2008;36:1698–1708.
  • Vieira MLT, Kirby B, Ragueneau-Majlessi I, et al. Evaluation of various static in vitro–in vivo extrapolation models for risk assessment of the CYP3A inhibition potential of an investigational drug. Clin Pharmacol Ther. 2014;95:189–198.
  • Holdgate GA, Gill AL. Kinetic efficiency: the missing metric for enhancing compound quality? Drug Discov Today. 2011;16:910–913.
  • Beaumont K, Schmid E, Smith DA. Oral delivery of G protein-coupled receptor modulators: an explanation for the observed class difference. Bioorganic Med Chem Lett. 2005;15:3658–3664.
  • DeWire SM, Ahn S, Lefkowitz RJ, et al. Beta-arrestins and cell signaling. Annu Rev Physiol. 2007;69:483–510.
  • Wu CY, Benet LZ. Predicting drug disposition via application of BCS: transport/absorption/elimination interplay and development of a biopharmaceutics drug disposition classification system. Pharm Res. 2005;22:11–23.
  • Hosey CM, Chan R, Benet LZ. BDDCS predictions, self-correcting aspects of BDDCS assignments, BDDCS assignment corrections, and classification for more than 175 additional drugs. AAPS J. 2016;18:251–260.
  • Barton P, Riley RJ. A new paradigm for navigating compound property related drug attrition. Drug Discov Today. 2016;21:72–81.
  • 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;91:1053–1064.
  • EMA. Guideline on the investigation of drug interactions. Guid Doc [Internet]. 2012;59. Available from: http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2012/07/WC500129606.pdf
  • FDA. Guidance for industry. Drug interaction studies study design, data analysis, implications for dosing, and labeling recommendations. Guid Doc. 2012;79. Available from: https://www.fda.gov/downloads/drugs/guidances/ucm292362.pdf
  • Vaidyanathan J, Yoshida K, Arya V, et al. 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:S59–S72.
  • Mcfadden B, Heitzman-Powell L. What do drug transporters really do? Nat Rev Drug Discov. 2015;8:1699–1712.
  • Roth M, Obaidat A, Hagenbuch B. OATPs, OATs and OCTs: the organic anion and cation transporters of the SLCO and SLC22A gene superfamilies. Br J Pharmacol. 2012;165:1260–1287.
  • Gui C, Obaidat A, Chaguturu R, et al. Development of a cell-based high-throughput assay to screen for inhibitors of organic anion transporting polypeptides 1B1 and 1B3. Curr Chem Genomics. 2010;4:1–8.
  • Ito K, Brown HS, Houston JB. Database analyses for the prediction of in vivo drug-drug interactions from in vitro data. Br J Clin Pharmacol. 2004;57:473–486.
  • Obach RS, Walsky RL, Venkatakrishnan K. Mechanism-based inactivation of human cytochrome p450 enzymes and the prediction of drug-drug interactions. Drug Metab Dispos. 2007;35:246–255.
  • Zhang L, Zhang YD, Strong JM, et al. A regulatory viewpoint on transporter-based drug interactions. Xenobiotica. 2008;38:709–724.
  • Li AP. Drug-drug interactions in pharmaceutical development [Internet]. Drug-Drug Interact Pharm Dev. 2007. Available from: http://www.scopus.com/inward/record.url?eid=2-s2.0-84889475717&partnerID=40&md5=b7b3325577b70fa50dbb414538ac90e1
  • Chu X, Korzekwa K, Elsby R, et al. Intracellular drug concentrations and transporters: measurement, modeling, and implications for the liver. Clin Pharmacol Ther. 2013;94:126–141.
  • Culm-Merdek KE, Von Moltke LL, Harmatz JS, et al. Fluvoxamine impairs single-dose caffeine clearance without altering caffeine pharmacodynamics. Br J Clin Pharmacol. 2005;60:486–493.
  • Varma MV, Bi YA, Kimoto E, et al. Quantitative prediction of transporter- and enzyme-mediated clinical drug-drug interactions of organic anion-transporting polypeptide 1B1 substrates using a mechanistic net-effect model. J Pharmacol Exp Ther. 2014;351:214–223.
  • Hu Z-Y. Disposition pathway-dependent approach for predicting organic anion-transporting polypeptide-mediated drug–drug interactions. Clin Pharmacokinet. 2013;52:433–441.
  • Elsby R, Hilgendorf C, Fenner K. Understanding the critical disposition pathways of statins to assess drug–drug interaction risk during drug development: it’s not just about OATP1B1. Clin Pharmacol Ther. 2012;92:584–598.
  • Guest EJ, Rowland-Yeo K, Rostami-Hodjegan A, et al. Assessment of algorithms for predicting drug-drug interactions via inhibition mechanisms: comparison of dynamic and static models. Br J Clin Pharmacol. 2011;71:72–87.
  • Fahmi OA, Hurst S, Plowchalk D, et al. Comparison of different algorithms for predicting clinical drug-drug interactions, based on the use of CYP3A4 in vitro data: predictions of compounds as precipitants of interaction. Drug Metab Dispos. 2009;37:1658–1666.
