Abstract 740: Oncodesign translational drug discovery process

Despite major advances in translational methods, oncology drug discovery remains a largely sequential process, in most cases starting from a molecular target with some initial but often limited relevance to the disease. It takes multiple years and investments in the order of 5-10 million US$ before a compound is validated in advanced efficacy and safety models. In addition, due to the remoteness of many of the models to real disease pathophysiology, attrition rates in clinical phases remain very high. We have developed and validated a flexible and iterative “Translational Drug Discovery Process”, in which multiple translational research platforms create a tight link between molecule development and cancer pathophysiology. Our “Translational Drug Discovery process” is based on multiple research platforms that are used as flexible building blocks to design an optimal process to advance compounds and position them towards precise oncology applications. These platforms include cellular models, in vivo tumourgrafts, phenotypic models and a multi-modality imaging platform. Recent additions that are based on fresh patient-derived tumour tissue include ex vivo 3D models and low passage tumourgrafts. We have also initiated a program to discover 18F-labeled kinase inhibitor based biomarkers/imaging tracers for use in PET applications. Our research base was recently completed with the addition of a diverse collection of potent and selective kinase inhibitors and the associated proprietary chemical technology. We will describe how we have validated the ex vivo 3D model, based on tumour tissue collected directly in patients or from low passage tumourgrafts in mice. After mincing in small fragments and culturing in poly-HEMA coated plates, the tumour fragments are treated with drug for 24h. Tissue-microarrays are created by fixing and embedding the fragments in paraffin. Different classes of reference compounds were analysed by immunohistochemistry of Ki67 (proliferation) and M30 (apoptosis) using automated quantification. Following this validation, the model is used to select promising new compounds from our internal collection for further optimization or to position advanced compounds from our clients. We will finally demonstrate how our “Translational Drug Discovery process” has allowed the identification of attractive compounds of high disease relevance at a fraction of the typical drug discovery cost within reduced timelines. Citation Format: {Authors}. {Abstract t