The Need for a Change
in Life Science Signal Detection

The Paradigm Shift – Put Into Perspective by CEO Michael Heltzen.

Imagine trying to understand music by simply listening to sound bits out of order from an unknown song, one type of instrument at a time. That would be almost impossible, right?

Yet for most life science researchers, that’s the kind of complexity they face when trying to understand a disease or how the biology of their interest is working.

It is understandable why life science researchers are often spending a lifetime specializing in either Genomics, or Proteomics, or Transcriptomics, or… that is the life science world’s equivalent of specializing in the different kinds of instrument such as guitar, drums, or flute, but being tone-deaf to all other instruments.

Current life science signal detection is 99.9% of the time just working from a “reductionist biology” perspective of “one signal type at a time”, and hoping to find a “single analyte signal” that is the most important one to make a good drug or diagnostic test or other life science application.

Very few researchers have the ability to work on all perspectives of system biology – even if they will all admit that it should be studied in such a perspective in a perfect world. They simply do not have the tools, the budgets and comprehension bandwidth to work on anything else than one type of signal at a time (DNA, RNA or Proteins). This has lead to a long era where we have been developing datasets (frozen snapshots in time), instead of having access to live signals via data-streams. These “frozen in time” bottlenecks come mostly from the “sample prep” methods like DNA/RNA amplification, protein labeling etc. that are needed to get optical systems to measure these molecular signals that are smaller than the wavelength of light.

All of this has resulted in a life science industry suffering from “omics tunnel vision” and without a way of interacting with the signals that runs biology. Until now!

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