Assessment of Drug Effects in Xenograft Models Using Constrained Parametric Maximum Likelihood Estimations

• Activity Number: 57
• Type: Topic Contributed
• Date/Time: Sunday, August 1, 2010 : 4:00 PM to 5:50 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Hong-Bin Fang*+
• Companies: University of Maryland Greenebaum Cancer Center
• Keywords: tumor xenograft models ; longitudinal data ; restricted parameter estimation ; ECM algorithm ; missingness ; MLE

Abstract

Tumor xenograft experiments demonstrated a good correlation in efficacy with clinical outcomes. In xenograft experiments, incomplete repeated measurements arise because mice may be sacrificed or die when its tumor volume reaches a threshold and a tumor may become undetectable for some time. Because of the small sample sizes, asymptotic inferences are usually questionably. In addition, the tumor-bearing mice were not treated, the tumors would keep growing until the mice die or are sacrificed. This intrinsic growth of tumor in the absence of treatment constrains the parameters in statistical models. In this paper, we review the recent advance in statistical inference accounting for these statistical challenges. Furthermore, we develop a multivariate random effects model with constrained parameters for multiple tumors in xenograft experiments.