At MNM our goal has always been to understand cancer and be in a position to find the right therapy for every patient. We set out on this journey analyzing somatic variants of patient tumors to guide their therapy. Soon, however, we realized that we were neglecting much information that is contained in the so-called dark/junk genome, to better understand cancer origins we needed to better understand that dark genome. Hence we decided to start our BioBank which would help us build a database with tumors' WGS data.
With rich datasets at hand, we are now applying machine learning to drive novel insights. For example, we have developed and patented custom CDK4/6u, HRD. and PD1i patient stratification algorithms. The analysis of patient response to existing therapies in urn has inspired our- still broader-vision. We have realized that our genome analysis technology can reveal patterns of cancer mutations related to genes that are not yet targeted by any therapy. It is this realization that lies at the heart of our mission. In contrast to the classical drug discovery approach, our solution starts from real patient data, it then leverages AI and bioinformatics to understand mutation profiles and to find relevant drug target candidates, we are already creating our drug - MNM177!
The idea for MutationsNoMore (MNM) was born while we were at Oxford University, where we understood that a new “dictionary” for interpreting a tumor’s mutation language is needed. Over the past four years, we were building a technology that translates different mutation types into biological insights. Then, we have built a new AI framework for these data modalities – our most valuable asset.
We are proud that MNM’s predictive algorithms are used in clinics to help select the right treatment for cancer patients.