Population pharmacokinetic models of anti-PD-1 mAbs in patients with multiple tumor types: A systematic review

Aims and backgroundA number of population pharmacokinetic (PPK) models of anti-programmed cell death-1 (PD-1) monoclonal antibodies (mAbs) in multiple tumor types have been published to characterize the influencing factors of their pharmacokinetics. This review described PPK models of anti-PD-1 mAbs...

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Main Authors: Jingyuan Shang, Lin Huang, Jing Huang, Xiaolei Ren, Yi Liu, Yufei Feng
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-08-01
Series:Frontiers in Immunology
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fimmu.2022.871372/full
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author Jingyuan Shang
Jingyuan Shang
Lin Huang
Jing Huang
Xiaolei Ren
Yi Liu
Yufei Feng
author_facet Jingyuan Shang
Jingyuan Shang
Lin Huang
Jing Huang
Xiaolei Ren
Yi Liu
Yufei Feng
author_sort Jingyuan Shang
collection DOAJ
description Aims and backgroundA number of population pharmacokinetic (PPK) models of anti-programmed cell death-1 (PD-1) monoclonal antibodies (mAbs) in multiple tumor types have been published to characterize the influencing factors of their pharmacokinetics. This review described PPK models of anti-PD-1 mAbs that investigate the magnitude and types of covariate effects in PK parameters, provide a reference for building PPK models of other anti-PD-1 mAbs, and identify areas requiring additional research to facilitate the application of PPK models.MethodsA systematic search for analyses of PPK models of eleven anti-PD-1 mAbs on the market that were carried out in humans was conducted using PubMed, Embase, and the Cochrane Library. The search covered the period from the inception of the databases to April 2022.ResultsCurrently, there are fourteen analyses on PPK models of anti-PD-1 mAbs summarized in this review, including seven models that refer to nivolumab, four referring to pembrolizumab, one referring to cemiplimab, one referring to camrelizumab, and one referred to dostarlimab. Most analyses described the pharmacokinetics of anti-PD-1 mAbs with a two-compartment model with time-varying clearance (CL) and a sigmoidal maximum effect. The estimated CL and volume of distribution in the central (VC) ranged from 0.179 to 0.290 L/day and 2.98 to 4.46 L, respectively. The median (range) of interindividual variability (IIV) for CL and VC was 30.9% (8.7%–50.8%) and 29.0% (4.32%–40.7%), respectively. The commonly identified significant covariates were body weight (BW) on CL and VC, and albumin (ALB), tumor type, sex, and performance status (PS) on CL. Other less assessed significant covariates included lactate dehydrogenase (LDH), immunoglobulin G (IgG), ipilimumab coadministration (IPICO) on CL, and body mass index (BMI), malignant pleural mesothelioma (MESO) on VC.ConclusionThis review provides detailed information about the characteristics of PPK models of anti-PD-1 mAbs, the effects of covariates on PK parameters, and the current status of the application of the models. ALB, BW, specific tumor type, sex, and PS should be considered for the future development of the PPK model of anti-PD-1 mAbs. Other potential covariates that were assessed less frequently but still have significance (e.g., LDH, IgG, and IPICO) should not be ignored. Thus, further research and thorough investigation are needed to assess new or potential covariates, which will pave the way for personalized anti-PD-1 mAbs therapy.
