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Population Pharmacokinetics of Durvalumab in Cancer Patients and Association With Longitudinal Biomarkers of Disease Status

The objectives of this analysis were to develop a population pharmacokinetics (PK) model of durvalumab, an anti‐PD‐L1 antibody, and quantify the impact of baseline and time‐varying patient/disease characteristics on PK. Pooled data from two studies (1,409 patients providing 7,407 PK samples) were an...

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Autores principales: Baverel, Paul G., Dubois, Vincent F.S., Jin, Chao Yu, Zheng, Yanan, Song, Xuyang, Jin, Xiaoping, Mukhopadhyay, Pralay, Gupta, Ashok, Dennis, Phillip A., Ben, Yong, Vicini, Paolo, Roskos, Lorin, Narwal, Rajesh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5887840/
https://www.ncbi.nlm.nih.gov/pubmed/29243223
http://dx.doi.org/10.1002/cpt.982
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author Baverel, Paul G.
Dubois, Vincent F.S.
Jin, Chao Yu
Zheng, Yanan
Song, Xuyang
Jin, Xiaoping
Mukhopadhyay, Pralay
Gupta, Ashok
Dennis, Phillip A.
Ben, Yong
Vicini, Paolo
Roskos, Lorin
Narwal, Rajesh
author_facet Baverel, Paul G.
Dubois, Vincent F.S.
Jin, Chao Yu
Zheng, Yanan
Song, Xuyang
Jin, Xiaoping
Mukhopadhyay, Pralay
Gupta, Ashok
Dennis, Phillip A.
Ben, Yong
Vicini, Paolo
Roskos, Lorin
Narwal, Rajesh
author_sort Baverel, Paul G.
collection PubMed
description The objectives of this analysis were to develop a population pharmacokinetics (PK) model of durvalumab, an anti‐PD‐L1 antibody, and quantify the impact of baseline and time‐varying patient/disease characteristics on PK. Pooled data from two studies (1,409 patients providing 7,407 PK samples) were analyzed with nonlinear mixed effects modeling. Durvalumab PK was best described by a two‐compartment model with both linear and nonlinear clearances. Three candidate models were evaluated: a time‐invariant clearance (CL) model, an empirical time‐varying CL model, and a semimechanistic time‐varying CL model incorporating longitudinal covariates related to disease status (tumor shrinkage and albumin). The data supported a slight decrease in durvalumab clearance with time and suggested that it may be associated with a decrease in nonspecific protein catabolic rate among cancer patients who benefit from therapy. No covariates were clinically relevant, indicating no need for dose adjustment. Simulations indicated similar overall PK exposures following weight‐based and flat‐dosing regimens.
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spelling pubmed-58878402018-04-10 Population Pharmacokinetics of Durvalumab in Cancer Patients and Association With Longitudinal Biomarkers of Disease Status Baverel, Paul G. Dubois, Vincent F.S. Jin, Chao Yu Zheng, Yanan Song, Xuyang Jin, Xiaoping Mukhopadhyay, Pralay Gupta, Ashok Dennis, Phillip A. Ben, Yong Vicini, Paolo Roskos, Lorin Narwal, Rajesh Clin Pharmacol Ther Research The objectives of this analysis were to develop a population pharmacokinetics (PK) model of durvalumab, an anti‐PD‐L1 antibody, and quantify the impact of baseline and time‐varying patient/disease characteristics on PK. Pooled data from two studies (1,409 patients providing 7,407 PK samples) were analyzed with nonlinear mixed effects modeling. Durvalumab PK was best described by a two‐compartment model with both linear and nonlinear clearances. Three candidate models were evaluated: a time‐invariant clearance (CL) model, an empirical time‐varying CL model, and a semimechanistic time‐varying CL model incorporating longitudinal covariates related to disease status (tumor shrinkage and albumin). The data supported a slight decrease in durvalumab clearance with time and suggested that it may be associated with a decrease in nonspecific protein catabolic rate among cancer patients who benefit from therapy. No covariates were clinically relevant, indicating no need for dose adjustment. Simulations indicated similar overall PK exposures following weight‐based and flat‐dosing regimens. John Wiley and Sons Inc. 2018-02-02 2018-04 /pmc/articles/PMC5887840/ /pubmed/29243223 http://dx.doi.org/10.1002/cpt.982 Text en © 2018, The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Research
Baverel, Paul G.
Dubois, Vincent F.S.
Jin, Chao Yu
Zheng, Yanan
Song, Xuyang
Jin, Xiaoping
Mukhopadhyay, Pralay
Gupta, Ashok
Dennis, Phillip A.
Ben, Yong
Vicini, Paolo
Roskos, Lorin
Narwal, Rajesh
Population Pharmacokinetics of Durvalumab in Cancer Patients and Association With Longitudinal Biomarkers of Disease Status
title Population Pharmacokinetics of Durvalumab in Cancer Patients and Association With Longitudinal Biomarkers of Disease Status
title_full Population Pharmacokinetics of Durvalumab in Cancer Patients and Association With Longitudinal Biomarkers of Disease Status
title_fullStr Population Pharmacokinetics of Durvalumab in Cancer Patients and Association With Longitudinal Biomarkers of Disease Status
title_full_unstemmed Population Pharmacokinetics of Durvalumab in Cancer Patients and Association With Longitudinal Biomarkers of Disease Status
title_short Population Pharmacokinetics of Durvalumab in Cancer Patients and Association With Longitudinal Biomarkers of Disease Status
title_sort population pharmacokinetics of durvalumab in cancer patients and association with longitudinal biomarkers of disease status
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5887840/
https://www.ncbi.nlm.nih.gov/pubmed/29243223
http://dx.doi.org/10.1002/cpt.982
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