Abstract
In cytotoxic anticancer agents, efficacy depends on tumor heterogeneity and is not evaluated immediately after administration, and toxicities are severe and life threatening such as neutropenia and thrombocytopenia. Therefore because toxicity is often more readily measured than efficacy, there are more reported pharmacodynamic (PD) studies defining relationships between pharmacokinetic (PK) parameters and the toxicity. However, retrospective studies have shown that molecular targeted agent systemic exposure correlates with treatment response (efficacy and toxicity) in various cancers including renal cell carcinoma (RCC). The evidence of the relationship between PK and PD for imatinib currently exists in the treatment of leukemia and gastrointestinal stromal tumor (GIST). It is important to evaluate the relationship between PK and PD prospectively in clinical trials rather than extrapolating from retrospective analyses. Based on these findings, therapeutic levels should be defined for molecular targeted agents in the treatment of RCC such as that that already occurs for antiepileptic, immunosuppressive, and antibiotic agents. Optimization of systemic exposure by dose modification to eliminate individual variability can increase the probability of efficacy, decrease the probability of toxicity, or both in each RCC patient treated with molecular targeted agents.
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Reference
Boudou-Rouquette P, Narjoz C, Golmard JL et al (2012) Early sorafenib-induced toxicity is associated with drug exposure and UGTIA9 genetic polymorphism in patients with solid tumors: a preliminary study. PLoS One 7:e42875. doi:10.1371/journal.pone.0042875
Jain L, Woo S, Gardner ER et al (2011) Population pharmacokinetic analysis of sorafenib in patients with solid tumours. Br J Clin Pharmacol 72:294–305. doi:10.1111/j.1365-2125.2011.03963.x
European Medicines Agency (2007) Nexavar: EPAR – scientific discussion. Available from: http://www.ema.europa.eu. Accessed 5 Oct 2012
Houk BE, Bello CL, Kang D et al (2009) Population pharmacokinetic meta-analysis of sunitinib malate (SU11248) and its primary metabolite (SU12662) in healthy volunteers and oncology patients. Clin Cancer Res 15:2497–2506. doi:10.1158/1078-0432
Mizuno T, Fukudo M, Fukuda T et al (2014) The effect of ABCG2 genotype on the population pharmacokinetics of sunitinib in patients with renal cell carcinoma. Ther Drug Monit 36:310–316. doi:10.1097/FTD.0000000000000025
HoukBello CL, Poland B, Rosen LS et al (2010) Relationship between exposure to sunitinib and efficacy and tolerability endpoints in patients with cancer: results of a pharmacokinetic/pharmacodynamic meta analysis. Cancer Chemother Pharmacol 66:357–371. doi:10.1007/s00280-009-1170-y
Imai Y, Nakane M, Kage K et al (2002) C421A polymorphism in the human breast cancer resistance protein gene is associated with low expression of Q141K protein and low-level drug resistance. Mol Cancer Ther 1:611–616
Kim KA, Joo HJ, Park JY (2010) ABCG2 polymorphisms, 34G>A and 421C>A in a Korean population: analysis and a comprehensive comparison with other populations. J Clin Pharm Ther 35(6):705–712. doi:10.1111/j.1365-2710.2009.01127.x
de Jong FA, Marsh S, Mathijssen RH et al (2004) ABCG2 pharmacogenetics: ethnic differences in allele frequency and assessment of influence on irinotecan disposition. Clin Cancer Res 10:5889–5894
Tomita Y, Shinohara M, Yuasa T et al (2010) Overall survival and updated results from a phase II study of sunitinib in Japanese patients with metastatic renal cell carcinoma. Jpn J Clin Oncol 40:1166–1172. doi:10.1093/jjco/hyq146
