e14612 Background: Most anticancer drug candidates, currently in clinical trials, have clear targets in molecular and cellular systems. However, such molecular targets are not always affected (or not correlated with efficacious endpoints) when the candidate is evaluated in a clinical setting. There is an urgent need to develop better biological tools and models to ease the transition between in vitro and in vivo, and between preclinical and clinical settings. Activation of tyrosine kinases in tumor cells has been recognized as key driving force in malignancy; therefore inhibitors of tyrosine kinases (TKI) have often shown efficacy in preclinical in vivo models and beneficial responses in clinical trials. An increasing number of TKI has been approved as anticancer drugs in selected cancer types. Methods: We have developed a unique platform combining our novel HuPrime™ xenograft models with our PD biomarker technologies. This platform is used to better understand the efficacy of novel drug candidates and generate information critical to maximize the chance of a successful clinical development. To illustrate the usefulness of our platform, we have applied it to understand the pharmacodynamic changes (at the molecular level) which are associated with the activity of sunitinib and sorafenib in our sensitive esophageal HuPrime models. Tumor tissues from sensitive esophageal HuPrime models treated with single dose of the respective drugs (and a vehicle control) have been collected at time-points 4, 8, 16, and 24 hour. Results: We have successfully applied immunohistochemistry (IHC) assays on many molecules covering most pathways including proliferation, apoptotic, necrotic, and cell cycle regulation, G2M phase arrest, DNA damage response, etc. Additional markers including angiogenesis can also be included for certain therapeutic compounds. These tissues have been analyzed with our platform and we have uncovered key molecular events which correlate with the efficacy and potency of the drugs. Conclusions: The PD biomarkers validated in this approach have potential for clinical application and patient stratification. [Table: see text]