Population Modeling Integrating Pharmacokinetics, Pharmacodynamics, Pharmacogenetics, and Clinical Outcome in Patients With Sunitinib‐Treated Cancer
The tyrosine kinase inhibitor sunitinib is used as first‐line therapy in patients with metastasized renal cell carcinoma (mRCC), given in fixed‐dose regimens despite its high variability in pharmacokinetics (PKs). Interindividual variability of drug exposure may be responsible for differences in res...
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| Veröffentlicht in: | CPT: pharmacometrics and systems pharmacology 2017-09, Vol.6 (9), p.604-613 |
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| creator | Diekstra, MH Fritsch, A Kanefendt, F Swen, JJ Moes, DJAR Sörgel, F Kinzig, M Stelzer, C Schindele, D Gauler, T Hauser, S Houtsma, D Roessler, M Moritz, B Mross, K Bergmann, L Oosterwijk, E Kiemeney, LA Guchelaar, HJ Jaehde, U |
| description | The tyrosine kinase inhibitor sunitinib is used as first‐line therapy in patients with metastasized renal cell carcinoma (mRCC), given in fixed‐dose regimens despite its high variability in pharmacokinetics (PKs). Interindividual variability of drug exposure may be responsible for differences in response. Therefore, dosing strategies based on pharmacokinetic/pharmacodynamic (PK/PD) models may be useful to optimize treatment. Plasma concentrations of sunitinib, its active metabolite SU12662, and the soluble vascular endothelial growth factor receptors sVEGFR‐2 and sVEGFR‐3, were measured in 26 patients with mRCC within the EuroTARGET project and 21 patients with metastasized colorectal cancer (mCRC) from the C‐II‐005 study. Based on these observations, PK/PD models with potential influence of genetic predictors were developed and linked to time‐to‐event (TTE) models. Baseline sVEGFR‐2 levels were associated with clinical outcome in patients with mRCC, whereas active drug PKs seemed to be more predictive in patients with mCRC. The models provide the basis of PK/PD‐guided strategies for the individualization of anti‐angiogenic therapies. |
| doi_str_mv | 10.1002/psp4.12210 |
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Interindividual variability of drug exposure may be responsible for differences in response. Therefore, dosing strategies based on pharmacokinetic/pharmacodynamic (PK/PD) models may be useful to optimize treatment. Plasma concentrations of sunitinib, its active metabolite SU12662, and the soluble vascular endothelial growth factor receptors sVEGFR‐2 and sVEGFR‐3, were measured in 26 patients with mRCC within the EuroTARGET project and 21 patients with metastasized colorectal cancer (mCRC) from the C‐II‐005 study. Based on these observations, PK/PD models with potential influence of genetic predictors were developed and linked to time‐to‐event (TTE) models. Baseline sVEGFR‐2 levels were associated with clinical outcome in patients with mRCC, whereas active drug PKs seemed to be more predictive in patients with mCRC. The models provide the basis of PK/PD‐guided strategies for the individualization of anti‐angiogenic therapies.</description><identifier>ISSN: 2163-8306</identifier><identifier>EISSN: 2163-8306</identifier><identifier>DOI: 10.1002/psp4.12210</identifier><identifier>PMID: 28571114</identifier><language>eng</language><publisher>United States: John Wiley & Sons, Inc</publisher><subject>Adult ; Aged ; Aged, 80 and over ; Antineoplastic Agents - blood ; Antineoplastic Agents - pharmacokinetics ; Antineoplastic Agents - pharmacology ; Antineoplastic Agents - therapeutic use ; ATP Binding Cassette Transporter, Subfamily B - genetics ; Biomarkers ; Carcinoma, Renal Cell - blood ; Carcinoma, Renal Cell - drug therapy ; Carcinoma, Renal