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Current Drug Metabolism

Editor-in-Chief

ISSN (Print): 1389-2002
ISSN (Online): 1875-5453

Perspective

2020 FDA Drug-drug Interaction Guidance: A Comparison Analysis and Action Plan by Pharmaceutical Industrial Scientists

Author(s): Sirimas Sudsakorn, Praveen Bahadduri, Jennifer Fretland and Chuang Lu*

Volume 21, Issue 6, 2020

Page: [403 - 426] Pages: 24

DOI: 10.2174/1389200221666200620210522

Price: $65

Abstract

Background: In January 2020, the US FDA published two final guidelines, one entitled “In vitro Drug Interaction Studies - Cytochrome P450 Enzyme- and Transporter-Mediated Drug Interactions Guidance for Industry” and the other entitled “Clinical Drug Interaction Studies - Cytochrome P450 Enzyme- and Transporter-Mediated Drug Interactions Guidance for Industry”. These were updated from the 2017 draft in vitro and clinical DDI guidance.

Methods: This study is aimed to provide an analysis of the updates along with a comparison of the DDI guidelines published by the European Medicines Agency (EMA) and Japanese Pharmaceuticals and Medical Devices Agency (PMDA) along with the current literature.

Results: The updates were provided in the final FDA DDI guidelines and explained the rationale of those changes based on the understanding from research and literature. Furthermore, a comparison among the FDA, EMA, and PMDA DDI guidelines are presented in Tables 1, 2 and 3.

Conclusion: The new 2020 clinical DDI guidance from the FDA now has even higher harmonization with the guidance (or guidelines) from the EMA and PMDA. A comparison of DDI guidance from the FDA 2017, 2020, EMA, and PMDA on CYP and transporter based DDI, mathematical models, PBPK, and clinical evaluation of DDI is presented in this review.

Keywords: Cytochrome P450, CYP, transporter, DDI, PK interaction, clinical DDI risk, PBPK, in vitro assay.

