Population PBPK modelling of trastuzumab: a framework for quantifying and predicting inter-individual variability
Abstract In this work we proposed a population physiologically-based pharmacokinetic (popPBPK) framework for quantifying and predicting inter-individual pharmacokinetic variability using the anti-HER2 monoclonal antibody (mAb) trastuzumab as an example. First, a PBPK model was developed to account f...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Malik, Paul R. V. [verfasserIn] Hamadeh, Abdullah [verfasserIn] Phipps, Colin [verfasserIn] Edginton, Andrea N. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Journal of Pharmacokinetics and Biopharmaceutics - Kluwer Academic Publishers-Plenum Publishers, 1973, 44(2017), 3 vom: 04. März, Seite 277-290 |
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| Übergeordnetes Werk: |
volume:44 ; year:2017 ; number:3 ; day:04 ; month:03 ; pages:277-290 |
| Links: |
|---|
| DOI / URN: |
10.1007/s10928-017-9515-3 |
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SPR014713047 |
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| 520 | |a Abstract In this work we proposed a population physiologically-based pharmacokinetic (popPBPK) framework for quantifying and predicting inter-individual pharmacokinetic variability using the anti-HER2 monoclonal antibody (mAb) trastuzumab as an example. First, a PBPK model was developed to account for the possible mechanistic sources of variability. Within the model, five key factors that contribute to variability were identified and the nature of their contribution was quantified with local and global sensitivity analyses. The five key factors were the concentration of membrane-bound HER2 (%$Ag%$), the convective flow rate of mAb through vascular pores (%$F2%$), the endocytic transport rate of mAb through vascular endothelium (%$CL_{up}%$), the degradation rate of mAb-HER2 complexes (%$K_{deg}^{Ag}%$) and the concentration of shed HER2 extracellular domain in circulation (%$ECD%$). %$F2%$ was the most important parameter governing trastuzumab distribution into tissues and primarily affected variability in the first 500 h post-administration. %$Ag%$ was the most significant contributor to variability in clearance. These findings were used together with population generation methods to accurately predict the observed variability in four experimental trials with trastuzumab. To explore anthropometric sources of variability, virtual populations were created to represent participants in the four experimental trials. Using populations with only their expected anthropometric diversity resulted in under-prediction of the observed inter-individual variability. Adapting the populations to include literature-based variability around the five key parameters enabled accurate predictions of the variability in the four trials. The successful application of this framework demonstrates the utility of popPBPK methods to understand the mechanistic underpinnings of pharmacokinetic variability. | ||
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10.1007/s10928-017-9515-3 doi (DE-627)SPR014713047 (SPR)s10928-017-9515-3-e DE-627 ger DE-627 rakwb eng Malik, Paul R. V. verfasserin aut Population PBPK modelling of trastuzumab: a framework for quantifying and predicting inter-individual variability 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this work we proposed a population physiologically-based pharmacokinetic (popPBPK) framework for quantifying and predicting inter-individual pharmacokinetic variability using the anti-HER2 monoclonal antibody (mAb) trastuzumab as an example. First, a PBPK model was developed to account for the possible mechanistic sources of variability. Within the model, five key factors that contribute to variability were identified and the nature of their contribution was quantified with local and global sensitivity analyses. The five key factors were the concentration of membrane-bound HER2 (%$Ag%$), the convective flow rate of mAb through vascular pores (%$F2%$), the endocytic transport rate of mAb through vascular endothelium (%$CL_{up}%$), the degradation rate of mAb-HER2 complexes (%$K_{deg}^{Ag}%$) and the concentration of shed HER2 extracellular domain in circulation (%$ECD%$). %$F2%$ was the most important parameter governing trastuzumab distribution into tissues and primarily affected variability in the first 500 h post-administration. %$Ag%$ was the most significant contributor to variability in clearance. These findings were used together with population generation methods to accurately predict the observed variability in four experimental trials with trastuzumab. To explore anthropometric sources of variability, virtual populations were created to represent participants in the four experimental trials. Using populations with only their expected anthropometric diversity resulted in under-prediction of the observed inter-individual variability. Adapting