Non-compartmental estimation of pharmacokinetic parameters in serial sampling designs
Abstract Pharmacokinetic studies are commonly analyzed using a two-stage approach where the first stage involves estimation of pharmacokinetic parameters for each subject separately and the second stage uses the individual parameter estimates for statistical inference. This two-stage approach is not...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Wolfsegger, Martin J. [verfasserIn] Jaki, Thomas [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2009 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Journal of Pharmacokinetics and Biopharmaceutics - Kluwer Academic Publishers-Plenum Publishers, 1973, 36(2009), 5 vom: 22. Okt. |
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| Übergeordnetes Werk: |
volume:36 ; year:2009 ; number:5 ; day:22 ; month:10 |
| Links: |
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| DOI / URN: |
10.1007/s10928-009-9133-9 |
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SPR014708825 |
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| 520 | |a Abstract Pharmacokinetic studies are commonly analyzed using a two-stage approach where the first stage involves estimation of pharmacokinetic parameters for each subject separately and the second stage uses the individual parameter estimates for statistical inference. This two-stage approach is not applicable in sparse sampling situations where only one sample is available per subject. Nonlinear models are often applied to analyze pharmacokinetic data assessed in such serial sampling designs. Modelling approaches are suitable provided that the form of the true model is known, which is rarely the case in early stages of drug development. This paper presents an alternative approach to estimate pharmacokinetic parameters based on non-compartmental and asymptotic theories in the case of serial sampling when a drug is given as an intravenous bolus. The statistical properties of estimators of the pharmacokinetic parameters are investigated and evaluated using Monte Carlo simulations. | ||
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10.1007/s10928-009-9133-9 doi (DE-627)SPR014708825 (SPR)s10928-009-9133-9-e DE-627 ger DE-627 rakwb eng Wolfsegger, Martin J. verfasserin aut Non-compartmental estimation of pharmacokinetic parameters in serial sampling designs 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Pharmacokinetic studies are commonly analyzed using a two-stage approach where the first stage involves estimation of pharmacokinetic parameters for each subject separately and the second stage uses the individual parameter estimates for statistical inference. This two-stage approach is not applicable in sparse sampling situations where only one sample is available per subject. Nonlinear models are often applied to analyze pharmacokinetic data assessed in such serial sampling designs. Modelling approaches are suitable provided that the form of the true model is known, which is rarely the case in early stages of drug development. This paper presents an alternative approach to estimate pharmacokinetic parameters based on non-compartmental and asymptotic theories in the case of serial sampling when a drug is given as an intravenous bolus. The statistical properties of estimators of the pharmacokinetic parameters are investigated and evaluated using Monte Carlo simulations. Asymptotic (dpeaa)DE-He213 Non-compartmental (dpeaa)DE-He213 Pharmacokinetics (dpeaa)DE-He213 PK parameters (dpeaa)DE-He213 Serial sampling (dpeaa)DE-He213 Sparse sampling (dpeaa)DE-He213 Jaki, Thomas verfasserin aut Enthalten in Journal of Pharmacokinetics and Biopharmaceutics Kluwer Academic Publishers-Plenum Publishers, 1973 36(2009), 5 vom: 22. Okt. (DE-627)SPR014694166 nnns volume:36 year:2009 number:5 day:22 month:10 https://dx.doi.org/10.1007/s10928-009-9133-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_40 AR 36 2009 5 22 10 |
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10.1007/s10928-009-9133-9 doi (DE-627)SPR014708825 (SPR)s10928-009-9133-9-e DE-627 ger DE-627 rakwb eng Wolfsegger, Martin J. verfasserin aut Non-compartmental estimation of pharmacokinetic parameters in serial sampling designs 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Pharmacokinetic studies are commonly analyzed using a two-stage approach where the first stage involves estimation of pharmacokinetic parameters for each subject separately and the second stage uses the individual parameter estimates for statistical inference. This two-stage approach is not applicable in sparse sampling situations where only one sample is available per subject. Nonlinear models are often applied to analyze pharmacokinetic data assessed in such serial sampling designs. Modelling approaches are suitable provided that the form of the true model is known, which is rarely the case in early stages of drug development. This paper presents an alternative approach to estimate pharmacokinetic parameters based on non-compartmental and asymptotic theories in the case of serial sampling when a drug is given as an intravenous bolus. The statistical properties of estimators of the pharmacokinetic parameters are investigated and evaluated using Monte Carlo simulations. Asymptotic (dpeaa)DE-He213 Non-compartmental (dpeaa)DE-He213 Pharmacokinetics (dpeaa)DE-He213 PK parameters (dpeaa)DE-He213 Serial sampling (dpeaa)DE-He213 Sparse sampling (dpeaa)DE-He213 Jaki, Thomas verfasserin aut Enthalten in Journal of Pharmacokinetics and Biopharmaceutics Kluwer Academic Publishers-Plenum Publishers, 1973 36(2009), 5 vom: 22. Okt. (DE-627)SPR014694166 nnns volume:36 year:2009 number:5 day:22 month:10 https://dx.doi.org/10.1007/s10928-009-9133-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_40 AR 36 2009 5 22 10 |
