We turn cancer biology into intelligence that care teams act on. Not another report to skim

Unravel did not start from a slide deck. For nearly two decades our leaders and collaborators have worked on a single practical problem: how to read a tumor’s biology so clinicians can choose therapy with more confidence. Early work showed that cancers behave like recognizable pathway programs—not random noise—which opened the door to systematic, data-driven decisions (including landmark reporting in Nature in 2006). What followed was the unglamorous work that makes products possible: rigorous methods to combine genomics signals, predict how tumors respond to drugs, and keep results reproducible as data volumes grew.

Today we focus on what matters in the clinic: how resistance appears over time on modern endocrine and CDK-based regimens, how the immune system and surrounding tissue shape that course, and how to turn those signals into clear, interpretable biomarkers—work reflected in models such as ENDORSE and in our broader product roadmap. National trials and translational cohorts keep that science tied to patient outcomes, not theory alone. If you want the publication trail, a curated set lives under Technology → Science; the full record is also available through PubMed for diligence teams.