Cited by 82Monoclonal and Polyclonal Antibodies ResearchBiosimilars and Bioanalytical MethodsPharmaceutical studies and practices

Potential Sources of Inter-Subject Variability in Monoclonal Antibody Pharmacokinetics

Gill, Katherine L., Machavaram, Krishna K., Rose, Rachel H., Chetty, Manoranjenni·2016·Clinical Pharmacokinetics

Abstract

Understanding inter-subject variability in drug pharmacokinetics and pharmacodynamics is important to ensure that all patients attain suitable drug exposure to achieve efficacy and avoid toxicity. Inter-subject variability in the pharmacokinetics of therapeutic monoclonal antibodies (mAbs) is generally moderate to high; however, the factors responsible for the high inter-subject variability have not been comprehensively reviewed. In this review, the extent of inter-subject variability for mAb pharmacokinetics is presented and potential factors contributing to this variability are explored and summarised. Disease status, age, sex, ethnicity, body size, genetic polymorphisms, concomitant medication, co-morbidities, immune status and multiple other patient-specific details have been considered. The inter-subject variability for mAb pharmacokinetics most likely depends on the complex interplay of multiple factors. However, studies aimed at investigating the reasons for the inter-subject variability are sparse. Population pharmacokinetic models and physiologically based pharmacokinetic models are useful tools to identify important covariates, aiding in the understanding of factors contributing to inter-subject variability. Further understanding of inter-subject variability in pharmacokinetics should aid in development of dosing regimens that are more appropriate.

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Crossref · 10.1007/s40262-015-0361-4

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  • Many factors, such as antibody properties (hydrophobicity, charge, glycosylation patterns), intersubject variability (disease status, body size, genetic polymorphisms, concomitant medication, comorbidities), and immune-mediated response generated by mAbs administration, can also impact mAb clearance.

    “Many other factors, such as antibody properties (hydrophobicity, charge,38 glycosylation patterns39), intersubject variability (disease status, body size, genetic polymorphisms, concomitant medication, comorbidities, etc.40), and immune‐mediated response generated by mAbs administration can also impact mAb clearance.”
  • Once in clinical development, clinical pharmacology studies can identify covariates and potential sources of intersubject variability, establish exposure-response relationships in patients, and aid in development of a dosing regimen.

    “Once in clinical development, clinical pharmacology studies can identify the covariates and potential sources of intersubject variability; establish exposure–response relationships in patients, and aid in development of a dosing regimen.40”

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Authors
Gill, K. L., Machavaram, K. K., Rose, R. H., & Chetty, M.
Affiliations
Simcyp (United Kingdom) (GB)
Corresponding author
Chetty, Manoranjenni
Venue
Clinical Pharmacokinetics
Published
2016-01-27
Volume
55
Issue
7
Pages
789-805
ISSN
  • 0312-5963 (ISSN-L)
  • 1179-1926
OpenAlex
W2296252503
Cited by
82
References
210
Citations by year
2026: 3 · 2025: 12 · 2024: 9 · 2023: 11 · 2022: 11 · 2021: 7 · 2020: 5 · 2019: 6 · 2018: 10 · 2017: 7 · 2016: 1
FWCI
1.24
Type
journal article
Language
en
Open access
closed
Locations
  • Clinical Pharmacokinetics (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Monoclonal and Polyclonal Antibodies Research
  • Life Sciences › Immunology and Microbiology › Immunology › Biosimilars and Bioanalytical Methods
  • Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Pharmaceutical studies and practices
Keywords
monoclonal antibodies, interindividual variability, pharmacokinetics, covariates, genetic polymorphism, population pharmacokinetic model, physiologically based pharmacokinetic modeling, dosing regimen, disease status, immune status, concomitant medications, comorbidities
MeSH terms
Age Factors, Antibodies, Monoclonal, Body Weights and Measures, Dose-Response Relationship, Drug, Drug Interactions, Ethnicity, Humans, Lymphatic System, Models, Biological, Polymorphism, Genetic, Receptors, Fc, Severity of Illness Index, Sex Factors, Histocompatibility Antigens Class I, Comorbidity

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