Company: BLLN
Filing Date: 2025-10-07
Form Type: S-1
Source: 0001193125-25-233697
Chunk: 26

Company: BillionToOne, Inc.
Filing Date: 2025-10-07
Form: S-1
Chunk 26
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 to be over $30 billion. 19Longer term, we believe that our smNGS-based technology could address the sensitivity challenges of early-stage cancer detection. While we have not yet started development in this area, the research work that we have done for Northstar Response and MRD is a necessary precursor for early detection development. In particular, we believe that a sensitive tissue-free MRD test, which we have already de-risked by the recent launch of an ultra-sensitive response monitoring assay (Northstar Response v2), which can detect tumor DNA in blood down to a limit of detection (LOD) of 0.01%, can be technically equivalent to an early detection test for cancer. 20We estimate the annual United States market opportunity for early detection to be over $50 billion. 21 Our vision of powering AI-enabledpersonalized medicine for all Healthcare today stands at an inflection point, poised for transformation through the convergence of unprecedented molecular insights and artificial intelligence (AI). Despite significant advances in precision medicine, particularly in oncology where treatments have evolved from being organ-based to increasingly being mutation-based, response rates for many marketed targeted therapies can be as low as single-digit percentages in their indicated patient populations. Similarly, pregnancy care follows one-size-fits-allstandardized protocols despite unique patient biology. Even with broader technological advances, clinicians still cannot reliably predict or prevent major complications like preterm birth, preeclampsia, and gestational diabetes. This sobering reality underscores a fundamental challenge: many current approaches to precision medicine often rely on single biomarkers that fail to capture the full complexity of disease biology and individual patient variation. We believe that these important problems can be addressed in the future with the combination of AI and smNGS technology. We believe AI-enabledpersonalized medicine can revolutionize healthcare delivery across all specialties. Truly personalized medicine requires the (i) characterization of the disease specific to each patient beyond the presence of the single mutation marker to quantification of disease biology of individuals at the single-molecule level, and (ii) integration of this characterization with multi-modal clinical history, powered by AI. We have already built products for this characterization, and we are starting to integrate our diagnostics with this multi-modal clinical history. Our approach to building AI-enabledprecision medicine will begin with our ability to generate extraordinarily precise molecular data. As we continue to generate unique data via our smNGS platform, we are building a differentiated and clinically actionable genomics dataset. Our advantage stems from two key factors: first, our biomarker measurements achieve single