Graphical Abstract

[1]
Zhang, D.; Gang, L.; Ding, X.; Lu, C. Preclinical experimental models of drug metabolism and disposition in drug discovery and development. Acta Pharm. Sin. B, 2012, 2(6), 549-561.
[http://dx.doi.org/10.1016/j.apsb.2012.10.004]
[2]
Lu, C.; Di, L. In vitro and in vivo methods to assess pharmacokinetic drug- drug interactions in drug discovery and development. Biopharm. Drug Dispos., 2020, 41(1-2), 3-31.
[http://dx.doi.org/10.1002/bdd.2212] [PMID: 31778578]
[3]
Di, L.; Kerns, E.H. Application of pharmaceutical profiling assays for optimization of drug-like properties. Curr. Opin. Drug Discov. Devel., 2005, 8(4), 495-504.
[PMID: 16022186]
[4]
U. S. Food and Drug Administration. FDA Center for Drug Evaluation and Research, Guidance for Industry; Clinical drug interaction studies - Cytochrome P450 Enzyme and Transportermediated drug interactions, . 2020.https://www.fda.gov/media/134581/download
[5]
U. S. Food and Drug Administration. FDA. Center for Drug Evaluation and Research, Guidance for Industry; In vitro drug interaction studies - Cytochrome P450 Enzyme and Transportermediated drug interactions. 2020.https://www.fda.gov/media/134582/download
[6]
Pharmaceuticals and Medical Devices Agency of Japan. PMDA. Guideline on drug interaction for drug development and appropriate provision of information,. 2019.http://www.pmda.go.jp/files/000228122.pdf
[7]
U. S. Food and Drug Administration. FDA. Center for Drug Evaluation and Research, Guidance for Industry; Clinical Drug Interactions Studies - Study Design, Data Analysis, and Clinical Implications, Guidance for Industry. Draft Guidance,. 2017.https://www.fda.gov/files/drugs/published/Clinical-Drug-Interaction-Studies-%E2%80%94-Study-Design--Data-Analysis--and-Clinical-Implications-Guidance-for-Industry.pdf
[8]
European Medicines Agency. EMA. Concept paper on a revision of the guideline on the investigation of drug interactions, . 2017.https://www.ema.europa.eu/en/documents/scientific-guideline/con-cept-paper-revision-guideline-investigation-drug-interactions_en.pdf
[9]
U. S. Food and Drug Administration. FDA. Center for Drug Evaluation and Research, Guidance for Industry; In vitro metabolism- and transporter- mediated drug-drug interaction studies, Guidance for Industry, Draft Guidance,. 2017.https://www.fda.gov/files/drugs/published/In-Vitro-Metabolism--and-Transporter--Mediated-Drug-Drug-Interaction-Studies-Guidance-for-Industry.pdf
[10]
European Medicines AgencyEMA. Guideline on the Investigation od Drug Interactions Final,. 2013.https://www.ema.europa.eu/en/documents/scientific-guideline/guide-line-investigation-drug-interactions_en.pdf
[11]
Tweedie, D.; Polli, J.W.; Berglund, E.G.; Huang, S.M.; Zhang, L.; Poirier, A.; Chu, X.; Feng, B. International Transporter Consortium. 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), 113-125.
[http://dx.doi.org/10.1038/clpt.2013.77] [PMID: 23588318]
[12]
Kenny, J.R.; Ramsden, D.; Buckley, D.B.; Dallas, S.; Fung, C.; Mohutsky, M.; Einolf, H.J.; Chen, L.; Dekeyser, J.G.; Fitzgerald, M.; Goosen, T.C.; Siu, Y.A.; Walsky, R.L.; Zhang, G.; Tweedie, D.; Hariparsad, N. Considerations from the innovation and quality induction working group in response to drug-drug interaction guidances from regulatory agencies: focus on CYP3A4 mRNA in vitro response thresholds, variability, and clinical relevance. Drug Metab. Dispos., 2018, 46(9), 1285-1303.
[http://dx.doi.org/10.1124/dmd.118.081927] [PMID: 29959133]
[13]
Grimm, S.W.; Einolf, H.J.; Hall, S.D.; He, K.; Lim, H.K.; Ling, K.H.; Lu, C.; Nomeir, A.A.; Seibert, E.; Skordos, K.W.; Tonn, G.R.; Van Horn, R.; Wang, R.W.; Wong, Y.N.; Yang, T.J.; Obach, R.S. The conduct of in vitro studies to address time-dependent inhibition of drug-metabolizing enzymes: a perspective of the pharmaceutical research and manufacturers of America. Drug Metab. Dispos., 2009, 37(7), 1355-1370.
[http://dx.doi.org/10.1124/dmd.109.026716] [PMID: 19359406]
[14]
Bohnert, T.; Patel, A.; Templeton, I.; Chen, Y.; Lu, C.; Lai, G.; Leung, L.; Tse, S.; Einolf, H.J.; Wang, Y.H.; Sinz, M.; Stearns, R.; Walsky, R.; Geng, W.; Sudsakorn, S.; Moore, D.; He, L.; Wahlstrom, J.; Keirns, J.; Narayanan, R.; Lang, D.; Yang, X. International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) Victim Drug-Drug Interactions Working Group. Evaluation of a new molecular entity as a victim of metabolic drug-drug interactions-an industry perspective. Drug Metab. Dispos., 2016, 44(8), 1399-1423.