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10.1007/s10928-009-9133-9 doi (DE-627)SPR014708825 (SPR)s10928-009-9133-9-e DE-627 ger DE-627 rakwb eng Wolfsegger, Martin J. verfasserin aut Non-compartmental estimation of pharmacokinetic parameters in serial sampling designs 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Pharmacokinetic studies are commonly analyzed using a two-stage approach where the first stage involves estimation of pharmacokinetic parameters for each subject separately and the second stage uses the individual parameter estimates for statistical inference. This two-stage approach is not applicable in sparse sampling situations where only one sample is available per subject. Nonlinear models are often applied to analyze pharmacokinetic data assessed in such serial sampling designs. Modelling approaches are suitable provided that the form of the true model is known, which is rarely the case in early stages of drug development. This paper presents an alternative approach to estimate pharmacokinetic parameters based on non-compartmental and asymptotic theories in the case of serial sampling when a drug is given as an intravenous bolus. The statistical properties of estimators of the pharmacokinetic parameters are investigated and evaluated using Monte Carlo simulations. Asymptotic (dpeaa)DE-He213 Non-compartmental (dpeaa)DE-He213 Pharmacokinetics (dpeaa)DE-He213 PK parameters (dpeaa)DE-He213 Serial sampling (dpeaa)DE-He213 Sparse sampling (dpeaa)DE-He213 Jaki, Thomas verfasserin aut Enthalten in Journal of Pharmacokinetics and Biopharmaceutics Kluwer Academic Publishers-Plenum Publishers, 1973 36(2009), 5 vom: 22. Okt. (DE-627)SPR014694166 nnns volume:36 year:2009 number:5 day:22 month:10 https://dx.doi.org/10.1007/s10928-009-9133-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_40 AR 36 2009 5 22 10 |
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10.1007/s10928-009-9133-9 doi (DE-627)SPR014708825 (SPR)s10928-009-9133-9-e DE-627 ger DE-627 rakwb eng Wolfsegger, Martin J. verfasserin aut Non-compartmental estimation of pharmacokinetic parameters in serial sampling designs 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Pharmacokinetic studies are commonly analyzed using a two-stage approach where the first stage involves estimation of pharmacokinetic parameters for each subject separately and the second stage uses the individual parameter estimates for statistical inference. This two-stage approach is not applicable in sparse sampling situations where only one sample is available per subject. Nonlinear models are often applied to analyze pharmacokinetic data assessed in such serial sampling designs. Modelling approaches are suitable provided that the form of the true model is known, which is rarely the case in early stages of drug development. This paper presents an alternative approach to estimate pharmacokinetic parameters based on non-compartmental and asymptotic theories in the case of serial sampling when a drug is given as an intravenous bolus. The statistical properties of estimators of the pharmacokinetic parameters are investigated and evaluated using Monte Carlo simulations. Asymptotic (dpeaa)DE-He213 Non-compartmental (dpeaa)DE-He213 Pharmacokinetics (dpeaa)DE-He213 PK parameters (dpeaa)DE-He213 Serial sampling (dpeaa)DE-He213 Sparse sampling (dpeaa)DE-He213 Jaki, Thomas verfasserin aut Enthalten in Journal of Pharmacokinetics and Biopharmaceutics Kluwer Academic Publishers-Plenum Publishers, 1973 36(2009), 5 vom: 22. Okt. (DE-627)SPR014694166 nnns volume:36 year:2009 number:5 day:22 month:10 https://dx.doi.org/10.1007/s10928-009-9133-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_40 AR 36 2009 5 22 10 |
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Abstract Pharmacokinetic studies are commonly analyzed using a two-stage approach where the first stage involves estimation of pharmacokinetic parameters for each subject separately and the second stage uses the individual parameter estimates for statistical inference. This two-stage approach is not applicable in sparse sampling situations where only one sample is available per subject. Nonlinear models are often applied to analyze pharmacokinetic data assessed in such serial sampling designs. Modelling approaches are suitable provided that the form of the true model is known, which is rarely the case in early stages of drug development. This paper presents an alternative approach to estimate pharmacokinetic parameters based on non-compartmental and asymptotic theories in the case of serial sampling when a drug is given as an intravenous bolus. The statistical properties of estimators of the pharmacokinetic parameters are investigated and evaluated using Monte Carlo simulations. |
