A database for AI-generated molecular “fingerprints”
Since 2022, MSAID has been marketing a patented successor of the software whose prototype sparked the company’s founding. It streamlines the analysis of complex, large datasets. MSAID COO Daniel Zolg compares the approach to fingerprint identification: “Every protein consists of different peptides, each with its own specific fingerprint. We can make the fingerprints in a sample visible using a mass spectrometer. But the quality of these fingerprints isn’t always good-often you only have a partial print of a peptide, and sometimes they even overlap. That makes it harder to tell which measurement corresponds to which peptide. It’s a bit like trying to analyze fingerprints on a doorknob that’s been touched by many different people.”
Manually analyzing such large amounts of data is no longer possible. After all, humans are made up of more than 20,000 different proteins. The founders therefore leverage AI’s strengths in pattern simulation: an algorithm compares the measurement results with a kind of “peptide database” containing AI-generated patterns created by the team. These patterns match those produced by peptides during mass-spectrometry-based analysis. And more: they can even be used to predict what patterns will emerge when different peptides overlap.
“Using our approach, we can substantially improve protein identification in complex samples like tissue and plasma, better quantify their amounts, and reduce manual steps. Our software also enables analyses that would otherwise take several weeks to be completed in just a few days,” says MSAID CEO Martin Frejno. “That opens new avenues for early disease detection, personalized medicine, and drug development.”