[http://dx.doi.org/10.1124/dmd.115.069096] [PMID: 27052879]
[15]
Bjornsson, T.D.; Callaghan, J.T.; Einolf, H.J.; Fischer, V.; Gan, L.; Grimm, S.; Kao, J.; King, S.P.; Miwa, G.; Ni, L.; Kumar, G.; McLeod, J.; Obach, S.R.; Roberts, S.; Roe, A.; Shah, A.; Snikeris, F.; Sullivan, J.T.; Tweedie, D.; Vega, J.M.; Walsh, J.; Wrighton, S.A.; Pharmaceutical, R. Pharmaceutical Research and Manufacturers of America Drug Metabolism/Clinical Pharmacology Technical Working Groups. The conduct of in vitro and in vivo drug-drug interaction studies: a PhRMA perspective. J. Clin. Pharmacol., 2003, 43(5), 443-469.
[http://dx.doi.org/10.1177/0091270003252519] [PMID: 12751267]
[16]
Vieira, M.L.; Kirby, B.; Ragueneau-Majlessi, I.; Galetin, A.; Chien, J.Y.; Einolf, H.J.; Fahmi, O.A.; Fischer, V.; Fretland, A.; Grime, K.; Hall, S.D.; Higgs, R.; Plowchalk, D.; Riley, R.; Seibert, E.; Skordos, K.; Snoeys, J.; Venkatakrishnan, K.; Waterhouse, T.; Obach, R.S.; Berglund, E.G.; Zhang, L.; Zhao, P.; Reynolds, K.S.; Huang, S.M. 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(2), 189-198.
[http://dx.doi.org/10.1038/clpt.2013.187] [PMID: 24048277]
[17]
Tachibana, T.; Kato, M.; Watanabe, T.; Mitsui, T.; Sugiyama, Y. Method for predicting the risk of drug-drug interactions involving inhibition of intestinal CYP3A4 and P-glycoprotein. Xenobiotica, 2009, 39(6), 430-443.
[http://dx.doi.org/10.1080/00498250902846252] [PMID: 19480549]
[18]
Fahmi, O.A.; Ripp, S.L. Evaluation of models for predicting drug-drug interactions due to induction. Expert Opin. Drug Metab. Toxicol., 2010, 6(11), 1399-1416.
[http://dx.doi.org/10.1517/17425255.2010.516251] [PMID: 20955108]
[19]
Burk, O.; Koch, I.; Raucy, J.; Hustert, E.; Eichelbaum, M.; Brockmöller, J.; Zanger, U.M.; Wojnowski, L. The induction of cytochrome P450 3A5 (CYP3A5) in the human liver and intestine is mediated by the xenobiotic sensors pregnane X receptor (PXR) and constitutively activated receptor (CAR). J. Biol. Chem., 2004, 279(37), 38379-38385.
[http://dx.doi.org/10.1074/jbc.M404949200] [PMID: 15252010]
[20]
Sager, J.E.; Tripathy, S.; Price, L.S.; Nath, A.; Chang, J.; Stephenson-Famy, A.; Isoherranen, N. In vitro to in vivo extrapolation of the complex drug-drug interaction of bupropion and its metabolites with CYP2D6; simultaneous reversible inhibition and CYP2D6 downregulation. Biochem. Pharmacol., 2017, 123, 85-96.
[http://dx.doi.org/10.1016/j.bcp.2016.11.007] [PMID: 27836670]
[21]
Do, M.T.; Kim, H.G.; Tran, T.T.; Khanal, T.; Choi, J.H.; Chung, Y.C.; Jeong, T.C.; Jeong, H.G. Metformin suppresses CYP1A1 and CYP1B1 expression in breast cancer cells by down-regulating aryl hydrocarbon receptor expression. Toxicol. Appl. Pharmacol., 2014, 280(1), 138-148.
[http://dx.doi.org/10.1016/j.taap.2014.07.021] [PMID: 25110054]
[22]
Wollmann, B.M.; Syversen, S.W.; Vistnes, M.; Lie, E.; Mehus, L.L.; Molden, E. Associations between cytokine levels and CYP3A4 phenotype in patients with rheumatoid arthritis. Drug Metab. Dispos., 2018, 46(10), 1384-1389.
[http://dx.doi.org/10.1124/dmd.118.082065] [PMID: 29991576]
[23]
Le Vee, M.; Lecureur, V.; Stieger, B.; Fardel, O. Regulation of drug transporter expression in human hepatocytes exposed to the proinflammatory cytokines tumor necrosis factor-alpha or interleukin-6. Drug Metab. Dispos., 2009, 37(3), 685-693.
[http://dx.doi.org/10.1124/dmd.108.023630] [PMID: 19074973]
[24]
Kalvass, J.C.; Phipps, C.; Jenkins, G.J.; Stuart, P.; Zhang, X.; Heinle, L.; Nijsen, M.J.M.A.; Fischer, V. Mathematical and experimental validation of flux dialysis method: an improved approach to measure unbound fraction for compounds with high protein binding and other challenging properties. Drug Metab. Dispos., 2018, 46(4), 458-469.
[http://dx.doi.org/10.1124/dmd.117.078915] [PMID: 29437872]
[25]
Nakajima, M.; Fukami, T.; Yamanaka, H.; Higashi, E.; Sakai, H.; Yoshida, R.; Kwon, J.T.; McLeod, H.L.; Yokoi, T. Comprehensive evaluation of variability in nicotine metabolism and CYP2A6 polymorphic alleles in four ethnic populations. Clin. Pharmacol. Ther., 2006, 80(3), 282-297.
[http://dx.doi.org/10.1016/j.clpt.2006.05.012] [PMID: 16952495]
[26]
Tanner, J.A.; Tyndale, R.F. Variation in CYP2A6 activity and personalized medicine. J. Pers. Med., 2017, 7(4)E18
[http://dx.doi.org/10.3390/jpm7040018] [PMID: 29194389]
[27]