  • Watanabe T, Kusuhara H, Sugiyama Y. Application of physiologically based pharmacokinetic modeling and clearance concept to drugs showing transporter-mediated distribution and clearance in humans. J Pharmacokinet Pharmacodyn. 2010;37:575–590.
  • Jamei M, Marciniak S, Feng K, et al. The Simcyp® population-based ADME simulator. Expert Opin Drug Metab Toxicol. 2009;5:211–223.
  • Giavarina D. Understanding Bland Altman analysis. Biochem Medica. 2015;25:141–151.
  • Zamek-Gliszczynski MJ, Kalvass JC, Pollack GM, et al. Relationship between Drug/Metabolite Exposure and Impairment of Excretory Transport Function. Drug Metab. Dispos. [Internet]. 2009;37:386–390. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2680528/
  • Binet I, Wallnöfer A, Weber C, et al. Renal hemodynamics and pharmacokinetics of bosentan with and without cyclosporine A. Kidney Int. 2000;57:224–231.
  • Treiber A, Schneiter R, Delahaye S, et al. Inhibition of organic anion transporting polypeptide-mediated hepatic uptake is the major determinant in the pharmacokinetic interaction between bosentan and cyclosporin A in the rat. J Pharmacol Exp Ther. 2004;308:1121–1129.
  • Williamson B, Soars AC, Owen A, et al. Dissecting the relative contribution of OATP1B1-mediated uptake of xenobiotics into human hepatocytes using siRNA. Xenobiotica. 2013;43:920–931.
  • Brown HS, Galetin A, Hallifax D, et al. Prediction of in vivo drug-drug interactions from in vitro data: factors affecting prototypic drug-drug interactions involving CYP2C9, CYP2D6 and CYP3A4. Clin Pharmacokinet. 2006;45:1035–1050.
  • Oliver RE, Jones AF, Rowland M. A whole-body physiologically based pharmacokinetic model incorporating dispersion concepts: short and long time characteristics. J Pharmacokinet Pharmacodyn. 2001;28:27–55.
  • Ridgway D, Tuszynski JA, Tam YK. Reassessing models of hepatic extraction. J Biol Phys. 2003;29:1–21.
  • Riccardi K, Lin J, Li Z, et al. Novel method to predict in vivo liver-to-plasma Kpuu for OATP substrates using suspension hepatocytes. Drug Metab Dispos. 2017;45:576–580.
  • Rostami-Hodjegan A, Tucker G. “In silico” simulations to assess the “in vivo” consequences of “in vitro” metabolic drug-drug interactions. Drug Discov Today Technol. 2004;1:441–448.
  • Tachibana T, Kato M, Watanabe T, et al. Method for predicting the risk of drug–drug interactions involving inhibition of intestinal CYP3A4 and P-glycoprotein. Xenobiotica. 2009;39:430–443.
  • Fenner K, Troutman M, Kempshall S, et al. Drug–drug interactions mediated through P-glycoprotein: clinical relevance and in vitro–in vivo correlation using digoxin as a probe drug. Clin Pharmacol Ther. 2009;85:173–181.
  • Sinha VK, Snoeys J, Osselaer NV, et al. From preclinical to human – prediction of oral absorption and drug–drug interaction potential using physiologically based pharmacokinetic (PBPK) modeling approach in an industrial setting: a workflow by using case example. Biopharm Drug Dispos. 2012;33:111–121.
  • De Bruyn T, Stieger B, Augustijns PF, et al. Clearance prediction of HIV protease inhibitors in man: role of hepatic uptake. J Pharm Sci. 2016;105:854–863.
  • Obach RS. The utility of in vitro cytochrome P450 inhibition data in the prediction of drug-drug interactions. J Pharmacol Exp Ther. 2005;316:336–348.
  • O’Keeffe AG, Nazareth I, Petersen I. Time trends in the prescription of statins for the primary prevention of cardiovascular disease in the United Kingdom: a cohort study using The Health Improvement Network primary care data. Clin Epidemiol. 2016;8:123–132.
  • Gu Q, Paulose-Ram R, Burt V, et al. Prescription cholesterol-lowering medication use in adults aged 40 and over: United States, 2003 – 2012. [Internet]. NCHS Data Brief. 2017. Available from: http://www.cdc.gov/nchs/data/databriefs/db177.pdf
  • Köck K, Ferslew BC, Netterberg I, et al. Risk factors for development of cholestatic drug-induced liver injury: inhibition of hepatic basolateral bile acid transporters multidrug resistance-associated proteins 3 and 4. Drug Metab Dispos. 2014;42:665–674.
  • Di L, Atkinson K, Orozco CC, et al. In vitro–in vivo correlation for low-clearance compounds using hepatocyte relay method. Drug Metab Dispos. 2013;41:2018 LP–2023.
  • König J, Müller F, Fromm MF. Transporters and drug-drug interactions: important determinants of drug disposition and effects. Michel MC, Editor Pharmacol Rev. 2013;65:944 LP–966.
  • Meanwell NA. Improving drug design: an update on recent applications of efficiency metrics, strategies for replacing problematic elements, and compounds in nontraditional drug space. Chem Res Toxicol. 2016;29:564–616.
  • Schuetz JD, Swaan PW, Tweedie DJ. The role of transporters in toxicity and disease. Drug Metab Dispos. 2014;42:541–545.

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