We have over twenty years of experience in data processing, data-driven modeling, and building software products that utilize machine learning.
We apply machine-learning to chemistry. Our products maximize the utility of data, reducing the time and cost of chemical R&D.
We build enterprise solutions. Designed with integration in mind, our technologies are both accessible via API and deployable on our partners’ infrastructure.
Press Release ToxTrack Wins Two NCATS ASPIRE Awards, Part of the HEAL Initiative
Toxicological Sciences Machine Learning of Toxicological Big Data Enables Read-Across Structure Activity Relationships (RASAR) Outperforming Animal Test Reproducibility (Tom Luechtefeld, Dan Marsh)
The Economist It should soon be easier to tell a chemical’s toxicity without killing animals
Nature Software beats animal tests at predicting toxicity of chemicals
Quartz AI is getting closer to replacing animal testing
NIH, National Toxicology Program Workshop: Predictive Models for Acute Oral Systemic Toxicity
Founder & Lead Scientist
Chief Technology Officer
Chief Revenue Officer