Our team behind the scenes at SXSW | Opening by Joanna Shields, BenevolentAI CEO


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 this first video our CEO, Joanna Shields, introduces the Benevolent team and our vision.And this is what brought our Benevolent Team to Texas - to share our collective vision of using the power of technology to solve something that truly matters to the world. For us this means tackling the most challenging and devastating diseases that currently have no cure, and we believe our efforts can and will change outcomes for patients.

There are an estimated 9,000 untreated diseases and 300 million people in the world suffering from rare diseases. Developing a drug and getting it to market take 10-15 years and costs more than $2.5 billion, and still the top ten selling drugs in the market today only work for 30-50% of patients.

Biology is complicated. The underlying molecular mechanisms, pathways and biological processes specific to a patient needs to be fully understood to effectively diagnose a disease and develop a medicine to treat it. Humans, are limited by the amount of information they can absorb and process.

Against a backdrop of >10,000 new scientific papers published daily, and the millions of patents, chemical databases, clinical trials and countless other data sources, it’s almost impossible for scientists to leverage all the existing information to make new discoveries. While this deluge of data represents a limitation of human comprehension, it lends itself perfectly to machine learning.

AI can help us uncover relationships between diseases and symptoms, drugs and their effect, the patients that will best respond to treatment and much more. At Benevolent, we believe that unconventional thinking combined with purposeful technology can truly make an impact on humanity.

Watch our team share this example of how we work to do exactly that.


Up next

Building a Disease Specific Knowledge Base