Our Research Philosophy
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Nowadays, we are in an unprecedented situation in our fight against cancer. We have accumulated an enormous amount of information about them, while developing extremely modern experimental techniques that allows us generate in a record time a truly fingerprint of a patient.
However this advance came to a high price: modern clinicians are not able to use anymore their pure medical intuition to interpret the avalanche of information and data that science can provide to them, and therefore decision making and treatment design is becoming extremely difficult and expensive. It is like if they would be in the very middle of a Chinese ten million inhabitants city trying to find the address of a given restaurant by just asking people and using a 10x10 cm map. |
The map of the Shanghai Public transport
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Section of the map of regulatory pathways governing cancer progression as complex as the public transport system of any metropolis, like Shanghai
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Systems biology is for clinicians fighting multifactorial diseases like cancer what the GPS is for this tourist in Shanghai. It is a tool to help them finding the quickest and shortest path. It is a tool that uses sophisticated and challenging biological theories, mathematics and computational methods to collect, process and analyze the unimaginable amount of biomedical knowledge currently available, and integrate it with the genetic fingerprint of a patient into mathematical models of the disease.
Our vision for the future is that computational expert systems, based on the use of data-driven mathematical models will help clinicians to make in the shortest time the right decision about the precise (personalize) treatment a patient urgently needs.
Our vision for the future is that computational expert systems, based on the use of data-driven mathematical models will help clinicians to make in the shortest time the right decision about the precise (personalize) treatment a patient urgently needs.
Figure. The Systems Medicine approach to develop faster more personalized treatments. Computational methods are used to collect, process and integrate biomedical knowledge and the genetic fingerprint of a patient. This information is to be used by an expert system, based on the use of mathematical modeling, that will help clinicians making a more efficient decision on the treatment a patient needs. The approach is a multidisciplinary endeavor that integrates biomedical researcher, computational scientist and clinicians.