the populations to include literature-based variability around the five key parameters enabled accurate predictions of the variability in the four trials. The successful application of this framework demonstrates the utility of popPBPK methods to understand the mechanistic underpinnings of pharmacokinetic variability. Pharmacokinetics (dpeaa)DE-He213 PBPK (dpeaa)DE-He213 Monoclonal antibody (dpeaa)DE-He213 Inter-individual variability (dpeaa)DE-He213 Hamadeh, Abdullah verfasserin aut Phipps, Colin verfasserin aut Edginton, Andrea N. verfasserin aut Enthalten in Journal of Pharmacokinetics and Biopharmaceutics Kluwer Academic Publishers-Plenum Publishers, 1973 44(2017), 3 vom: 04. März, Seite 277-290 (DE-627)SPR014694166 nnns volume:44 year:2017 number:3 day:04 month:03 pages:277-290 https://dx.doi.org/10.1007/s10928-017-9515-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_40 AR 44 2017 3 04 03 277-290 |
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10.1007/s10928-017-9515-3 doi (DE-627)SPR014713047 (SPR)s10928-017-9515-3-e DE-627 ger DE-627 rakwb eng Malik, Paul R. V. verfasserin aut Population PBPK modelling of trastuzumab: a framework for quantifying and predicting inter-individual variability 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this work we proposed a population physiologically-based pharmacokinetic (popPBPK) framework for quantifying and predicting inter-individual pharmacokinetic variability using the anti-HER2 monoclonal antibody (mAb) trastuzumab as an example. First, a PBPK model was developed to account for the possible mechanistic sources of variability. Within the model, five key factors that contribute to variability were identified and the nature of their contribution was quantified with local and global sensitivity analyses. The five key factors were the concentration of membrane-bound HER2 (%$Ag%$), the convective flow rate of mAb through vascular pores (%$F2%$), the endocytic transport rate of mAb through vascular endothelium (%$CL_{up}%$), the degradation rate of mAb-HER2 complexes (%$K_{deg}^{Ag}%$) and the concentration of shed HER2 extracellular domain in circulation (%$ECD%$). %$F2%$ was the most important parameter governing trastuzumab distribution into tissues and primarily affected variability in the first 500 h post-administration. %$Ag%$ was the most significant contributor to variability in clearance. These findings were used together with population generation methods to accurately predict the observed variability in four experimental trials with trastuzumab. To explore anthropometric sources of variability, virtual populations were created to represent participants in the four experimental trials. Using populations with only their expected anthropometric diversity resulted in under-prediction of the observed inter-individual variability. Adapting the populations to include literature-based variability around the five key parameters enabled accurate predictions of the variability in the four trials. The successful application of this framework demonstrates the utility of popPBPK methods to understand the mechanistic underpinnings of pharmacokinetic variability. Pharmacokinetics (dpeaa)DE-He213 PBPK (dpeaa)DE-He213 Monoclonal antibody (dpeaa)DE-He213 Inter-individual variability (dpeaa)DE-He213 Hamadeh, Abdullah verfasserin aut Phipps, Colin verfasserin aut Edginton, Andrea N. verfasserin aut Enthalten in Journal of Pharmacokinetics and Biopharmaceutics Kluwer Academic Publishers-Plenum Publishers, 1973 44(2017), 3 vom: 04. März, Seite 277-290 (DE-627)SPR014694166 nnns volume:44 year:2017 number:3 day:04 month:03 pages:277-290 https://dx.doi.org/10.1007/s10928-017-9515-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_40 AR 44 2017 3 04 03 277-290 |
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10.1007/s10928-017-9515-3 doi (DE-627)SPR014713047 (SPR)s10928-017-9515-3-e DE-627 ger DE-627 rakwb eng Malik, Paul R. V. verfasserin aut Population PBPK modelling of trastuzumab: a framework for quantifying and predicting inter-individual variability 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this work we proposed a population physiologically-based pharmacokinetic (popPBPK) framework for quantifying and predicting inter-individual pharmacokinetic variability using the anti-HER2 monoclonal antibody (mAb) trastuzumab as an example. First, a PBPK model was developed to account for the possible mechanistic sources of variability. Within the model, five key factors that contribute to variability were identified and the nature of their contribution was quantified with local and global sensitivity analyses. The five key factors were the concentration of membrane-bound HER2 (%$Ag%$), the convective flow rate of mAb through vascular pores (%$F2%$), the endocytic transport rate of mAb through vascular endothelium (%$CL_{up}%$), the degradation rate of mAb-HER2 complexes (%$K_{deg}^{Ag}%$) and the