Zanger, U.M.; Schwab, M. Cytochrome P450 enzymes in drug metabolism: regulation of gene expression, enzyme activities, and impact of genetic variation. Pharmacol. Ther., 2013, 138(1), 103-141.
[http://dx.doi.org/10.1016/j.pharmthera.2012.12.007] [PMID: 23333322]
[28]
Matsumoto, S.; Hirama, T.; Matsubara, T.; Nagata, K.; Yamazoe, Y. Involvement of CYP2J2 on the intestinal first-pass metabolism of antihistamine drug, astemizole. Drug Metab. Dispos., 2002, 30(11), 1240-1245.
[http://dx.doi.org/10.1124/dmd.30.11.1240] [PMID: 12386130]
[29]
Michaels, S.; Wang, M.Z. The revised human liver cytochrome P450 “Pie”: absolute protein quantification of CYP4F and CYP3A enzymes using targeted quantitative proteomics. Drug Metab. Dispos., 2014, 42(8), 1241-1251.
[http://dx.doi.org/10.1124/dmd.114.058040] [PMID: 24816681]
[30]
Caldwell, M.D.; Awad, T.; Johnson, J.A.; Gage, B.F.; Falkowski, M.; Gardina, P.; Hubbard, J.; Turpaz, Y.; Langaee, T.Y.; Eby, C.; King, C.R.; Brower, A.; Schmelzer, J.R.; Glurich, I.; Vidaillet, H.J.; Yale, S.H.; Qi, Zhang. K.; Berg, R.L.; Burmester, J.K. CYP4F2 genetic variant alters required warfarin dose. Blood, 2008, 111(8), 4106-4112.
[http://dx.doi.org/10.1182/blood-2007-11-122010] [PMID: 18250228]
[31]
Kudzi, W.; Ahorhorlu, S.Y.; Dzudzor, B.; Olayemi, E.; Nartey, E.T.; Asmah, R.H. Genetic polymorphisms of patients on stable warfarin maintenance therapy in a Ghanaian population. BMC Res. Notes, 2016, 9(1), 507.
[http://dx.doi.org/10.1186/s13104-016-2306-x] [PMID: 27938396]
[32]
Takeuchi, M.; Kobayashi, T.; Biss, T.; Kamali, F.; Vear, S.I.; Ho, R.H.; Bajolle, F.; Loriot, M.A.; Shaw, K.; Carleton, B.C.; Hamberg, A.K.; Wadelius, M.; Hirono, K.; Taguchi, M.; Wakamiya, T.; Yanagimachi, M.; Hirai, K.; Itoh, K.; Brandao, L.R.; Ito, S. CYP2C9, VKORC1, and CYP4F2 polymorphisms and pediatric warfarin maintenance dose: a systematic review and meta-analysis. Pharmacogenomics J., 2019.
[PMID: 31673144]
[33]
Gurley, B.J.; Gardner, S.F.; Hubbard, M.A.; Williams, D.K.; Gentry, W.B.; Khan, I.A.; Shah, A. In vivo effects of goldenseal, kava kava, black cohosh, and valerian on human cytochrome P450 1A2, 2D6, 2E1, and 3A4/5 phenotypes. Clin. Pharmacol. Ther., 2005, 77(5), 415-426.
[http://dx.doi.org/10.1016/j.clpt.2005.01.009] [PMID: 15900287]
[34]
Johnson, W.W. Cytochrome P450 inactivation by pharmaceuticals and phytochemicals: therapeutic relevance. Drug Metab. Rev., 2008, 40(1), 101-147.
[http://dx.doi.org/10.1080/03602530701836704] [PMID: 18259986]
[35]
Sager, J.E.; Yu, J.; Ragueneau-Majlessi, I.; Isoherranen, N. Physiologically based pharmacokinetic (PBPK) modeling and simulation approaches: a systematic review of published models, applications, and model verification. Drug Metab. Dispos., 2015, 43(11), 1823-1837.
[http://dx.doi.org/10.1124/dmd.115.065920] [PMID: 26296709]
[36]
Wagner, C.; Pan, Y.; Hsu, V.; Sinha, V.; Zhao, P. Predicting the Effect of CYP3A inducers on the pharmacokinetics of substrate drugs using physiologically based pharmacokinetic (PBPK) modeling: an analysis of PBPK submissions to the US FDA. Clin. Pharmacokinet., 2016, 55(4), 475-483.
[http://dx.doi.org/10.1007/s40262-015-0330-y] [PMID: 26369776]
[37]
Yang, Q.J.; Bukuroshi, P.; Quach, H.P.; Chow, E.C.Y.; Pang, K.S. Highlighting vitamin D receptor-targeted activities of 1α,25-dihydroxyvitamin D3 in mice via physiologically based pharmacokinetic-pharmacodynamic modeling. Drug Metab. Dispos., 2018, 46(1), 75-87.
[http://dx.doi.org/10.1124/dmd.117.077271] [PMID: 29084783]
[38]
Yao, Y.; Toshimoto, K.; Kim, S.J.; Yoshikado, T.; Sugiyama, Y. Quantitative analysis of complex drug-drug interactions between cerivastatin and metabolism/transport inhibitors using physiologically based pharmacokinetic modeling. Drug Metab. Dispos., 2018, 46(7), 924-933.
[http://dx.doi.org/10.1124/dmd.117.079210] [PMID: 29712725]
[39]
Zhuang, X.; Lu, C. PBPK modeling and simulation in drug research and development. Acta Pharm. Sin. B, 2016, 6(5), 430-440.
[http://dx.doi.org/10.1016/j.apsb.2016.04.004] [PMID: 27909650]
[40]
Ito, S.; Kusuhara, H.; Yokochi, M.; Toyoshima, J.; Inoue, K.; Yuasa, H.; Sugiyama, Y. Competitive inhibition of the luminal efflux by multidrug and toxin extrusions, but not basolateral uptake by organic cation transporter 2, is the likely mechanism underlying the pharmacokinetic drug-drug interactions caused by cimetidine in the kidney. J. Pharmacol. Exp. Ther., 2012, 340(2), 393-403.