Cell - genetics ; Clinical outcomes ; Colorectal cancer ; Colorectal Neoplasms - blood ; Colorectal Neoplasms - drug therapy ; Colorectal Neoplasms - genetics ; Cytochrome P-450 CYP3A - genetics ; Drug dosages ; Female ; Genotype ; Humans ; Indoles - blood ; Indoles - pharmacokinetics ; Indoles - pharmacology ; Indoles - therapeutic use ; Interleukin-8 - genetics ; Kidney cancer ; Kidney Neoplasms - blood ; Kidney Neoplasms - drug therapy ; Kidney Neoplasms - genetics ; Male ; Middle Aged ; Models, Biological ; Original ; Patients ; Pharmacodynamics ; Pharmacokinetics ; Polymorphism, Single Nucleotide ; Protein Kinase Inhibitors - blood ; Protein Kinase Inhibitors - pharmacokinetics ; Protein Kinase Inhibitors - pharmacology ; Protein Kinase Inhibitors - therapeutic use ; Pyrroles - blood ; Pyrroles - pharmacokinetics ; Pyrroles - pharmacology ; Pyrroles - therapeutic use ; Studies ; Sunitinib ; Targeted cancer therapy ; Treatment Outcome ; Tumors ; Vascular endothelial growth factor ; Vascular Endothelial Growth Factor A - genetics ; Vascular Endothelial Growth Factor Receptor-2 - blood ; Vascular Endothelial Growth Factor Receptor-2 - genetics ; Vascular Endothelial Growth Factor Receptor-3 - blood ; Vascular Endothelial Growth Factor Receptor-3 - genetics</subject><ispartof>CPT: pharmacometrics and systems pharmacology, 2017-09, Vol.6 (9), p.604-613</ispartof><rights>2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics</rights><rights>2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.</rights><rights>2017. 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Interindividual variability of drug exposure may be responsible for differences in response. Therefore, dosing strategies based on pharmacokinetic/pharmacodynamic (PK/PD) models may be useful to optimize treatment. Plasma concentrations of sunitinib, its active metabolite SU12662, and the soluble vascular endothelial growth factor receptors sVEGFR‐2 and sVEGFR‐3, were measured in 26 patients with mRCC within the EuroTARGET project and 21 patients with metastasized colorectal cancer (mCRC) from the C‐II‐005 study. Based on these observations, PK/PD models with potential influence of genetic predictors were developed and linked to time‐to‐event (TTE) models. Baseline sVEGFR‐2 levels were associated with clinical outcome in patients with mRCC, whereas active drug PKs seemed to be more predictive in patients with mCRC. 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blood</subject><subject>Indoles - pharmacokinetics</subject><subject>Indoles - pharmacology</subject><subject>Indoles - therapeutic use</subject><subject>Interleukin-8 - genetics</subject><subject>Kidney cancer</subject><subject>Kidney Neoplasms - blood</subject><subject>Kidney Neoplasms - drug therapy</subject><subject>Kidney Neoplasms - genetics</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Models, Biological</subject><subject>Original</subject><subject>Patients</subject><subject>Pharmacodynamics</subject><subject>Pharmacokinetics</subject><subject>Polymorphism, Single Nucleotide</subject><subject>Protein Kinase Inhibitors - blood</subject><subject>Protein Kinase Inhibitors - pharmacokinetics</subject><subject>Protein Kinase Inhibitors - pharmacology</subject><subject>Protein Kinase Inhibitors - therapeutic use</subject><subject>Pyrroles - blood</subject><subject>Pyrroles - pharmacokinetics</subject><subject>Pyrroles - pharmacology</subject><subject>Pyrroles - 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Interindividual variability of drug exposure may be responsible for differences in response. Therefore, dosing strategies based on pharmacokinetic/pharmacodynamic (PK/PD) models may be useful to optimize