ACCELERATING PRECLINICAL UNDERSTANDING & SUCCESS IN THE CLINIC
CANCER IS NOT A SINGLE DISEASE
There is no single treatment that is effective for all patients even within a single cancer type or subtype. The future of cancer treatments lies in the development of tailored strategies for the individual cancer patient (precision medicine).
The goal for cpo is to help our customers design the best strategy for their drug candidates. By working with cpo and using our unique PD3D models and powerful phenomics data analysis capabilities, our customers significantly improve the opportunity for success during clinical development. We support you with:
- clinical compound selection
- clinical compound indication
- biomarker strategies
- patient stratification
cpo has developed an unique collection of PD3D cancer models and assays. Our customers can use and combine these to select target candidates and improve preparation for clinical development by identifying biomarkers for patient responders by exploring the curated knowledge of our extensive model collection to identify genetic signatures.
In the last decade the development of new molecular therapeutics, drugs that target specific molecules involved in cancer growth and spreading, has highlighted the fundamental role of individual differences in drug response. The National Academy of Science has defined ‘precision medicine’ as ‘the use of genomic, epigenomic, exposure and other data to define individual patterns of disease, potentially leading to better individual treatment’ (ref).
At clinical level, experimental tools able to stratify patients for the most appropriate treatment are strongly needed, to both increase the therapeutic success as well as to limit the side-effects of the treatment.
In this scenario, 3D patients-derived organotypic cultures represent a very promising tools since they efficiently mimic the tumor behaviour in vivo preserving the original tissue characteristics such as morphology, cell polarity and marker expression. Moreover, compared to animal models, they allow for screening of a greater number of single as well as combination drugs in a limited time.
Additionally, 3D cancer spheroids show a resistance response similar to the one observed in patient tumors. This peculiar characteristic allows the application of this model to both study the mechanisms of drug resistance as well as to determine second line therapies after recurrence.