Population Pharmacokinetic Analysis of Alirocumab in Healthy Volunteers or Hypercholesterolemic Subjects Using a Michaelis–Menten Approximation of a Target-Mediated Drug Disposition ... View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-01

AUTHORS

Jean-Marie Martinez, Aurélie Brunet, Fabrice Hurbin, A. Thomas DiCioccio, Clémence Rauch, David Fabre

ABSTRACT

BACKGROUND: Alirocumab, a human monoclonal antibody, inhibits proprotein convertase subtilisin/kexin type 9 (PCSK9) to significantly reduce low-density lipoprotein cholesterol levels; pharmacokinetics (PK) are governed by non-linear, target-mediated drug disposition (TMDD). OBJECTIVES: We aimed to develop and qualify a population PK (PopPK) model to characterize the PK profile of alirocumab, evaluate the impact of covariates on alirocumab PK and on individual patient exposures, and estimate individual predicted concentrations for a subsequent PK/pharmacodynamic (PD) analysis. METHODS: Data from 13 phase I-III trials of 2799 healthy volunteers or patients with hypercholesterolemia treated with intravenous or subcutaneous alirocumab (13,717 alirocumab concentrations) were included; a Michaelis-Menten approximation of the TMDD model was used to estimate PK parameters and exposures. The final model comprised two compartments with first-order absorption. Elimination from the central compartment was described by linear (CLL) and non-linear Michaelis-Menten clearance (Vm and Km). The model was validated using visual predictive check and bootstrap methods. Patient exposures to alirocumab were computed using individual PK parameters. RESULTS: The PopPK model was well-qualified, with the majority of observed alirocumab concentrations in the 2.5th-97.5th predicted percentiles. Covariates responsible for interindividual variability were identified. Body weight and concomitant statin administration impacted CLL, whereas time-varying free PCSK9 concentrations and age affected Km and peripheral distribution volume (V3), respectively. No covariates were clinically meaningful, therefore no dose adjustments were needed. CONCLUSIONS: The model explained the between-subject variability, quantified the impact of covariates, and, finally, predicted alirocumab concentrations (subsequently used in a PopPK/PD model, see Part II) and individual exposures. More... »

PAGES

101-113

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s40262-018-0669-y

DOI

http://dx.doi.org/10.1007/s40262-018-0669-y

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1103766257

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/29725996


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37 schema:description BACKGROUND: Alirocumab, a human monoclonal antibody, inhibits proprotein convertase subtilisin/kexin type 9 (PCSK9) to significantly reduce low-density lipoprotein cholesterol levels; pharmacokinetics (PK) are governed by non-linear, target-mediated drug disposition (TMDD). OBJECTIVES: We aimed to develop and qualify a population PK (PopPK) model to characterize the PK profile of alirocumab, evaluate the impact of covariates on alirocumab PK and on individual patient exposures, and estimate individual predicted concentrations for a subsequent PK/pharmacodynamic (PD) analysis. METHODS: Data from 13 phase I-III trials of 2799 healthy volunteers or patients with hypercholesterolemia treated with intravenous or subcutaneous alirocumab (13,717 alirocumab concentrations) were included; a Michaelis-Menten approximation of the TMDD model was used to estimate PK parameters and exposures. The final model comprised two compartments with first-order absorption. Elimination from the central compartment was described by linear (CLL) and non-linear Michaelis-Menten clearance (Vm and Km). The model was validated using visual predictive check and bootstrap methods. Patient exposures to alirocumab were computed using individual PK parameters. RESULTS: The PopPK model was well-qualified, with the majority of observed alirocumab concentrations in the 2.5th-97.5th predicted percentiles. Covariates responsible for interindividual variability were identified. Body weight and concomitant statin administration impacted CLL, whereas time-varying free PCSK9 concentrations and age affected Km and peripheral distribution volume (V3), respectively. No covariates were clinically meaningful, therefore no dose adjustments were needed. CONCLUSIONS: The model explained the between-subject variability, quantified the impact of covariates, and, finally, predicted alirocumab concentrations (subsequently used in a PopPK/PD model, see Part II) and individual exposures.
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