Evidence map›Paper›PMID 41543435›Full record

ArticleCPT: pharmacometrics & systems pharmacology2026

Albumin Levels Are Predictive of Cachexia-Induced Time-Dependent Clearance of Therapeutic Antibodies: A Physiologically Based Pharmacokinetic Model of Durvalumab.

Jeffrey R Proctor, Harvey Wong

Abstract read
In one paragraph

Article in CPT: pharmacometrics & systems pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Jeffrey R ProctorFaculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada.ORCID https://orcid.org/0000-0002-2274-5607
Harvey WongFaculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada.ORCID https://orcid.org/0000-0003-1550-5071

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cachexia is a metabolic condition that accelerates the clearance of monoclonal antibodies in cancer patients and is a known mechanism causing time-dependent clearance. Successful anticancer treatment often ameliorates symptoms of cachexia, reducing the drug clearance over time especially in patients who respond. Serum albumin level is a common biomarker of cachexia that is frequently associated with antibody drug clearance. Physiologically based pharmacokinetic (PBPK) models of antibody drugs have incorporated albumin metabolism but have not been applied to describe time-varying clearance due to improvement in cachexia. The objective of this analysis was to evaluate albumin levels as a biomarker that is predictive of changes in antibody clearance due to cachexia. A PBPK model that jointly describes metabolism of albumin and biologic drugs was fitted to longitudinal albumin data from cancer patients treated with durvalumab and was used to predict changes in durvalumab clearance over time. PBPK model predictions were compared to empirical population pharmacokinetic (PK) models of durvalumab and other checkpoint inhibitors fitted directly to clinical PK. The model fitted the observed albumin data in cancer patients closely, and the three fitted parameters showed low uncertainty (RSE < 10%). By accounting for longitudinal albumin data in patients, the PBPK model recapitulated the observed magnitude of the change in clearance of durvalumab without fitting to clinical PK data. The model simulation demonstrated that utilization of albumin levels as a marker of cachexia in PBPK models can be used to mechanistically predict time-dependent clearance of monoclonal antibodies.

Indexed as

Antibodies, MonoclonalAntineoplastic Agents, ImmunologicalCachexiaModels, BiologicalNeoplasmsSerum AlbuminBiomarkersFemaleHumansMetabolic Clearance RateAntibodies, MonoclonalAntineoplastic Agents, ImmunologicalBiomarkersdurvalumabSerum Albumincachexiamonoclonal antibodyoncologyPBPK modelpopulation pharmacokineticstherapeutic antibodytime‐dependent clearance

Identifiers

PMID41543435
PMCPMC12823314

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