Nautilus provides the Voyager™ Platform, a proteomics solution that uses proprietary Iterative Mapping technology to deliver deep, single‑molecule quantification of billions of protein molecules and proteoforms in a single assay.
Funding
$200M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
9OPAFounders
Product
Problem
Researchers lack methods that can comprehensively quantify the full range of proteins and proteoforms in a single experiment, limiting insight into disease mechanisms, biomarker discovery, and target validation.
Solution
Nautilus offers the Voyager™ Platform, which applies its proprietary Iterative Mapping technology to achieve deep, single‑molecule quantification of billions of protein molecules across the proteome. Hundreds of multi‑affinity probes repeatedly interrogate ultra‑dense arrays, and machine‑learning algorithms translate binding patterns into high‑confidence protein and proteoform identifications. The result is reproducible digital counts with up to nine orders of magnitude dynamic range, enabling researchers to detect low‑abundance species without depleting high‑abundance proteins. By delivering comprehensive, quantitative proteomic data in a standardized, scalable workflow, the platform supports drug‑target discovery, biomarker identification, and exploratory biology studies.
Target Audience
Primary users are pharmaceutical and biotech researchers, academic labs, and clinical scientists who need deep, quantitative proteomic profiling for drug development, biomarker discovery, or fundamental biological research.
Features
- Ultra‑dense single‑molecule arrays with up to 10 billion landing pads per sample for high sensitivity and dynamic range
- Multi‑affinity probe library that captures thousands of unique proteins and proteoforms in a single assay
- Iterative probing cycles that repeatedly interrogate each immobilized protein to improve identification confidence
- Machine‑learning‑driven analysis that converts probe binding patterns into accurate digital protein counts
- Integrated end‑to‑end workflow from sample preparation to quantification, compatible with standard laboratory equipment
- High reproducibility and standardization across runs, reducing technical noise and enabling reliable longitudinal studies
- Data output in digital count format optimized for AI integration and multi‑omic analyses