Bring diverse data.
We’re seeking cfDNA sequencing datasets, linked clinical outcomes, and partners with samples or cohorts to explore together.
FROM FRAGMENTS TO CLINICAL INTELLIGENCE
We’re building a foundation model to turn cell-free DNA data into clinical intelligence. Bring your data, your clinical questions, or your expertise.
↗01 / OUR APPROACH
A single dataset can help answer a specific question. Learning across datasets could unlock many more.
We’re bringing together cfDNA data and clinical expertise to learn the biology shared across diagnostic questions. Our aim is to give each new application a stronger starting point.
We’re seeking cfDNA sequencing datasets, linked clinical outcomes, and partners with samples or cohorts to explore together.
We’re developing a foundation model that learns patterns across samples, conditions, and datasets, so that new applications can share what it learns.
Together with clinical and diagnostic partners, we want to adapt and evaluate that foundation against questions that matter in care.
ONE FOUNDATION. MANY POSSIBILITIES.
We want to build a foundation for a wide range of blood-based diagnostics. These are the questions we want to explore with partners.
Can we identify a signal of disease earlier?
Where in the body is a signal coming from?
Which biological differences could matter for care?
Is a treatment having the intended effect?
Is a disease signal still present after treatment?
Is a disease signal returning over time?
Potential applications to develop and validate with collaborators.
02 / THE PEOPLE BEHIND THE QUESTION
Founded by Duco Gaillard, a PhD researcher at the Netherlands Cancer Institute and TU Delft, Circulating Intelligence brings together cfDNA fragmentomics and foundation-model research.
We are developing the technology and building collaborations to test it against meaningful clinical questions.
DATA. QUESTIONS. PEOPLE.
We’re looking for collaborators who want to build the next generation of clinical intelligence with us.
Biobanks, cohort teams, sequencing labs, and researchers with cfDNA data or samples.
Discuss a datasetClinicians, diagnostic developers, and biotech teams with a question to answer.
Bring a clinical questionPeople working across machine learning, genomics, and translation who want to contribute.
Start a conversation