Our team behind the scenes at SXSW | Patient Stratification in Target ID, OMICS data


BenevolentAI develops AI models to help scientists better define underlying mechanisms of disease in very specific patients groups.

Looking at patient clinical and biomedical data we try to dig into molecular-level detail to redefine the disease and better endotyping for two main purposes: target identification and designing better clinical trials.

There is an abundance of patient data created e.g. electronic health records or genome sequencing. With increasing amounts of data being generated, we need AI models to help make meaningful discoveries.

Precision medicine is the future of medicine. Our belief is that by better understanding the underlying mechanisms of diseases in patients and identifying more specific and precise endotypes, we will be able to provide better medicines that are efficient in the specific patients groups they are developed for.

Watch Poojitha Ojamies, a Solutions Architect at BenevolentAI discuss how our team uses AI and machine learning to improve patient endotyping in multi-omics for target identification.  



Up next

Next steps: From molecule design to medicine