[http://dx.doi.org/10.1124/jpet.111.184986] [PMID: 22072731]
[41]
Giacomini, K.M.; Huang, S.M. Transporters in drug development and clinical pharmacology. Clin. Pharmacol. Ther., 2013, 94(1), 3-9.
[http://dx.doi.org/10.1038/clpt.2013.86] [PMID: 23778703]
[42]
Giacomini, K.M.; Huang, S.M.; Tweedie, D.J.; Benet, L.Z.; Brouwer, K.L.; Chu, X.; Dahlin, A.; Evers, R.; Fischer, V.; Hillgren, K.M.; Hoffmaster, K.A.; Ishikawa, T.; Keppler, D.; Kim, R.B.; Lee, C.A.; Niemi, M.; Polli, J.W.; Sugiyama, Y.; Swaan, P.W.; Ware, J.A.; Wright, S.H.; Yee, S.W.; Zamek-Gliszczynski, M.J.; Zhang, L. International transporter consortium. membrane transporters in drug development. Nat. Rev. Drug Discov., 2010, 9(3), 215-236.
[http://dx.doi.org/10.1038/nrd3028] [PMID: 20190787]
[43]
Amundsen, R.; Christensen, H.; Zabihyan, B.; Asberg, A. Cyclosporine A, but not tacrolimus, shows relevant inhibition of organic anion-transporting protein 1B1-mediated transport of atorvastatin. Drug Metab. Dispos., 2010, 38(9), 1499-1504.
[http://dx.doi.org/10.1124/dmd.110.032268] [PMID: 20519340]
[44]
Izumi, S.; Nozaki, Y.; Maeda, K.; Komori, T.; Takenaka, O.; Kusuhara, H.; Sugiyama, Y. 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), 235-247.
[http://dx.doi.org/10.1124/dmd.114.059105] [PMID: 25414411]
[45]
Pahwa, S.; Alam, K.; Crowe, A.; Farasyn, T.; Neuhoff, S.; Hatley, O.; Ding, K.; Yue, W. Pretreatment with rifampicin and tyrosine kinase inhibitor dasatinib potentiates the inhibitory effects toward OATP1B1- and OATP1B3-mediated transport. J. Pharm. Sci., 2017, 106(8), 2123-2135.
[http://dx.doi.org/10.1016/j.xphs.2017.03.022] [PMID: 28373111]
[46]
Collett, A.; Tanianis-Hughes, J.; Warhurst, G. Rapid induction of P-glycoprotein expression by high permeability compounds in colonic cells in vitro: a possible source of transporter mediated drug interactions? Biochem. Pharmacol., 2004, 68(4), 783-790.
[http://dx.doi.org/10.1016/j.bcp.2004.05.006] [PMID: 15276086]
[47]
Lutz, J.D.; Kirby, B.J.; Wang, L.; Song, Q.; Ling, J.; Massetto, B.; Worth, A.; Kearney, B.P.; Mathias, A. Cytochrome P450 3A induction predicts p-glycoprotein induction; part 1: establishing induction relationships using ascending dose rifampin. Clin. Pharmacol. Ther., 2018, 104(6), 1182-1190.
[http://dx.doi.org/10.1002/cpt.1073] [PMID: 29569723]
[48]
Lutz, J.D.; Kirby, B.J.; Wang, L.; Song, Q.; Ling, J.; Massetto, B.; Worth, A.; Kearney, B.P.; Mathias, A. Cytochrome P450 3A induction predicts p-glycoprotein induction; part 2: prediction of decreased substrate exposure after rifabutin or carbamazepine. Clin. Pharmacol. Ther., 2018, 104(6), 1191-1198.
[http://dx.doi.org/10.1002/cpt.1072] [PMID: 29569712]
[49]
Misaka, S.; Müller, F.; Fromm, M.F. Clinical relevance of drug efflux pumps in the gut. Curr. Opin. Pharmacol., 2013, 13(6), 847-852.
[http://dx.doi.org/10.1016/j.coph.2013.08.010] [PMID: 24028838]
[50]
Westphal, K.; Weinbrenner, A.; Zschiesche, M.; Franke, G.; Knoke, M.; Oertel, R.; Fritz, P.; von Richter, O.; Warzok, R.; Hachenberg, T.; Kauffmann, H.M.; Schrenk, D.; Terhaag, B.; Kroemer, H.K.; Siegmund, W. Induction of P-glycoprotein by rifampin increases intestinal secretion of talinolol in human beings: a new type of drug/drug interaction. Clin. Pharmacol. Ther., 2000, 68(4), 345-355.
[http://dx.doi.org/10.1067/mcp.2000.109797] [PMID: 11061574]
[51]
Mao, J.; Martin, I.; McLeod, J.; Nolan, G.; van Horn, R.; Vourvahis, M.; Lin, Y.S. Perspective: 4β-hydroxycholesterol as an emerging endogenous biomarker of hepatic CYP3A. Drug Metab. Rev., 2017, 49(1), 18-34.
[http://dx.doi.org/10.1080/03602532.2016.1239630] [PMID: 27718639]
[52]
Gidal, B.E.; Maganti, R.; Laurenza, A.; Yang, H.; Verbel, D.A.; Schuck, E.; Ferry, J. Effect of enzyme inhibition on perampanel pharmacokinetics: Why study design matters. Epilepsy Res., 2017, 134, 41-48.
[http://dx.doi.org/10.1016/j.eplepsyres.2017.04.018] [PMID: 28535410]
[53]
Lee, K.H.; Shin, J.G.; Chong, W.S.; Kim, S.; Lee, J.S.; Jang, I.J.; Shin, S.G. Time course of the changes in prednisolone pharmacokinetics after co-administration or discontinuation of rifampin. Eur. J. Clin. Pharmacol., 1993, 45(3), 287-289.
[http://dx.doi.org/10.1007/BF00315399] [PMID: 8276057]
[54]
Lechner, C.; Ishiguro, N.; Fukuhara, A.; Shimizu, H.; Ohtsu, N.; Takatani, M.; Nishiyama, K.; Washio, I.; Yamamura, N.; Kusuhara, H. Impact of experimental conditions on the evaluation of interactions between multidrug and toxin extrusion proteins and candidate drugs. Drug Metab. Dispos., 2016, 44(8), 1381-1389.
