A model-based approach for assessing in vivo combination therapy interactions

We present an approach for evaluating the efficacy of combination antitumor agent schedules that accounts for order and timing of drug administration. Our model-based approach compares in vivo tumor volume data over a time co urse and offers a quantitative definition for additivity of drug effects, r elative to which synergism and antagonism are interpreted. We begin by fitt ing data from individual mice receiving at most one drug to a differential equation tumor growth/drug effect model and combine individual parameter es timates to obtain population statistics. Using two null hypotheses: (i) com bination therapy is consistent with additivity or (ii) combination therapy is equivalent to treating with the more effective single agent alone, we co mpute predicted tumor growth trajectories and their distribution for combin ation treated animals. We illustrate this approach by comparing entire obse rved and expected tumor volume trajectories for a data set in which 2/neu-o verexpressing MCF-7 human breast cancer xenografts are treated with a human ized, anti-HER-2 monoclonal antibody (rhuMAb HER-2), doxorubicin, or one of five proposed combination therapy schedules.