treatment. Plasma concentrations of sunitinib, its active metabolite SU12662, and the soluble vascular endothelial growth factor receptors sVEGFR‐2 and sVEGFR‐3, were measured in 26 patients with mRCC within the EuroTARGET project and 21 patients with metastasized colorectal cancer (mCRC) from the C‐II‐005 study. Based on these observations, PK/PD models with potential influence of genetic predictors were developed and linked to time‐to‐event (TTE) models. Baseline sVEGFR‐2 levels were associated with clinical outcome in patients with mRCC, whereas active drug PKs seemed to be more predictive in patients with mCRC. The models provide the basis of PK/PD‐guided strategies for the individualization of anti‐angiogenic therapies.</abstract><cop>United States</cop><pub>John Wiley & Sons, Inc</pub><pmid>28571114</pmid><doi>10.1002/psp4.12210</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
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| identifier | ISSN: 2163-8306 |
| ispartof | CPT: pharmacometrics and systems pharmacology, 2017-09, Vol.6 (9), p.604-613 |
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| source | MEDLINE; DOAJ Directory of Open Access Journals; Access via Wiley Online Library; EZB-FREE-00999 freely available EZB journals; Wiley Online Library (Open Access Collection); PubMed Central |
| subjects | Adult Aged Aged, 80 and over Antineoplastic Agents - blood Antineoplastic Agents - pharmacokinetics Antineoplastic Agents - pharmacology Antineoplastic Agents - therapeutic use ATP Binding Cassette Transporter, Subfamily B - genetics Biomarkers Carcinoma, Renal Cell - blood Carcinoma, Renal Cell - drug therapy Carcinoma, Renal Cell - genetics Clinical outcomes Colorectal cancer Colorectal Neoplasms - blood Colorectal Neoplasms - drug therapy Colorectal Neoplasms - genetics Cytochrome P-450 CYP3A - genetics Drug dosages Female Genotype Humans Indoles - blood Indoles - pharmacokinetics Indoles - pharmacology Indoles - therapeutic use Interleukin-8 - genetics Kidney cancer Kidney Neoplasms - blood Kidney Neoplasms - drug therapy Kidney Neoplasms - genetics Male Middle Aged Models, Biological Original Patients Pharmacodynamics Pharmacokinetics Polymorphism, Single Nucleotide Protein Kinase Inhibitors - blood Protein Kinase Inhibitors - pharmacokinetics Protein Kinase Inhibitors - pharmacology Protein Kinase Inhibitors - therapeutic use Pyrroles - blood Pyrroles - pharmacokinetics Pyrroles - pharmacology Pyrroles - therapeutic use Studies Sunitinib Targeted cancer therapy Treatment Outcome Tumors Vascular endothelial growth factor Vascular Endothelial Growth Factor A - genetics Vascular Endothelial Growth Factor Receptor-2 - blood Vascular Endothelial Growth Factor Receptor-2 - genetics Vascular Endothelial Growth Factor Receptor-3 - blood Vascular Endothelial Growth Factor Receptor-3 - genetics |
| title | Population Modeling Integrating Pharmacokinetics, Pharmacodynamics, Pharmacogenetics, and Clinical Outcome in Patients With Sunitinib‐Treated Cancer |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-26T17%3A17%3A30IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Population%20Modeling%20Integrating%20Pharmacokinetics,%20Pharmacodynamics,%20Pharmacogenetics,%20and%20Clinical%20Outcome%20in%20Patients%20With%20Sunitinib%E2%80%90Treated%20Cancer&rft.jtitle=CPT:%20pharmacometrics%20and%20systems%20pharmacology&rft.au=Diekstra,%20MH&rft.date=2017-09&rft.volume=6&rft.issue=9&rft.spage=604&rft.epage=613&rft.pages=604-613&rft.issn=2163-8306&rft.eissn=2163-8306&rft_id=info:doi/10.1002/psp4.12210&rft_dat=%3Cproquest_pubme%3E2290893912%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2290893912&rft_id=info:pmid/28571114&rfr_iscdi=true |