In our 5 part series filmed at SXSW, our team showcased how AI can be used to better understand the underlying causes of disease, and redefine the way new medicines are brought to patients.

In part two of our SXSW series, our team show how we use AI and machine learning to better understand specific diseases - in this case, Glioblastoma (GBM), the most common and aggressive form of brain cancer.

Watch our team investigate the target identification process for GBM using machine learning methods. Their aim was to identify genes or proteins involved in the development of glioblastoma stem cells - a type of cell at the origin of GBM that are resistant to the current treatments.

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 the molecular level detail to redefine the disease and better endotyping for two main purposes

Following target identification and endotyping, we have the ability to design molecule compounds and progress these into clinical trials. Our team walks through our approach in this video to conclude the series extracted from our SXSW keynote session.