CPO R&D IS SUPPORTED BY COLLABORATIONS AND ALLIANCES WITH LEADING INDUSTRY AND ACADEMIA.
CBmed is an Austrian funded competence center that links excellent research infrastructure, scientific expertise, medical knowledge, national and international industry partners for systematic medical biomarker research.
CBmed brings together scientific experts with leading pharmaceutical, diagnostic, medical-technology and IT industry partners. In addition, CBmed has a strong network in the area of Biobanking including the largest Biobank in Europe, Biobank Graz, and the European Biobanking network BBMRI-ERIC. CBmed research projects will identify new biomarkers, validate potential biomarkers and conduct translational biomarker research for products to be used in clinical practice.CBmed will develop easily applicable, targeted, minimally invasive biomarkers for better diagnosis, better therapy monitoring and a more personalized treatment of patients.
EFRE - POP
Precision Oncology and Personalized Therapy Prediction
This grant from the European Fund for Regional development (EFRE) enables Charité to launch a cooperation project with three regional biotech companies. The project is called Precision Oncology and Personalized Therapy Prediction, or POP for short. Its goal is to further develop test systems for medication screening, which reflect the varied tumor characteristics of individual patients.Patient-specific cell cultures and mouse models enabling scientists to assess and evaluate the effectiveness of a drug in advance are considered the new hope in personalized drug therapy.
New Combined Humanized Assay Platform based on Patient-Derived Tumour Models and 3D cultures
The goal of this project is the integration of two novel technologies to create a new groundbreaking assay system for immuno-oncological drug development. In the project, corresponding 3D organotypic cell cultures in parallel with new primary xenografts (PDX), both derived from patient tumours, will be developed and validated by focusing eminently on humanized tumour microenvironment. Created assay system will meet the high future demand of predictive models in immuno therapies development.
Preclinical oncology research in pharma and biotec industry heavily depends on the routine use of tumour cell cultures and animal models. However, the predictive value of traditional cell culture and xenograft models is limited by the dependence on artificial cell lines; often cultured for decades ex vivo, and fully adapted to artificial two-dimensional (2D) culture conditions.
Two new technologies, the 3D organotypic cell cultures and new primary xenografts (PDX), both derived from patient tumours, have recently provided a much more realistic and disease-relevant alternative. Based on the exceptional experience of the members of this consortium (EPO and Pharmatest) with 3D cell cultures and xenografts, the goal of this project is the integration and further improvement of both technologies to a new unique assay system for drug development. Corresponding patient derived, humanized 3D cell cultures and xenografts can be directly used for step wise drug discovery, starting with new high content screening assays in a miniaturized in vitro platform based on microscopic imaging and automated image analyses. Pre-formed, complex 3D co-cultures can also be directly utilized as starting materials for humanized xenografts. Aim is to focus on the humanization of currently available models, with the goal to avoid replacement of human stromal cells with mouse stroma, and to ascertain the presence of relevant human immune cells in the PDX models, therefore recapitulating critical tumour-immune interactions that are fundamental for understanding drug/target interactions, drug sensitivity versus non-responders, and the development of resistance.
Serum metabolomics and patient-derived knockout models for accurate diagnostic biomarker discovery in pancreatic cancer
The development of more effective treatments for cancer is one of the most important issues of the future albeit recent predictions confirm an overall favourable cancer mortality trend in the EU. Due to population ageing, total numbers of cancer deaths are predicted to rise. Strikingly, pancreatic cancer is the only major cancer showing unfavourable trends in both sexes. Its dismal survival rates are mainly due to 1) late diagnosis usually at advanced stages; 2) no available curative treatment except early stage surgery; 3) largely unknown aetiology. In view of the unmet medical need and promising market conditions, this topic is highly relevant to industrial R&D. The development of effective treatment and predictive, disease-specific diagnosis suffers from the lack of valid targets and biomarkers. We hypothesize: 1) serum metabolite alterations caused by reprogramming of cancer cells can be quantified and translated into a diagnostic assay for pancreatic cancer; 2) the predictive power of patient-derived 3D organoids and xenograft models combined with genome editing for target validation is highly superior to classical 2D cultures and immortalised cell lines. Using serum samples from well-defined patient cohorts we will develop a metabolomics assay kit for diagnosis of pancreatic cancer. We will apply CRISPR-based target gene knockout in 3D organoid and xenograft models of primary pancreatic cancer. These models will form the basis for a more efficient preclinical target validation and drug development platform. Samples taken during drug sensitivity testing of these models will be used to confirm the predicitve value of our metabolomics assay kit. Economically, during and certainly after the project, its outcome will be highly relevant for the three consortium members, a CRO (1), a metabolomics company (2) and a research institute focussing on target validation technologies (3). Subsequently a significant economic effect on the whole industrial sector is expected.
SARCOMAS ARE RARE TUMORS WITH ONLY LIMITED MOLECULAR DATA AND MODELS CURRENTLY AVAILABLE
In this project we seek to change that. Together with our clinical partner, we will establish at least 10 models per sarcoma subtype to study their biology and correlate molecular data with drug-response data. t.b.c.