On Jun. 8, 2026, the Wellcome Sanger Institute, Google.org, and Google DeepMind announced they are partnering up to generate large-scale genomic datasets and power AI-driven discoveries.

Over five years, the consortium will focus on addressing data gaps through strategic data generation and building high-quality AI-ready genomic datasets. These datasets will power the next generation of AI models for biological discovery. 

The partnership aims to make biology more predictive by developing a framework that will support the generation of AI-ready biological datasets specifically designed to train advanced machine learning models. The collaboration seeks to accelerate scientific discovery and unlock deeper biological and biomedical insights. 

The organisations will establish a broader consortium focused on generating the biological data required to advance AI in biology and welcome additional collaborators who share their goals.

The initiative builds on an existing relationship between the Sanger Institute and Google DeepMind, including previous research collaborations, a joint AI in genomics fellowship, and shared efforts to strengthen global AI capability and capacity in research, including in lower and middle income countries.

AI is creating unprecedented opportunities to extract insight from genomic and molecular data. While AI is already being used in genomics, opportunities remain to develop models and datasets for underexplored areas of the life sciences. The datasets that the consortium will generate will provide a foundation for training and evaluating AI models capable of making more accurate predictions about biological processes.

Researchers at the Sanger Institute are already applying AI-powered approaches across genomics, from extracting insights from large-scale datasets, integrating information from genes, RNA and proteins, to designing and interpreting experiments.