Mass spectrometry, without the jargon
Mass spectrometry is the lab technology BioTwin uses to read thousands of biomarker signals from a single blood drop. Here is how it works, in plain language.
What it does
Mass spectrometry sorts molecules by their mass and fingerprints each one. A drop of blood is not a single substance. It is a mixture of thousands of different biomolecules, each with its own shape and weight. A mass spectrometer separates them, weighs them, and identifies them one by one.
The simplest way to picture it is a molecular scale. It reads one molecule at a time, millions of times per second, and produces a list of everything that was in the sample. That list is called a spectrum. Each peak in the spectrum corresponds to a family of molecules with a specific mass, which can then be matched to a known biomarker.
Why it reads 30,000+ biomarkers when a standard test reads 30
A standard blood test asks very narrow questions: how much cholesterol, how much glucose, how much of this hormone. Each of those questions costs a dedicated test. Because the cost adds up quickly, clinicians only order the handful that match a specific clinical suspicion. The result is a short checklist.
Mass spectrometry asks a different question. Instead of "how much of this one molecule", it asks "show me everything in this sample". The output is a full biomarker signature, not a checklist. A single analysis yields more than 30,000 measurable signals, equivalent to external lab tests beyond $3,000. That is what lets BioTwin describe 7 functional areas at once from a single finger prick, instead of chasing one suspicion at a time.
Why it costs what it costs
Mass spectrometers are complex machines. They need to be calibrated carefully, run by trained operators, and maintained constantly. The raw output is not directly readable by humans either: it takes a serious data pipeline to extract biomarkers, normalize them, and turn them into scores that mean something.
BioTwin has invested in that full pipeline, from sample handling to reference populations to the scoring models that power your virtual twin. The goal was to make this depth of analysis affordable at $150 for a BioTwin kit, while conventional laboratories would still charge far more for a fraction of the same analysis. Volume, automation, and a purpose-built stack are what close that gap.