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spelling doaj.art-4f76944f1e2e415baae0f6b690e40f582022-12-22T02:07:20ZengFrontiers Media S.A.Frontiers in Immunology1664-32242022-08-011310.3389/fimmu.2022.871372871372Population pharmacokinetic models of anti-PD-1 mAbs in patients with multiple tumor types: A systematic reviewJingyuan Shang0Jingyuan Shang1Lin Huang2Jing Huang3Xiaolei Ren4Yi Liu5Yufei Feng6Department of Pharmacy, Peking University People’s Hospital, Beijing, ChinaFaculty of Life Sciences and Biopharmaceuticals, Shenyang Pharmceutical University, Shenyang, ChinaDepartment of Pharmacy, Peking University People’s Hospital, Beijing, ChinaDepartment of Pharmacy, Peking University People’s Hospital, Beijing, ChinaDepartment of Pharmacy, Peking University People’s Hospital, Beijing, ChinaDepartment of Pharmacy, Peking University People’s Hospital, Beijing, ChinaDepartment of Pharmacy, Peking University People’s Hospital, Beijing, ChinaAims and backgroundA number of population pharmacokinetic (PPK) models of anti-programmed cell death-1 (PD-1) monoclonal antibodies (mAbs) in multiple tumor types have been published to characterize the influencing factors of their pharmacokinetics. This review described PPK models of anti-PD-1 mAbs that investigate the magnitude and types of covariate effects in PK parameters, provide a reference for building PPK models of other anti-PD-1 mAbs, and identify areas requiring additional research to facilitate the application of PPK models.MethodsA systematic search for analyses of PPK models of eleven anti-PD-1 mAbs on the market that were carried out in humans was conducted using PubMed, Embase, and the Cochrane Library. The search covered the period from the inception of the databases to April 2022.ResultsCurrently, there are fourteen analyses on PPK models of anti-PD-1 mAbs summarized in this review, including seven models that refer to nivolumab, four referring to pembrolizumab, one referring to cemiplimab, one referring to camrelizumab, and one referred to dostarlimab. Most analyses described the pharmacokinetics of anti-PD-1 mAbs with a two-compartment model with time-varying clearance (CL) and a sigmoidal maximum effect. The estimated CL and volume of distribution in the central (VC) ranged from 0.179 to 0.290 L/day and 2.98 to 4.46 L, respectively. The median (range) of interindividual variability (IIV) for CL and VC was 30.9% (8.7%–50.8%) and 29.0% (4.32%–40.7%), respectively. The commonly identified significant covariates were body weight (BW) on CL and VC, and albumin (ALB), tumor type, sex, and performance status (PS) on CL. Other less assessed significant covariates included lactate dehydrogenase (LDH), immunoglobulin G (IgG), ipilimumab coadministration (IPICO) on CL, and body mass index (BMI), malignant pleural mesothelioma (MESO) on VC.ConclusionThis review provides detailed information about the characteristics of PPK models of anti-PD-1 mAbs, the effects of covariates on PK parameters, and the current status of the application of the models. ALB, BW, specific tumor type, sex, and PS should be considered for the future development of the PPK model of anti-PD-1 mAbs. Other potential covariates that were assessed less frequently but still have significance (e.g., LDH, IgG, and IPICO) should not be ignored. Thus, further research and thorough investigation are needed to assess new or potential covariates, which will pave the way for personalized anti-PD-1 mAbs therapy.https://www.frontiersin.org/articles/10.3389/fimmu.2022.871372/fullanti-PD-1 mAbsimmune checkpoint inhibitorspopulation pharmacokineticsPPK modelsystematic review
spellingShingle Jingyuan Shang
Jingyuan Shang
Lin Huang
Jing Huang
Xiaolei Ren
Yi Liu
Yufei Feng
Population pharmacokinetic models of anti-PD-1 mAbs in patients with multiple tumor types: A systematic review
Frontiers in Immunology
anti-PD-1 mAbs
immune checkpoint inhibitors
population pharmacokinetics
PPK model
systematic review
title Population pharmacokinetic models of anti-PD-1 mAbs in patients with multiple tumor types: A systematic review
title_full Population pharmacokinetic models of anti-PD-1 mAbs in patients with multiple tumor types: A systematic review
title_fullStr Population pharmacokinetic models of anti-PD-1 mAbs in patients with multiple tumor types: A systematic review
title_full_unstemmed Population pharmacokinetic models of anti-PD-1 mAbs in patients with multiple tumor types: A systematic review
title_short Population pharmacokinetic models of anti-PD-1 mAbs in patients with multiple tumor types: A systematic review
title_sort population pharmacokinetic models of anti pd 1 mabs in patients with multiple tumor types a systematic review
topic anti-PD-1 mAbs
immune checkpoint inhibitors
population pharmacokinetics
PPK model
systematic review
url https://www.frontiersin.org/articles/10.3389/fimmu.2022.871372/full
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