SpheroPredict
A 3D advanced test for prediction of drug response in secondary liver cancer
Total Cost €
0EC-Contrib. €
0Partnership
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0SpheroPredict project word cloud
Explore the words cloud of the SpheroPredict project. It provides you a very rough idea of what is the project "SpheroPredict" about.
Project "SpheroPredict" data sheet
The following table provides information about the project.
| Coordinator |
SPHEROTEC GMBH
Organization address contact info |
| Coordinator Country | Germany [DE] |
| Project website | http://www.spherotec.com/ - www.spheromed.com - www.spheroselect.com |
| Total cost | 71˙429 € |
| EC max contribution | 50˙000 € (70%) |
| Programme |
1. H2020-EU.3.1.3. (Treating and managing disease) |
| Code Call | H2020-SMEINST-1-2016-2017 |
| Funding Scheme | SME-1 |
| Starting year | 2017 |
| Duration (year-month-day) | from 2017-01-01 to 2017-04-30 |
Partnership
Take a look of project's partnership.
| # | ||||
|---|---|---|---|---|
| 1 | SPHEROTEC GMBH | DE (MARTINSRIED) | coordinator | 50˙000.00 |
Map
Project objective
Cancer remains one of the deathliest diseases of the 21st century, with more than 1.9 M deaths per year in Europe. Some tumours entail a high risk of metastasizing, meaning that they are able to reach other locations in the body. Migrating cells from a primary tumour often cause secondary cancer in the liver, which is one of the leading causes of death worldwide.Regarding treatment options, international institutions have published clear guidelines about first line treatments to treat particular types of primary cancers. However, when dealing with secondary cancers (like metastatic liver cancer) there is a heterogeneous and very wide range of treatment options and no clear guidelines. The choice of treatment in secondary cancer is based in “trial and error”. This “trial and error” approach causes many patients fail to respond to therapy due to chemoresistance (lack of response to chemotherapy). In response, we at SpheroTec have created SpheroPredict, an individualised drug testing platform designed to predict the patient’s response to guideline therapies before installing the treatment cycle. Using cancer cells from the patient’s tumour, we build an accurate and biologically relevant 3D micro-tumour (spheroid) model to test the drugs and analyse the response in advance. In the end, only drugs with proven efficacy and low toxicity will be applied in the patient’s therapy cycle. In the era of personalised medicine and with the urgent need for de-risked and efficient drug treatments, we have developed an innovative solution that will greatly improve the patient’s survival time, quality of life and will help to alleviate the economic burden on the EU healthcare system incurred by inefficient therapies and productivity loss. Thus, in Phase 1, we aim to warrant the feasibility of the SpheroPredict project from the technical, commercial and financial perspectives, in order to ensure its success upon commercialisation.
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