Abstract 366: Translational modeling of docetaxel-thalidomide combination treatment in metastatic, castrate-resistant prostate cancer: predicting clinical response using preclinical data

Abstract

Abstract A major cause of drug failure in the clinic is that preclinical studies do not predict with sufficient certainty what will happen in clinical practice. Accurately translating information from animal studies to the clinic would have a major impact on attrition rate. We have developed a mathematical model of a tumor cell population called the Virtual Tumour, which has been used extensively to predict the efficacy of single drug or drug combination treatment in preclinical studies. We have now extended and adapted our preclinical model to predict efficacy in the clinic, thus creating the “Virtual Tumour Clinical.” Here we show a comparative study of the preclinical Virtual Tumour calibrated model for prostate tumor xenografts in mice, with a Virtual Tumour Clinical version calibrated with a clinical data set comprising 53 prostate cancer patients treated with thalidomide, 25 treated with docetaxel and 50 treated with a docetaxel and thalidomide combination. PSA measurements were used as proxy for tumor size. We analysed the consistency, the capability and the limitations of the models in translating the effect of the drug combination from the preclinical situation to the clinic. Citation Format: Eric Fernandez, Hitesh Mistry, Frances Brightman, David Orrell, William L. Dahut, William D. Figg, Wilfried D. Stein, Christophe Chassagnole. Translational modeling of docetaxel-thalidomide combination treatment in metastatic, castrate-resistant prostate cancer: predicting clinical response using preclinical data. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 366. doi:10.1158/1538-7445.AM2014-366