@ EMBL-EBI

We investigate the molecular and cellular mechanisms by which environmental chemical exposures contribute to human disease using machine learning and multimodal data.

The Big Problem

Environmental contaminants cause 16% of premature deaths worldwide, yet most chemicals in commercial use have never been assessed for their potential to impact human health. Traditional chemical safety evaluation methods that use live animals are too expensive and slow to assess environmental chemical contributions to disease at scale.

There are too many chemicals with unknown toxicity to assess with traditional methods.

A New Paradigm

There are too many chemicals with unknown toxicity to assess with traditional methods.

Drug discovery programs routinely screen thousands to millions of compounds in computational and cellular models for their potential to treat disease. What if we used this same technology to assess whether chemicals used in other sectors of society are dangerous? Scientists and government regulators are urgently working to implement high-throughput screening methods to prioritize resource-instensive testing for the most hazardous compounds.

Computational Biology Challenges

A brute-force approach of testing every compound in all cell types and species is impractical. Instead, scientists must develop computational approaches that leverage prior knowledge of taxonomic relationships, cell types, and cell state to design efficient chemical screens and extrapolate observed toxicity across biological space.

There are too many chemicals with unknown toxicity to assess with traditional methods.

Our Work

Omics data enables us to measure thousands of molecular and morphological features from cells after they are exposed to chemicals. When we measure these data from in vitro cellular assays, we call it “cell profiling”. Using cell profiling data, the Ewald Lab:

We also value collaborating closely with stakeholders across government, industry, and academia to maximize the translational impact of our work.