[http://dx.doi.org/10.1124/dmd.115.068163] [PMID: 27271370]
[55]
Shitara, Y.; Sugiyama, Y. Preincubation-dependent and long-lasting inhibition of organic anion transporting polypeptide (OATP) and its impact on drug-drug interactions. Pharmacol. Ther., 2017, 177, 67-80.
[http://dx.doi.org/10.1016/j.pharmthera.2017.02.042] [PMID: 28249706]
[56]
Huang, S.M.; Zhao, H.; Lee, J.I.; Reynolds, K.; Zhang, L.; Temple, R.; Lesko, L.J. Therapeutic protein-drug interactions and implications for drug development. Clin. Pharmacol. Ther., 2010, 87(4), 497-503.
[http://dx.doi.org/10.1038/clpt.2009.308] [PMID: 20200513]
[57]
Sunman, J.A.; Hawke, R.L.; LeCluyse, E.L.; Kashuba, A.D. Kupffer cell-mediated IL-2 suppression of CYP3A activity in human hepatocytes. Drug Metab. Dispos., 2004, 32(3), 359-363.
[http://dx.doi.org/10.1124/dmd.32.3.359] [PMID: 14977871]
[58]
Tinel, M.; Robin, M.A.; Doostzadeh, J.; Maratrat, M.; Ballet, F.; Fardel, N.; el Kahwaji, J.; Beaune, P.; Daujat, M.; Labbe, G. The interleukin-2 receptor down-regulates the expression of cytochrome P450 in cultured rat hepatocytes. Gastroenterology, 1995, 109(5), 1589-1599.
[http://dx.doi.org/10.1016/0016-5085(95)90648-7] [PMID: 7557143]
[59]
Frye, R.F.; Schneider, V.M.; Frye, C.S.; Feldman, A.M. Plasma levels of TNF-alpha and IL-6 are inversely related to cytochrome P450-dependent drug metabolism in patients with congestive heart failure. J. Card. Fail., 2002, 8(5), 315-319.
[http://dx.doi.org/10.1054/jcaf.2002.127773] [PMID: 12411982]
[60]
Thal, C.; el Kahwaji, J.; Loeper, J.; Tinel, M.; Doostzadeh, J.; Labbe, G.; Leclaire, J.; Beaune, P.; Pessayre, D. Administration of high doses of human recombinant interleukin-2 decreases the expression of several cytochromes P-450 in the rat. J. Pharmacol. Exp. Ther., 1994, 268(1), 515-521.
[PMID: 8301593]
[61]
Chen, Y.L.; Le Vraux, V.; Leneveu, A.; Dreyfus, F.; Stheneur, A.; Florentin, I.; De Sousa, M.; Giroud, J.P.; Flouvat, B.; Chauvelot-Moachon, L. Acute-phase response, interleukin-6, and alteration of cyclosporine pharmacokinetics. Clin. Pharmacol. Ther., 1994, 55(6), 649-660.
[http://dx.doi.org/10.1038/clpt.1994.82] [PMID: 8004881]
[62]
Morgan, E.T. Impact of infectious and inflammatory disease on cytochrome P450-mediated drug metabolism and pharmacokinetics. Clin. Pharmacol. Ther., 2009, 85(4), 434-438.
[http://dx.doi.org/10.1038/clpt.2008.302] [PMID: 19212314]
[63]
Rivory, L.P.; Slaviero, K.A.; Clarke, S.J. Hepatic cytochrome P450 3A drug metabolism is reduced in cancer patients who have an acute-phase response. Br. J. Cancer, 2002, 87(3), 277-280.
[http://dx.doi.org/10.1038/sj.bjc.6600448] [PMID: 12177794]
[64]
Eng, H.; Sharma, R.; Wolford, A.; Di, L.; Ruggeri, R.B.; Buckbinder, L.; Conn, E.L.; Dalvie, D.K.; Kalgutkar, A.S. Species differences in the oxidative desulfurization of a thiouracil-based irreversible myeloperoxidase inactivator by flavin-containing monooxygenase enzymes. Drug Metab. Dispos., 2016, 44(8), 1262-1269.
[http://dx.doi.org/10.1124/dmd.116.070185] [PMID: 27079250]
[65]
Fan, P.W.; Zhang, D.; Halladay, J.S.; Driscoll, J.P.; Khojasteh, S.C. Going beyond common drug metabolizing enzymes: case Studies of biotransformation involving aldehyde oxidase, γ-glutamyl transpeptidase, cathepsin B, flavin-containing monooxygenase, and ADP-ribosyltransferase. Drug Metab. Dispos., 2016, 44(8), 1253-1261.
[http://dx.doi.org/10.1124/dmd.116.070169] [PMID: 27117704]
[66]
Foti, A.; Hartmann, T.; Coelho, C.; Santos-Silva, T.; Romão, M.J.; Leimkühler, S. Optimization of the expression of human aldehyde oxidase for investigations of single-nucleotide polymorphisms. Drug Metab. Dispos., 2016, 44(8), 1277-1285.
[http://dx.doi.org/10.1124/dmd.115.068395] [PMID: 26842593]
[67]
Foti, R.S.; Dalvie, D.K. Cytochrome P450 and non-cytochrome p450 oxidative metabolism: contributions to the pharmacokinetics, safety, and efficacy of xenobiotics. Drug Metab. Dispos., 2016, 44(8), 1229-1245.
[http://dx.doi.org/10.1124/dmd.116.071753] [PMID: 27298339]
[68]
Fu, J.; Sadgrove, M.; Marson, L.; Jay, M. Biotransformation capacity of carboxylesterase in skin and keratinocytes for the penta-ethyl ester prodrug of DTPA. Drug Metab. Dispos., 2016, 44(8), 1313-1318.
[http://dx.doi.org/10.1124/dmd.116.069377] [PMID: 27130352]
[69]
