title: Refinement of the population pharmacokinetic model for the monoclonal antibody matuzumab: external model evaluation and simulations.
abstract: OBJECTIVE
  A developed population pharmacokinetic model of the humanized monoclonal antibody (mAb) matuzumab was evaluated by external evaluation. Based on the estimates of the final model, simulations of different dosing regimens and the covariate effect were performed.
  
  
  METHODS
  The development dataset included 90 patients, and the evaluation dataset included 81 patients; the two sets of patients were from three different studies. In all studies, the patients had different types of advanced carcinoma - mainly colon, rectal and pancreatic cancer. They received matuzumab as multiple 1-hour intravenous infusions in a wide range of dosing regimens (development dataset: from 400 mg every 3 weeks to 2000 mg in the first week followed by 1600 mg weekly; evaluation dataset: from 100 mg weekly to 800 mg weekly). In addition to 1256 serum mAb concentrations for model development, there were 1124 concentrations available for model evaluation. Serum concentration-time data were simultaneously fitted using NONMEM software. The developed two-compartment model - with the parameters central volume of distribution (V(1)) and peripheral volume of distribution (V(2)), intercompartmental clearance and linear clearance (CLL), an additional nonlinear elimination pathway (Michaelis-Menten constant: the concentration with the half-maximal elimination rate and V(max): the maximum elimination rate) and covariate relations - was evaluated by an external dataset. Different simulation scenarios were performed to demonstrate the impact of the incorporated covariate effect and the influence of different dosing regimens and dosing strategies on the concentration-time profiles.
  
  
  RESULTS
  The developed model included the covariate fat-free mass (FFM) on V(1) and on CLL. The evaluation did not support the covariate FFM on V(1) and, after deletion of this covariate, the model parameters of the refined model were estimated. The model showed good precision for all parameters: the relative standard errors (RSEs) were <42% for the development dataset and < or = 51% for the evaluation dataset (excluding the higher RSEs for the correlation between V(2) and V(max) and the interindividual variability on V(2) for the evaluation dataset). The model showed good robustness for the ability to estimate highly precise parameters for the combined dataset of 171 patients (RSE <29%). Simulations revealed that variability in concentration-time profiles for minimum and maximum steady-state concentrations was reduced to a marginal extent by a proposed dose adaptation.
  
  
  CONCLUSIONS
  The population pharmacokinetic model for matuzumab was improved by evaluation with an external dataset. The new model obtained precise parameter estimates and demonstrated robustness. After correlation with efficacy data simulation results in particular could serve as a tool to guide dose selection for this 'targeted' cancer therapy.
authors.affiliation: Department of Clinical Pharmacy, Institute of Pharmacy, Freie Universitaet Berlin, Berlin, Germany.
authors.forename: Katharina
authors.initials: K
authors.lastname: Kuester
authors.forename: Andreas
authors.initials: A
authors.lastname: Kovar
authors.forename: Christian
authors.initials: C
authors.lastname: Lüpfert
authors.forename: Brigitte
authors.initials: B
authors.lastname: Brockhaus
authors.forename: Charlotte
authors.initials: C
authors.lastname: Kloft
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000911:Antibodies, Monoclonal / Q000008:administration & dosage / Q000493:pharmacokinetics*; D061067:Antibodies, Monoclonal, Humanized; D000970:Antineoplastic Agents / Q000008:administration & dosage / Q000493:pharmacokinetics*; D002986:Clinical Trials as Topic; D003198:Computer Simulation; D003625:Data Collection; D004334:Drug Administration Schedule; D004359:Drug Therapy, Combination; D006801:Humans; D007262:Infusions, Intravenous; D008875:Middle Aged; D008954:Models, Biological; D009369:Neoplasms / Q000188:drug therapy
chemical_list: D000911:Antibodies, Monoclonal; D061067:Antibodies, Monoclonal, Humanized; D000970:Antineoplastic Agents; C520777:matuzumab
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