Finding new ways to treat disease

Human intelligence and technology united to re-engineer drug discovery and deliver life-changing medicines.

our approach

The Benevolent Platform®

Built on powerful data foundations and state of the art technology, the Benevolent Platform® empowers scientists to decipher the vast and complex code underlying human biology and find new ways to treat disease. Our knowledge graph is therapeutic area agnostic and our data fabric enables powerful synergies across the entire drug discovery and development process.

Augmenting Knowledge & Reasoning

Our knowledge pipeline pulls data from various structured and unstructured biomedical data sources and curates and standardises this knowledge via a data fabric.
This is fed into our proprietary knowledge graph which extracts and contextualises the relevant information and is made up of a vast number of machine curated relationships between diseases, genes, drugs.

Generating drug-like molecules in fewer cycles

The chemical space for exploration is infinitely vast and only a small fraction of it can potentially be made into medicines. Our AI-augmented models empower chemists to evaluate millions of molecular structures, generate drug-like molecules and design better drugs in fewer cycles.

PARTNERships

Collaborate with us

We recognise that no one business can revolutionise the way medicines are discovered and developed on their own. We want to leverage our technology and expertise in partnership with the world’s leading researchers and scientists.

By combining AstraZeneca’s disease area expertise and large, diverse datasets with BenevolentAI’s leading AI and machine learning capabilities, we can unlock the potential of this wealth of data to improve our understanding of complex disease biology and identify new targets that could treat debilitating diseases.
Sir Mene Pangalos,  
EVP and President, R&D BioPharmaceuticals, AstraZeneca
"In a highly collaborative environment, we are integrating bioinformatics, AI-based technology and experimental models to inform aspects of human cardiovascular cell-biology and disease directly. New knowledge from this project may have a significant and direct impact on the understanding of CCM pathogenesis"
Miguel Lopez-Ramirez
PhD, Assistant Professor at UC San Diego School of Medicine - University of California San Diego
Data Diversity Initiative

The lack of diversity in biomedical data has serious consequences for research and treatment. We have made it our mission to join forces across industries to create tangible solutions to this urgent issue.