Yu, J.; Petrie, I.D.; Levy, R.H.; Ragueneau-Majlessi, I. Mechanisms and clinical significance of pharmacokinetic-based drug-drug interactions with drugs approved by the U.S. Food and Drug Administration in 2017. Drug Metab. Dispos., 2019, 47(2), 135-144.
[http://dx.doi.org/10.1124/dmd.118.084905] [PMID: 30442649]
[70]
Yu, J.; Ragueneau-Majlessi, I. In vitro-to-in vivo extrapolation of transporter inhibition data for drugs approved by the US Food and Drug Administration in 2018. Clin. Transl. Sci., 2020.
[http://dx.doi.org/10.1111/cts.12750] [PMID: 31981398]
[71]
Yu, J.; Zhou, Z.; Tay-Sontheimer, J.; Levy, R.H.; Ragueneau-Majlessi, I. Risk of clinically relevant pharmacokinetic-based drug-drug interactions with drugs approved by the U.S. Food and Drug Administration between 2013 and 2016. Drug Metab. Dispos., 2018, 46(6), 835-845.
[http://dx.doi.org/10.1124/dmd.117.078691] [PMID: 29572333]
[72]
Proctor, N.J.; Tucker, G.T.; Rostami-Hodjegan, A. Predicting drug clearance from recombinantly expressed CYPs: intersystem extrapolation factors. Xenobiotica, 2004, 34(2), 151-178.
[http://dx.doi.org/10.1080/00498250310001646353] [PMID: 14985145]
[73]
Boulenc, X.; Schmider, W.; Barberan, O. In vitro/In vivo Correlation for Drug-Drug Interactions. In: Drug Discovery and Evaluation: Methods in Clinical Pharmacology; Vogel, H.G.; Maas, J.; Gebauer, A., Eds.; Springer: Berlin, Heidelberg, 2011; pp. 133-160.
[http://dx.doi.org/10.1007/978-3-540-89891-7_14]
[74]
Akabane, T.; Tanaka, K.; Irie, M.; Terashita, S.; Teramura, T. Case report of extensive metabolism by aldehyde oxidase in humans: pharmacokinetics and metabolite profile of FK3453 in rats, dogs, and humans. Xenobiotica, 2011, 41(5), 372-384.
[http://dx.doi.org/10.3109/00498254.2010.549970] [PMID: 21385103]
[75]
Abbasi, A.; Paragas, E.M.; Joswig-Jones, C.A.; Rodgers, J.T.; Jones, J.P. Time course of aldehyde oxidase and why it is nonlinear. Drug Metab. Dispos., 2019, 47(5), 473-483.
[http://dx.doi.org/10.1124/dmd.118.085787] [PMID: 30787100]
[76]
Li, X.; Sun, J.; Guo, Z.; Zhong, D.; Chen, X. Carboxylesterase 2 and intestine transporters contribute to the low bioavailability of allisartan, a prodrug of Exp3174 for hypertension treatment in humans. Drug Metab. Dispos., 2019, 47(8), 843-853.
[http://dx.doi.org/10.1124/dmd.118.085092] [PMID: 31076412]
[77]
Marto, N.; Morello, J.; Monteiro, E.C.; Pereira, S.A. Implications of sulfotransferase activity in interindividual variability in drug response: clinical perspective on current knowledge. Drug Metab. Rev., 2017, 49(3), 357-371.
[http://dx.doi.org/10.1080/03602532.2017.1335749] [PMID: 28554218]
[78]
Waters, N.J. Evaluation of drug-drug interactions for oncology therapies: in vitro-in vivo extrapolation model-based risk assessment. Br. J. Clin. Pharmacol., 2015, 79(6), 946-958.
[http://dx.doi.org/10.1111/bcp.12563] [PMID: 25443889]
[79]
Elsby, R.; Hare, V.; Neal, H.; Outteridge, S.; Pearson, C.; Plant, K.; Gill, R.U.; Butler, P.; Riley, R.J. Mechanistic In vitro studies indicate that the clinical drug-drug interaction between telithromycin and simvastatin acid is driven by time-dependent inhibition of CYP3A4 with minimal effect on OATP1B1. Drug Metab. Dispos., 2019, 47(1), 1-8.
[http://dx.doi.org/10.1124/dmd.118.083832] [PMID: 30348903]
[80]
Shebley, M.; Sandhu, P.; Emami Riedmaier, A.; Jamei, M.; Narayanan, R.; Patel, A.; Peters, S.A.; Reddy, V.P.; Zheng, M.; de Zwart, L.; Beneton, M.; Bouzom, F.; Chen, J.; Chen, Y.; Cleary, Y.; Collins, C.; Dickinson, G.L.; Djebli, N.; Einolf, H.J.; Gardner, I.; Huth, F.; Kazmi, F.; Khalil, F.; Lin, J.; Odinecs, A.; Patel, C.; Rong, H.; Schuck, E.; Sharma, P.; Wu, S.P.; Xu, Y.; Yamazaki, S.; Yoshida, K.; Rowland, M. Physiologically based pharmacokinetic model qualification and reporting procedures for regulatory submissions: a consortium perspective. Clin. Pharmacol. Ther., 2018, 104(1), 88-110.
[http://dx.doi.org/10.1002/cpt.1013] [PMID: 29315504]
[81]
Margolis, J.M.; Obach, R.S. Impact of nonspecific binding to microsomes and phospholipid on the inhibition of cytochrome P4502D6: implications for relating in vitro inhibition data to in vivo drug interactions. Drug Metab. Dispos., 2003, 31(5), 606-611.
[http://dx.doi.org/10.1124/dmd.31.5.606] [PMID: 12695349]
[82]