concentration of shed HER2 extracellular domain in circulation (%$ECD%$). %$F2%$ was the most important parameter governing trastuzumab distribution into tissues and primarily affected variability in the first 500 h post-administration. %$Ag%$ was the most significant contributor to variability in clearance. These findings were used together with population generation methods to accurately predict the observed variability in four experimental trials with trastuzumab. To explore anthropometric sources of variability, virtual populations were created to represent participants in the four experimental trials. Using populations with only their expected anthropometric diversity resulted in under-prediction of the observed inter-individual variability. Adapting the populations to include literature-based variability around the five key parameters enabled accurate predictions of the variability in the four trials. The successful application of this framework demonstrates the utility of popPBPK methods to understand the mechanistic underpinnings of pharmacokinetic variability. Pharmacokinetics (dpeaa)DE-He213 PBPK (dpeaa)DE-He213 Monoclonal antibody (dpeaa)DE-He213 Inter-individual variability (dpeaa)DE-He213 Hamadeh, Abdullah verfasserin aut Phipps, Colin verfasserin aut Edginton, Andrea N. verfasserin aut Enthalten in Journal of Pharmacokinetics and Biopharmaceutics Kluwer Academic Publishers-Plenum Publishers, 1973 44(2017), 3 vom: 04. März, Seite 277-290 (DE-627)SPR014694166 nnns volume:44 year:2017 number:3 day:04 month:03 pages:277-290 https://dx.doi.org/10.1007/s10928-017-9515-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_40 AR 44 2017 3 04 03 277-290 |
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10.1007/s10928-017-9515-3 doi (DE-627)SPR014713047 (SPR)s10928-017-9515-3-e DE-627 ger DE-627 rakwb eng Malik, Paul R. V. verfasserin aut Population PBPK modelling of trastuzumab: a framework for quantifying and predicting inter-individual variability 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this work we proposed a population physiologically-based pharmacokinetic (popPBPK) framework for quantifying and predicting inter-individual pharmacokinetic variability using the anti-HER2 monoclonal antibody (mAb) trastuzumab as an example. First, a PBPK model was developed to account for the possible mechanistic sources of variability. Within the model, five key factors that contribute to variability were identified and the nature of their contribution was quantified with local and global sensitivity analyses. The five key factors were the concentration of membrane-bound HER2 (%$Ag%$), the convective flow rate of mAb through vascular pores (%$F2%$), the endocytic transport rate of mAb through vascular endothelium (%$CL_{up}%$), the degradation rate of mAb-HER2 complexes (%$K_{deg}^{Ag}%$) and the concentration of shed HER2 extracellular domain in circulation (%$ECD%$). %$F2%$ was the most important parameter governing trastuzumab distribution into tissues and primarily affected variability in the first 500 h post-administration. %$Ag%$ was the most significant contributor to variability in clearance. These findings were used together with population generation methods to accurately predict the observed variability in four experimental trials with trastuzumab. To explore anthropometric sources of variability, virtual populations were created to represent participants in the four experimental trials. Using populations with only their expected anthropometric diversity resulted in under-prediction of the observed inter-individual variability. Adapting the populations to include literature-based variability around the five key parameters enabled accurate predictions of the variability in the four trials. The successful application of this framework demonstrates the utility of popPBPK methods to understand the mechanistic underpinnings of pharmacokinetic variability. Pharmacokinetics (dpeaa)DE-He213 PBPK (dpeaa)DE-He213 Monoclonal antibody (dpeaa)DE-He213 Inter-individual variability (dpeaa)DE-He213 Hamadeh, Abdullah verfasserin aut Phipps, Colin verfasserin aut Edginton, Andrea N. verfasserin aut Enthalten in Journal of Pharmacokinetics and Biopharmaceutics Kluwer Academic Publishers-Plenum Publishers, 1973 44(2017), 3 vom: 04. März, Seite 277-290 (DE-627)SPR014694166 nnns volume:44 year:2017 number:3 day:04 month:03 pages:277-290 https://dx.doi.org/10.1007/s10928-017-9515-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_40 AR 44 2017 3 04 03 277-290 |
