Science Pool

The Foundation for Technological Innovation (FIT) is happy to announce new loan Isospec Analytics. Isospec Analytics, specializing in advanced biomolecular analysis, receives a Tech Seed loan of CHF 100’000.

Isospec Analytics, a Swiss-based startup spun out of EPFL, has secured $1.9 million in pre-seed funding to advance its groundbreaking biomolecular analysis technology. The company's innovative approach promises to identify a significantly larger number of small molecules in blood samples, potentially leading to earlier disease detection and more effective treatments.

MS Vision and Isospec Analytics have formed a partnership to advance molecular analysis by combining cryogenic IR spectroscopy with IMS-MS, aiming to improve the identification of complex molecules and reduce analytical uncertainties.

Professor Thomas Rizzo from EPFL is recognized for integrating vibrational spectroscopy with ion mobility and mass spectrometry to innovate bioanalytical science.

Isospec Analytics won Venture Kick's support for its advanced biomolecular analysis technology, aimed at accelerating drug discovery and development by providing rapid and reliable molecular characterization.

Discover how our Cryo-IR technology can transform your glycan analysis. Cryogenic IR spectroscopy inside a mass spectrometer provides an information-rich metric by which to unambiguously identify isomeric glycans. Isospec Analytics introduces groundbreaking Cryo-IR spectroscopy technology for unparalleled glycan identification. Our innovative approach solves the complex puzzle of isomeric structures.

In the world of molecular identification, high-resolution mass spectrometry has long been the gold standard. However, a groundbreaking study by van Tetering et al. has shed new light on the limitations of tandem mass spectrometry (MS-MS) for de novo molecular structure determination. This white paper explores the implications of their findings and introduces Isospec Analytics' cutting-edge solution to this critical challenge in molecular analysis.

The integration of AI in glycoinformatics requires large, high-quality, glycan datasets to train models, and inconsistent or incorrect annotations can significantly affect the performance of these models. In their review paper entitled: "Glycoinformatics in the Artificial Intelligence Era", Daniel Bojar and Frederique Lisacek explain that the limited use of AI in glycomics to date arises from peculiarities of glyco-data that are notoriously hard to produce and analyze. This white paper explains how Isospec Analytics' technology helps solve this problem.