Magnetic Group Signaling (MGS®) Technology

Magnetic Group Signaling (MGS®) standardizes NMR systems and sample processing to ensure reproducible results on different NMR instruments.

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Advanced. Automated. Affordable. Mastering Metabolite Networks for Real-Time Precision Medicine.

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AXINON® System

AXINON® is the first modular software-based system providing hardware, operating system, MGS® processor and individual test applications.

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The <i>AXINON<sup>&reg;</sup> System</i>. |Precision Diagnostics.

AXINON® is the first modular software-based system for clinical diagnostics - providing hardware, operating system, Magnetic Group Signaling (MGS®) processor and individual test applications, collectively enabling:
  •         Innovative real-time use of metabolic data
  •         Precise results for specific medical questions and diagnostic decisions
  •         Standardized analysis
  •         Multi-testing flexibility
  •         High throughput capability
  •                 Fully automated lab solution
  •                 High reproducibility (inter-laboratory precision)
  •                 Connectivity to lab systems (LIS/LIMS)
  •                 Easy-to-use

Platform

The NMR based AXINON® System offers high throughput multi-testing capability

Precision

AXINON® enables a more detailed, standardized and automated lipoprotein and metabolite profiling

Performance

Identification of more than 400 metabolites within one run enables the discovery of meaningful metabolite constellations/profiles

<i>Magnetic Group Signaling.</i> |Next Generation of NMR Use.

Magnetic Group Signaling (MGS®) is the core of the AXINON® System. MGS® enables AXINON® to reproducibly elucidate metabolite constellations from an NMR (nuclear magnetic resonance spectroscopy) spectrum and thus allows us a NMR use for diagnostic purpose.

  • Standardized algorithms based on Artificial Intelligence (AI)
  • Reproducible multivariable signal fitting
  • Quantitative multi-signal interpretation
  • Validated extraction of information from NMR spectra
  • Sophisticated SCORE calculation 

 

 

“With MGS®, we evolved NMR to a fully automated IVD System applicable to routine analysis. It enables diagnostics with excellent precision and comparability. MGS®-generated data can be analysed by several other AXINON® tests and reveal new diagnostic information.”

Dr. Daniela Baumstark

Head of Lipoprotein Analysis & Data Processing at numares 

 

Importance of Metabolomics. |Use of Metabolite Constellations.

The concentration of metabolic products (metabolites) in various body fluids depends on the genetic and environmental exposure of a human being. This individual metabolic pattern is subject to normal physiological variation, but may also reflect pathological processes in the body.

Nuclear magnetic resonance (NMR) spectroscopy is the method of choice to detect metabolite constellations, as NMR allows the simultaneous quantification of ~400 metabolites in human specimens.

Metabolites & AI. |Combine Human & Machine.

Finding metabolite constellations among hundreds of signals is not easy. We use machine learning to analyze study data together with NMR metabolite measurements to identify the markers that carry the most information about the disease in question and to build an equation that represents the metabolite constellation. This equation is then used as a diagnostic test in our products.

Machine learning comprises a number of methods within the field of artificial intelligence. Basically, these are very sophisticated statistical algorithms that use labeled examples of both healthy and sick subjects to identify the signals that separate the two (“learning the difference”). The resulting models from this metabolite constellation can then be used to predict if a patient is healthy or sick.

Our highly skilled statisticians ensure that the machine learning algorithms are used expertly. We complement this with the knowledge of our biochemists to guide the learning process with human knowledge. Combining the strengths of human and machine we ensure best possible results and allow our models to be understood by human experts like physicians.