2012 - Venice - Italy

PAGE 2012: Other Drug/Disease Modelling
Enrica Mezzalana

A Target-Mediated Drug Disposition model to quantify the relationship between Anti-CD3 monoclonal antibody and CD3/TCR receptors in Patients with autoimmune diseases.

E. Mezzalana (1), A. MacDonald (2), R. Bizzotto (3), G. De Nicolao (1), S. Zamuner (2)

(1) Department of Computer Engineering and Systems Science, University of Pavia, Pavia, Italy; (2) Clinical Pharmacology Modelling and Simulation, GlaxoSmithKline, Stockley Park, UK; (3) Institute of Biomedical Engineering, National Research Council, Padova, Italy.

Objectives: Otelixizumab is a monoclonal antibody (mAb) directed against human CD3ε, which forms part of the CD3/T-cell receptor (TCR) complex on T lymphocytes. Attempts have been made to model the relationships between Otelixizumab, receptor binding and changes in lymphocytes count [1]. Based on the observed short half-life for Otelixizumab and other anti-CD3 mAbs relative to endogenous Immunoglobulin G it is hypothesised that the antibody is subject to target-mediated drug disposition (TMDD) at clinically relevant doses. TMDD is a phenomenon where a drug binds with high affinity to its pharmacological target, such that this interaction influences the pharmacokinetics of the drug. The aim of the present work was to develop a mechanistic target-mediated drug disposition (TMDD) model for Otelixizumab using published clinical data.

Methods: Published data from 3 clinical trials of Otelixizumab in type 1 diabetes mellitus and psoriasis patients were utilized. Free drug in serum (C) and free (FR), bound (DR) and total (TR) receptors on both CD4+ and CD8+ lymphocytes were measured using immunoassay and flow cytometry, respectively. A general TMDD model [2] and its Quasi Equilibrium (QE) approximation [3] were implemented. The QE TMDD model was also extended as in [4] to account for the two different lymphocytes populations, under the assumption of equal affinity between drug and receptors on CD4+ and CD8+. Berkeley-Madonna, R and NONMEM VII were used to develop the model. Model performances were evaluated through changes in Objective Function, GoF plots and VPCs.

Results: First, attempts were made to fit the general TMDD model to the available data. The sum of measured quantities on CD4+ and CD8+ was used for each of FR, DR and TR. However, the general model was unstable and the QE approximation model was then used. An additional source of model instability was then identified when attempting to estimate the conversion factors between FR, DR and TR and their actually measured quantities (in MESF units) [5]. Sensitivity analyses and simulations were conducted using the QE TMDD model to better characterise the model behaviour.

Conclusions: A general TMDD model and its QE approximation were proposed in the attempt to describe Otelixizumab binding to CD3/TCR on T lymphocytes. A critical factor for model identifiability was found in the relative measurements for free, bound and total receptors. Further strategies for improving model robustness while maintaining the key characteristics of TMDD are discussed.

[1] Wiczling P, Rosenzweig M, Vaickus L, Jusko WJ. Pharmacokinetics and Pharmacodynamics of a Chimeric/Humanized Anti-CD3 Monoclonal Antibody, Otelixizumab (TRX4), in Subjects With Psoriasis and With Type 1 Diabetes Mellitus. J  Clinical Pharmacol 2010;50(5):494-506.
[2] Mager DE, Jusko WJ. General pharmacokinetic model for drugs exhibiting target-mediated drug disposition. J Pharmacokinet Pharmacodyn 2001;28(6):507-32.
[3] Mager DE, Krzyzanski W. Quasi-equilibrium pharmacokinetic model for drugs exhibiting target-mediated drug disposition. Pharmaceutical Research 2005;2(10):1589-1596.
[4] Gibiansky L, Gibiansky E, Target-Mediated Drug Disposition Model for Drugs That Bind to More than One Target. J Pharmacokinet Pharmacodyn 2010;37:323-346.
[5] Gratama JW, D'Hautcourt JL, Mandy F, et al; European Working Group on Clinical Cell Analysis. Flow cytometric quantitation of immunofluorescence intensity: problems and perspectives. Cytometry 1998;33:166-178.

Reference: PAGE 21 (2012) Abstr 2463 [www.page-meeting.org/?abstract=2463]
Poster: Other Drug/Disease Modelling
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