Angiogenesis, the development of new blood vessels from pre-existing vasculator, plays a crucial role in the growth of malignant tumors and the development of metastases. It is particularly mediated by vascular endothelial growth factor (VEGF), a therapeutic target of new anti-angiogenic drugs such as aflibercept (Zaltrap , developed by Regeneron and Sanofi). It is a recombinant fusion protein consisting of human VEGF receptor extracellular domains (VEGFR1 and VEGFR2) fused to the Fc portion of human IgG1. It binds to VEGF-A, VEGF-B as well as to placental growth factor (PlGF). Because of this binding, the pharmacokinetic (PK)/pharmacodynamic (PD) properties of this new drug become more complex. In this thesis, we have studied the mechanism of action of aflibercept by building population PK/PD models. We firstly developed the joint PK model of free and bound aflibercept in healthy subjects thanks to rich data. We then applied this model to data in cancer patients and also assessed the influence of physiopathologic factors on their PK. This model allowed to simulate different dosing regimens and to support the choice of therapeutic dose. To better evaluate the efficacy of aflibercept, we also build a PD model for tumor growth inhibition under the effect of aflibercept and FOLFIRI (5-fluorouracil, leucovorin and irinotecan) in patients with metastatic colorectal cancer. The uncertainty in parameter estimates in complex models may be biased or sometimes cannot be obtained. We therefore investigated by simulation the uncertainty obtained by different bootstrap methods allowing resampling two levels of variability (between subject and residual) in nonlinear mixed-effects models (NLMEM). We have shown that the bootstraps only provide better estimates of uncertainty in NLMEM with high nonlinearity compared to the asymptotic method. The case bootstrap performs as well as the nonparametric bootstrap of both random effects and residuals. However, they may face practical problems, e.g skewed distributions in parameter estimates and unbalanced designs where stratification may be insufficient.
