A Semiparametric Response Surface Model for Assessing Drug Interaction as Synergy, Additivity, or Antagonism

• Activity Number: 361
• Type: Contributed
• Date/Time: Wednesday, August 10, 2005 : 8:30 AM to 10:20 AM
• Sponsor: Biopharmaceutical Section
• Author(s): Maiying Kong*+ and J. Jack Lee
• Companies: The University of Texas M. D. Anderson Cancer Center and The University of Texas M. D. Anderson Cancer Center
• Keywords: bivariate splines ; drug interactions ; synergy ; antagonism

Abstract

In this paper, we focus on assessing drug interaction of two agents under the commonly accepted framework of the Loewe additivity model. The response surface method (RSM) represents a natural and effective means to assess drug interaction utilizing all information contained in the entire dose-effect dataset. Several response surface models (Machado and Robinson 1994, Greco et al. 1990, Carter et al. 1988, Plummer and Short 1990) were proposed using a single parameter to capture the mode of drug interaction as synergism, additivity, or antagonism. Limitation of these models exists when combinations at certain doses are synergistic while additive or antagonistic at other doses. We propose a semiparametric RSM by assuming the dose-effect curve for each single drug follows a parametric model, and instead of a single parameter, a nonparametric function of combination doses is used to identify and quantify departures from additivity. The proposed model could capture different modes of drug interaction at different combinations of two drugs. Examples and simulations will be given to illustrate the advantages of the proposed method.