Einolf, H.J.; Chen, L.; Fahmi, O.A.; Gibson, C.R.; Obach, R.S.; Shebley, M.; Silva, J.; Sinz, M.W.; Unadkat, J.D.; Zhang, L.; Zhao, P. Evaluation of various static and dynamic modeling methods to predict clinical CYP3A induction using in vitro CYP3A4 mRNA induction data. Clin. Pharmacol. Ther., 2014, 95(2), 179-188.
[http://dx.doi.org/10.1038/clpt.2013.170] [PMID: 23995268]
[83]
Sane, R.S.; Ramsden, D.; Sabo, J.P.; Cooper, C.; Rowland, L.; Ting, N.; Whitcher-Johnstone, A.; Tweedie, D.J. Contribution of major metabolites toward complex drug-drug interactions of deleobuvir: in vitro predictions and in vivo outcomes. Drug Metab. Dispos., 2016, 44(3), 466-475.
[http://dx.doi.org/10.1124/dmd.115.066985] [PMID: 26684498]
[84]
Jones, H.; Rowland-Yeo, K. Basic concepts in physiologically based pharmacokinetic modeling in drug discovery and development. CPT Pharmacometric. Syst. Pharmacol., 2013, 2e63,
[http://dx.doi.org/10.1038/psp.2013.41] [PMID: 23945604]
[85]
Rowland Yeo, K.; Jamei, M.; Yang, J.; Tucker, G.T.; Rostami-Hodjegan, A. Physiologically based mechanistic modelling to predict complex drug-drug interactions involving simultaneous competitive and time-dependent enzyme inhibition by parent compound and its metabolite in both liver and gut - the effect of diltiazem on the time-course of exposure to triazolam. Eur. J. Pharm. Sci., 2010, 39(5), 298-309.
[http://dx.doi.org/10.1016/j.ejps.2009.12.002] [PMID: 20025966]
[86]
Miller, N.A.; Reddy, M.B.; Heikkinen, A.T.; Lukacova, V.; Parrott, N. Physiologically based pharmacokinetic modelling for first-in-human predictions: an updated model building strategy illustrated with challenging industry case studies. Clin. Pharmacokinet., 2019, 58(6), 727-746.
[http://dx.doi.org/10.1007/s40262-019-00741-9] [PMID: 30729397]
[87]
Grimstein, M.; Yang, Y.; Zhang, X.; Grillo, J.; Huang, S.M.; Zineh, I.; Wang, Y. Physiologically based pharmacokinetic modeling in regulatory science: an update from the U.S. Food and Drug Administration’s Office of Clinical Pharmacology. J. Pharm. Sci., 2019, 108(1), 21-25.
[http://dx.doi.org/10.1016/j.xphs.2018.10.033] [PMID: 30385284]
[88]
Penzak, S.R.; Rojas-Fernandez, C. 4β-Hydroxycholesterol as an endogenous biomarker for CYP3A activity: literature review and critical evaluation. J. Clin. Pharmacol., 2019, 59(5), 611-624.
[http://dx.doi.org/10.1002/jcph.1391] [PMID: 30748026]
[89]
Brouwer, K.L.; Keppler, D.; Hoffmaster, K.A.; Bow, D.A.; Cheng, Y.; Lai, Y.; Palm, J.E.; Stieger, B.; Evers, R. International Transporter Consortium. In vitro methods to support transporter evaluation in drug discovery and development. Clin. Pharmacol. Ther., 2013, 94(1), 95-112.
[http://dx.doi.org/10.1038/clpt.2013.81] [PMID: 23588315]
[90]
Ellens, H.; Deng, S.; Coleman, J.; Bentz, J.; Taub, M.E.; Ragueneau-Majlessi, I.; Chung, S.P.; Herédi-Szabó, K.; Neuhoff, S.; Palm, J.; Balimane, P.; Zhang, L.; Jamei, M.; Hanna, I.; O’Connor, M.; Bednarczyk, D.; Forsgard, M.; Chu, X.; Funk, C.; Guo, A.; Hillgren, K.M.; Li, L.; Pak, A.Y.; Perloff, E.S.; Rajaraman, G.; Salphati, L.; Taur, J.S.; Weitz, D.; Wortelboer, H.M.; Xia, C.Q.; Xiao, G.; Yamagata, T.; Lee, C.A. Application of receiver operating characteristic analysis to refine the prediction of potential digoxin drug interactions. Drug Metab. Dispos., 2013, 41(7), 1367-1374.
[http://dx.doi.org/10.1124/dmd.112.050542] [PMID: 23620486]
[91]
Zhang, L.; Zhang, Y.D.; Strong, J.M.; Reynolds, K.S.; Huang, S.M. A regulatory viewpoint on transporter-based drug interactions. Xenobiotica, 2008, 38(7-8), 709-724.
[http://dx.doi.org/10.1080/00498250802017715] [PMID: 18668428]
[92]
Dong, Z.; Yang, X.; Arya, V.; Zhang, L. Comparing various in vitro prediction criteria to assess the potential of a new molecular entity (NME) to inhibit organic anion transporter 1 and 3 (OAT1 and 3). Clin. Pharmacol. Ther., 2016, 99(S1), S94. [a]
[93]
Dong, Z.Y.Y.; Arya, V.; Zhang, L. Comparing various in vitro prediction criteria to assess the potential of a new molecular entity (NME) to inhibit OCT2 and MATE transporters in vivo. Clin. Pharmacol. Ther., 2016, 99(S1), S94. [b]
[94]
Kalvass, J.C.; Polli, J.W.; Bourdet, D.L.; Feng, B.; Huang, S.M.; Liu, X.; Smith, Q.R.; Zhang, L.K.; Zamek-Gliszczynski, M.J. International Transporter Consortium. Why clinical modulation of efflux transport at the human blood-brain barrier is unlikely: the ITC evidence-based position. Clin. Pharmacol. Ther., 2013, 94(1), 80-94.
[http://dx.doi.org/10.1038/clpt.2013.34] [PMID: 23588303]

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