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Population pharmacokinetic data analysis of three phase I studies of matuzumab, a humanised anti-EGFR monoclonal antibody in clinical cancer development.

Kuester K, Kovar A, Lüpfert C, Brockhaus B, Kloft C - Br. J. Cancer (2008)

Bottom Line: All parameters were estimated with good precision (RSE<39%).In addition, relevant and plausible covariates were identified and incorporated into the model.When correlated to efficacy, this model could serve as a tool to guide dose selection for this 'targeted' cancer therapy.

View Article: PubMed Central - PubMed

Affiliation: Department of Clinical Pharmacy, Institute of Pharmacy, Freie Universitaet Berlin, Berlin, Germany.

ABSTRACT
A population pharmacokinetic model based on data from three phase I studies was to be developed including a covariate analysis to describe the concentration-time profiles of matuzumab, a novel humanised monoclonal antibody. Matuzumab was administered as multiple 1 h i.v. infusions with 11 different dosing regimens ranging from 400 to 2000 mg, q1w-q3w. For analysis, 90 patients with 1256 serum concentration-time data were simultaneously fitted using the software NONMEM. Data were best described using a two-compartment model with the parameters central (V1) and peripheral distribution volume (V2), intercompartmental (Q) and linear (CLL) clearance and an additional nonlinear elimination pathway (Km, Vmax). Structural parameters were in agreement with immunoglobulin characteristics. In total, interindividual variability on Vmax, CLL, V1 and V2 and interoccasion variability on CLL was 22-62% CV. A covariate analysis identified weight having an influence on V1 (+0.44% per kg) and CLL (+0.87% per kg). All parameters were estimated with good precision (RSE<39%). A robust population pharmacokinetic model for matuzumab was developed, including a nonlinear pharmacokinetic process. In addition, relevant and plausible covariates were identified and incorporated into the model. When correlated to efficacy, this model could serve as a tool to guide dose selection for this 'targeted' cancer therapy.

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Goodness-of-fit plots. Population predictions (upper panel) and individual predictions (lower panel) vs observed matuzumab serum concentrations are shown using linear (left) and logarithmic (right) scale of both axes.
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fig4: Goodness-of-fit plots. Population predictions (upper panel) and individual predictions (lower panel) vs observed matuzumab serum concentrations are shown using linear (left) and logarithmic (right) scale of both axes.

Mentions: In Figure 4, the goodness-of-fit plots obtained from the final population PK model in linear (left) and logarithmic (right) scale are shown. The upper panel presents the population predictions vs the observed concentrations. Especially the data points in the low region were uniformly spread around the line of unity with a slight underprediction in the higher region. Examining the lower panel with individual predicted vs observed concentrations, those in the higher region were more uniformly scattered, and the lower concentrations were closer to the line of unity. Overall, the plots indicate that the study data were sufficiently well described by the developed model.


Population pharmacokinetic data analysis of three phase I studies of matuzumab, a humanised anti-EGFR monoclonal antibody in clinical cancer development.

Kuester K, Kovar A, Lüpfert C, Brockhaus B, Kloft C - Br. J. Cancer (2008)

Goodness-of-fit plots. Population predictions (upper panel) and individual predictions (lower panel) vs observed matuzumab serum concentrations are shown using linear (left) and logarithmic (right) scale of both axes.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2266843&req=5

fig4: Goodness-of-fit plots. Population predictions (upper panel) and individual predictions (lower panel) vs observed matuzumab serum concentrations are shown using linear (left) and logarithmic (right) scale of both axes.
Mentions: In Figure 4, the goodness-of-fit plots obtained from the final population PK model in linear (left) and logarithmic (right) scale are shown. The upper panel presents the population predictions vs the observed concentrations. Especially the data points in the low region were uniformly spread around the line of unity with a slight underprediction in the higher region. Examining the lower panel with individual predicted vs observed concentrations, those in the higher region were more uniformly scattered, and the lower concentrations were closer to the line of unity. Overall, the plots indicate that the study data were sufficiently well described by the developed model.

Bottom Line: All parameters were estimated with good precision (RSE<39%).In addition, relevant and plausible covariates were identified and incorporated into the model.When correlated to efficacy, this model could serve as a tool to guide dose selection for this 'targeted' cancer therapy.

View Article: PubMed Central - PubMed

Affiliation: Department of Clinical Pharmacy, Institute of Pharmacy, Freie Universitaet Berlin, Berlin, Germany.

ABSTRACT
A population pharmacokinetic model based on data from three phase I studies was to be developed including a covariate analysis to describe the concentration-time profiles of matuzumab, a novel humanised monoclonal antibody. Matuzumab was administered as multiple 1 h i.v. infusions with 11 different dosing regimens ranging from 400 to 2000 mg, q1w-q3w. For analysis, 90 patients with 1256 serum concentration-time data were simultaneously fitted using the software NONMEM. Data were best described using a two-compartment model with the parameters central (V1) and peripheral distribution volume (V2), intercompartmental (Q) and linear (CLL) clearance and an additional nonlinear elimination pathway (Km, Vmax). Structural parameters were in agreement with immunoglobulin characteristics. In total, interindividual variability on Vmax, CLL, V1 and V2 and interoccasion variability on CLL was 22-62% CV. A covariate analysis identified weight having an influence on V1 (+0.44% per kg) and CLL (+0.87% per kg). All parameters were estimated with good precision (RSE<39%). A robust population pharmacokinetic model for matuzumab was developed, including a nonlinear pharmacokinetic process. In addition, relevant and plausible covariates were identified and incorporated into the model. When correlated to efficacy, this model could serve as a tool to guide dose selection for this 'targeted' cancer therapy.

Show MeSH