Research

In Europe, over 40 000 women die of ovarian cancer every year. In addition to surgery, most patients are treated with platinum-based chemotherapy. Unfortunately, the effect of the chemotherapy often decreases during the treatment cycles, and currently there are few effective treatments to those patients who develop resistance to platinum-based drugs. The survival of these patients has not improved much in the past decades and new solutions are in urgent need.

In the DECIDER project, a patient’s response to treatments was predicted using methods, which use, among others, histopathological and genomic data from the patient. Genomic changes and aberrations in gene functions were used to find effective, personalized treatments. This was done by developing an open source program, which integrates and visualizes all relevant data from a patient. Using this information, doctors can more easily identify effective drugs for their patient. All patients participating in the research were treated in Finland, and Finnish patient organizations had an important advisory role in the project.

The companies involved in the project were developing diagnostic kits (AB ANALITICA), a drug-sensitivity test based on the tumour tissue samples (2cureX), image based diagnostics of digital samples (Aiforia), and data pseudonymisation and anonymisation techniques necessary for the management of sensitive patient data for privacy risk protection (Veil.AI).

We also studied the legal issues that impede or slow down the use of new treatments in order to facilitate commercialization and availability of personalized therapies in an ethically and legally sustainable manner.

The DECIDER leaflet that summarizes the goals of the project can be downloaded as pdf file from here.

The current version of the Data Management Plan of the project is available here: DECIDER_DMP_v4.0.