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10.1007/s10928-017-9515-3 doi (DE-627)SPR014713047 (SPR)s10928-017-9515-3-e DE-627 ger DE-627 rakwb eng Malik, Paul R. V. verfasserin aut Population PBPK modelling of trastuzumab: a framework for quantifying and predicting inter-individual variability 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this work we proposed a population physiologically-based pharmacokinetic (popPBPK) framework for quantifying and predicting inter-individual pharmacokinetic variability using the anti-HER2 monoclonal antibody (mAb) trastuzumab as an example. First, a PBPK model was developed to account for the possible mechanistic sources of variability. Within the model, five key factors that contribute to variability were identified and the nature of their contribution was quantified with local and global sensitivity analyses. The five key factors were the concentration of membrane-bound HER2 (%$Ag%$), the convective flow rate of mAb through vascular pores (%$F2%$), the endocytic transport rate of mAb through vascular endothelium (%$CL_{up}%$), the degradation rate of mAb-HER2 complexes (%$K_{deg}^{Ag}%$) and the concentration of shed HER2 extracellular domain in circulation (%$ECD%$). %$F2%$ was the most important parameter governing trastuzumab distribution into tissues and primarily affected variability in the first 500 h post-administration. %$Ag%$ was the most significant contributor to variability in clearance. These findings were used together with population generation methods to accurately predict the observed variability in four experimental trials with trastuzumab. To explore anthropometric sources of variability, virtual populations were created to represent participants in the four experimental trials. Using populations with only their expected anthropometric diversity resulted in under-prediction of the observed inter-individual variability. Adapting the populations to include literature-based variability around the five key parameters enabled accurate predictions of the variability in the four trials. The successful application of this framework demonstrates the utility of popPBPK methods to understand the mechanistic underpinnings of pharmacokinetic variability. Pharmacokinetics (dpeaa)DE-He213 PBPK (dpeaa)DE-He213 Monoclonal antibody (dpeaa)DE-He213 Inter-individual variability (dpeaa)DE-He213 Hamadeh, Abdullah verfasserin aut Phipps, Colin verfasserin aut Edginton, Andrea N. verfasserin aut Enthalten in Journal of Pharmacokinetics and Biopharmaceutics Kluwer Academic Publishers-Plenum Publishers, 1973 44(2017), 3 vom: 04. März, Seite 277-290 (DE-627)SPR014694166 nnns volume:44 year:2017 number:3 day:04 month:03 pages:277-290 https://dx.doi.org/10.1007/s10928-017-9515-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_40 AR 44 2017 3 04 03 277-290 |
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Population PBPK modelling of trastuzumab: a framework for quantifying and predicting inter-individual variability |
| author_sort |
Malik, Paul R. V. |
| journal |
Journal of Pharmacokinetics and Biopharmaceutics |
| journalStr |
Journal of Pharmacokinetics and Biopharmaceutics |
| lang_code |
eng |
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2017 |
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| container_start_page |
277 |
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Malik, Paul R. V. Hamadeh, Abdullah Phipps, Colin Edginton, Andrea N. |
| container_volume |
44 |
| format_se |
Elektronische Aufsätze |
| author-letter |
Malik, Paul R. V. |
| doi_str_mv |
10.1007/s10928-017-9515-3 |
| author2-role |
verfasserin |
| title_sort |
population pbpk modelling of trastuzumab: a framework for quantifying and predicting inter-individual variability |
| title_auth |
Population PBPK modelling of trastuzumab: a framework for quantifying and predicting inter-individual variability |
| abstract |
Abstract In this work we proposed a population physiologically-based pharmacokinetic (popPBPK) framework for quantifying and predicting inter-individual pharmacokinetic variability using the anti-HER2 monoclonal antibody (mAb) trastuzumab as an example. First, a PBPK model was developed to account for the possible mechanistic sources of variability. Within the model, five key factors that contribute to variability were identified and the nature of their contribution was quantified with local and global sensitivity analyses. The five key factors were the concentration of membrane-bound HER2 (%$Ag%$), the convective flow rate of mAb through vascular pores (%$F2%$), the endocytic transport rate of mAb through vascular endothelium (%$CL_{up}%$), the degradation rate of mAb-HER2 complexes (%$K_{deg}^{Ag}%$) and the concentration of shed HER2 extracellular domain in circulation (%$ECD%$). %$F2%$ was the most important parameter governing trastuzumab distribution into tissues and primarily affected variability in the first 500 h post-administration. %$Ag%$ was the most significant contributor to variability in clearance. These findings were used together with population generation methods to accurately predict the observed variability in four experimental trials with trastuzumab. To explore anthropometric sources of variability, virtual populations were created to represent participants in the four experimental trials. Using populations with only their expected anthropometric diversity resulted in under-prediction of the observed inter-individual variability. Adapting the populations to include literature-based variability around the five key parameters enabled accurate predictions of the variability in the four trials. The successful application of this framework demonstrates the utility of popPBPK methods to understand the mechanistic underpinnings of pharmacokinetic variability. |
