Early cancer detection is crucial for ultimate control and prevention.
Moreover, accuracy in patient staging and in the selection of personalised treatment plan can be of critical importance for patient’s health or even survival.
However, patient personalized treatments are not possible nowadays, because there still is no solution to easily correlate the patient clinical situation with the patient DNA Single Nucleotide Polymorphisms (SNPs) / mutations and so with his/her real condition.
Actually, the therapies are selected by using a performance driver which is based on general statistics and not tied to the very specific patient case.
In this framework, MATCH is now developed and is expected to provide some kind of help in identifying these correlations in order to provide the oncologist with a better understanding of the personalized conditions of every single patient.
MATCH is a web based multi functional platform that integrates medicine and molecular biology to provide more effective treatment and enhance pharmaceutical research and drug discovery. In MATCH, clinical and biological data are integrated in order to discover correlations between SNPs and colon cancer to allow for patient diagnosis, staging and treatment selection.
The MATCH project aims to provide health professionals with a multi-functional platform for colon cancer prevention and pharmaceutical research, aiming at new drug design and discovery. It will contribute directly to the health care sector by grouping previously unrelated data and reducing cost of expensive trials in the area of biochemical and pharmaceutical research.
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