We let the data tell us what to target because we are able to generate a massive dataset that captures the complexity of whole human cells. This target-agnostic approach opens us up to novel pathways, new discoveries and ultimately, transformative medicines for patients.
An engineering mindset is a process mindset. We aim not only to discover drugs, but to build a system that quickly and efficiently discovers drugs at scale. We look beyond the direct questions in front of us to whole systems of biology. We develop processes that are repeatable, scalable and efficient. Our experiments are not done in isolation; each experiment is conducted with the intention of answering immediate direct questions and building a massive, relatable dataset that spans diseases, cell types and more.
Unlike many other AI-enabled drug discovery companies, we iterate through experimental biology (wet lab) and computation (dry lab) to test our results in a continuous, confirmatory loop. By combining dry and wet lab capabilities, we can more confidently generate actionable insights on human biology for rapid discovery of novel treatments.
Every modern biotech aspires to build cross-disciplinary teams, but our teams are equal parts tech and science. We hire experts in data science, biology, machine learning, automation, chemistry and software engineering to work together to make decisions around novel discoveries and advance our programs.