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Abstract Pharmacokinetic studies are commonly analyzed using a two-stage approach where the first stage involves estimation of pharmacokinetic parameters for each subject separately and the second stage uses the individual parameter estimates for statistical inference. This two-stage approach is not applicable in sparse sampling situations where only one sample is available per subject. Nonlinear models are often applied to analyze pharmacokinetic data assessed in such serial sampling designs. Modelling approaches are suitable provided that the form of the true model is known, which is rarely the case in early stages of drug development. This paper presents an alternative approach to estimate pharmacokinetic parameters based on non-compartmental and asymptotic theories in the case of serial sampling when a drug is given as an intravenous bolus. The statistical properties of estimators of the pharmacokinetic parameters are investigated and evaluated using Monte Carlo simulations. |
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Abstract Pharmacokinetic studies are commonly analyzed using a two-stage approach where the first stage involves estimation of pharmacokinetic parameters for each subject separately and the second stage uses the individual parameter estimates for statistical inference. This two-stage approach is not applicable in sparse sampling situations where only one sample is available per subject. Nonlinear models are often applied to analyze pharmacokinetic data assessed in such serial sampling designs. Modelling approaches are suitable provided that the form of the true model is known, which is rarely the case in early stages of drug development. This paper presents an alternative approach to estimate pharmacokinetic parameters based on non-compartmental and asymptotic theories in the case of serial sampling when a drug is given as an intravenous bolus. The statistical properties of estimators of the pharmacokinetic parameters are investigated and evaluated using Monte Carlo simulations. |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR014708825</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230519141603.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201006s2009 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10928-009-9133-9</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR014708825</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s10928-009-9133-9-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Wolfsegger, Martin J.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Non-compartmental estimation of pharmacokinetic parameters in serial sampling designs</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2009</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Pharmacokinetic studies are commonly analyzed using a two-stage approach where the first stage involves estimation of pharmacokinetic parameters for each subject separately and the second stage uses the individual parameter estimates for statistical inference. This two-stage approach is not applicable in sparse sampling situations where only one sample is available per subject. Nonlinear models are often applied to analyze pharmacokinetic data assessed in such serial sampling designs. Modelling approaches are suitable provided that the form of the true model is known, which is rarely the case in early stages of drug development. This paper presents an alternative approach to estimate pharmacokinetic parameters based on non-compartmental and asymptotic theories in the case of serial sampling when a drug is given as an intravenous bolus. The statistical properties of estimators of the pharmacokinetic parameters are investigated and evaluated using Monte Carlo simulations.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Asymptotic</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Non-compartmental</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Pharmacokinetics</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">PK parameters</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Serial sampling</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Sparse sampling</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Jaki, Thomas</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Journal of Pharmacokinetics and Biopharmaceutics</subfield><subfield code="d">Kluwer Academic Publishers-Plenum Publishers, 1973</subfield><subfield code="g">36(2009), 5 vom: 22. Okt.</subfield><subfield code="w">(DE-627)SPR014694166</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:36</subfield><subfield code="g">year:2009</subfield><subfield code="g">number:5</subfield><subfield code="g">day:22</subfield><subfield code="g">month:10</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s10928-009-9133-9</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">36</subfield><subfield code="j">2009</subfield><subfield code="e">5</subfield><subfield code="b">22</subfield><subfield code="c">10</subfield></datafield></record></collection>
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