Kim HS, Hong MH, Kim K et al (2011) Sunitinib for Asian patients with advanced renal cell carcinoma: a comparable efficacy with different toxicity profiles. Oncology 80:395–405. doi:10.1159/000330361
Motzer RJ, Hutson TE, Tomczak P et al (2007) Sunitinib versus interferon alfa in metastatic renal-cell carcinoma. N Engl J Med 356:115–124
Brennan M, Williams JA, Chen Y et al (2012) Mete-analysis of contribution of genetic polymorphisms in drug-metabolizing enzymes or transporters to axitinib pharmacokinetics. Eur J Clin Pharmacol 68:645–655. doi:10.1007/s00228-011-1171-8
Garrett M, Poland B, Brennan M et al (2014) Population pharmacokinetic analysis of axitinib in healthy volunteers. Br J Clin Pharmacol 77:480–492. doi:10.1111/bcp.12206
Rini BI, Gaeertt M, Poland B et al (2013) Axitinib in metastatic renal cell carcinoma: results of a pharmacokinetic and pharmacodynamic analysis. J Clin Pharmacol 53:491–504. doi:10.1002/jcph.73
Heath EI, Chiorean EG, Sweeney CJ et al (2010) A phase I study of the pharmacokinetic and safety profiles of oral pazopanib with a high-fat or low-fat meal in patients with advanced solid tumors. Clin Pharmacol Ther 88:818–823. doi:10.1038/clpt.2010.199
Kumar R, Knick VB, Rudolph SK et al (2007) Pharmacokinetic-pharmacodynamic correlation from mouse to human with pazopanib, a multikinase angiogenesis inhibitor with potent antitumor and antiangiogenic activity. Mol Cancer Ther 6:2012–2021
Suttle AB, Ball HA, Molimard M et al (2014) Relationships between pazopanib exposure and clinical safety and efficacy in patients with advanced renal cell carcinoma. Br J Cancer 111:1909–1916. doi:10.1038/bjc.2014.503
Moes DJ, Press RR, den Hartigh J et al (2012) Population pharmacokinetics and pharmacogenetics of everolimus in renal transplant patients. Clin Pharmacokinet 51:467–480. doi:10.2165/11599710-000000000-00000
Lemaitre F, Bezian E, Goldwirt L et al (2012) Population pharmacokinetics of everolimus in cardiac recipients: comedications, ABCB1, and CYP3A5 polymorphisms. Ther Drug Monit 34:686–694. doi:10.1097/FTD.0b013e318273c899
Tabernero J, Rojo F, Calvo E et al (2008) Dose- and schedule-dependent inhibition of the mammalian target of rapamycin pathway with everolimus: a phase I tumor pharmacodynamic study in patients with advanced solid tumors. J Clin Oncol 26:1603–1610. doi:10.1200/JCO.2007.14.5482
Ravaud A, Urva SR, Grosch K et al (2014) Relationship between everolimus exposure and safety and efficacy: meta-analysis of clinical trials in oncology. Eur J Cancer 50:486–495. doi:10.1016/j.ejca.2013.11.022. Epub 2013 Dec 9
Thiery-Vuillemin A, Mouillet G, Nguyen Tan Hon T et al (2014) Impact of everolimus blood concentration on its anti-cancer activity in patients with metastatic renal cell carcinoma. Cancer Chemother Pharmacol 73:999–1007. doi:10.1007/s00280-014-2435-7
Ferté C, Paci A, Zizi M et al (2011) Natural history, management and pharmacokinetics of everolimus-induced-oral ulcers: insights into compliance issues. Eur J Cancer 47:2249–2255. doi:10.1016/j.ejca.2011.03.017
Boni JP, Leister C, Bender G et al (2005) Population pharmacokinetics of CCI-779: correlations to safety and pharmacogenomic responses in patients with advanced renal cancer. Clin Pharmacol Ther 77:76–89
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Imamura, C.K. (2017). Optimization of Therapy by Pharmacokinetic–Pharmacodynamic Analyses. In: Oya, M. (eds) Renal Cell Carcinoma. Springer, Tokyo. https://doi.org/10.1007/978-4-431-55531-5_16
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DOI: https://doi.org/10.1007/978-4-431-55531-5_16
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