| abstractGer |
Abstract In this work we proposed a population physiologically-based pharmacokinetic (popPBPK) framework for quantifying and predicting inter-individual pharmacokinetic variability using the anti-HER2 monoclonal antibody (mAb) trastuzumab as an example. First, a PBPK model was developed to account for the possible mechanistic sources of variability. Within the model, five key factors that contribute to variability were identified and the nature of their contribution was quantified with local and global sensitivity analyses. The five key factors were the concentration of membrane-bound HER2 (%$Ag%$), the convective flow rate of mAb through vascular pores (%$F2%$), the endocytic transport rate of mAb through vascular endothelium (%$CL_{up}%$), the degradation rate of mAb-HER2 complexes (%$K_{deg}^{Ag}%$) and the concentration of shed HER2 extracellular domain in circulation (%$ECD%$). %$F2%$ was the most important parameter governing trastuzumab distribution into tissues and primarily affected variability in the first 500 h post-administration. %$Ag%$ was the most significant contributor to variability in clearance. These findings were used together with population generation methods to accurately predict the observed variability in four experimental trials with trastuzumab. To explore anthropometric sources of variability, virtual populations were created to represent participants in the four experimental trials. Using populations with only their expected anthropometric diversity resulted in under-prediction of the observed inter-individual variability. Adapting the populations to include literature-based variability around the five key parameters enabled accurate predictions of the variability in the four trials. The successful application of this framework demonstrates the utility of popPBPK methods to understand the mechanistic underpinnings of pharmacokinetic variability. |
| abstract_unstemmed |
Abstract In this work we proposed a population physiologically-based pharmacokinetic (popPBPK) framework for quantifying and predicting inter-individual pharmacokinetic variability using the anti-HER2 monoclonal antibody (mAb) trastuzumab as an example. First, a PBPK model was developed to account for the possible mechanistic sources of variability. Within the model, five key factors that contribute to variability were identified and the nature of their contribution was quantified with local and global sensitivity analyses. The five key factors were the concentration of membrane-bound HER2 (%$Ag%$), the convective flow rate of mAb through vascular pores (%$F2%$), the endocytic transport rate of mAb through vascular endothelium (%$CL_{up}%$), the degradation rate of mAb-HER2 complexes (%$K_{deg}^{Ag}%$) and the concentration of shed HER2 extracellular domain in circulation (%$ECD%$). %$F2%$ was the most important parameter governing trastuzumab distribution into tissues and primarily affected variability in the first 500 h post-administration. %$Ag%$ was the most significant contributor to variability in clearance. These findings were used together with population generation methods to accurately predict the observed variability in four experimental trials with trastuzumab. To explore anthropometric sources of variability, virtual populations were created to represent participants in the four experimental trials. Using populations with only their expected anthropometric diversity resulted in under-prediction of the observed inter-individual variability. Adapting the populations to include literature-based variability around the five key parameters enabled accurate predictions of the variability in the four trials. The successful application of this framework demonstrates the utility of popPBPK methods to understand the mechanistic underpinnings of pharmacokinetic variability. |
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| title_short |
Population PBPK modelling of trastuzumab: a framework for quantifying and predicting inter-individual variability |
| url |
https://dx.doi.org/10.1007/s10928-017-9515-3 |
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| author2 |
Hamadeh, Abdullah Phipps, Colin Edginton, Andrea N. |
| author2Str |
Hamadeh, Abdullah Phipps, Colin Edginton, Andrea N. |
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| doi_str |
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| up_date |
2024-07-04T02:47:22.855Z |
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