The RIght Patient
Better defining endotypes to improve target identification and clinical trial design.
Traditionally diseases have been defined by symptoms or location in the body, not by their underlying molecular mechanisms, pathways or the biological processes specific to a patient. The result is that 30-50% of top selling drugs don’t work in the patients they are prescribed for.
At BenevolentAI we apply machine learning models to identify patient groups by the molecular signature of their disease and design, allowing us to run faster clinical trials.
This precision medicine guided approach allows us to identify patient subtypes more likely to respond to drugs, further increasing the probability of success in the clinic.
This approach has benefits for existing medicines too: it can be used to elucidate the mechanism of action, identify new patient responders, improve diagnosis and more precisely target treatment.
Disease Sprint for glioblastoma
The multi-disciplinary approach to patient stratification.
We believe by better understanding the underlying mechanisms of diseases in patients, and identifying more precise endotypes, we can provide better medicines that are more efficient in the patients groups they are created for.