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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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AXINON® System

Using FDA-cleared technology, this is our core platform. It incorporates diagnostic testing algorithms into nuclear magnetic resonance (NMR) spectroscopy. It's the first modular software-based system for clinical diagnostics. 

New paper in Frontiers in Medicine reveals first reliable biomarker test for early kidney transplant rejection detection in living-donor recipients

  • Use of numares’ metabolite constellation showed a stable urinary metabolic profile in the first 14 days for living donor recipients, enabling accurate early rejection detection
  • Deceased donor recipients exhibit ischemiadriven metabolic alterations that transiently mask rejection signals
  • Groundbreaking study was led by researchers at University Hospital Regensburg in conjunction with numares Health

Regensburg, Germany, 09 March 2026 – numares Health (“numares”), the transformative metabolomics company pioneering multidimensional biomarker insights that deliver clinical pathways for optimal patient care, today announces the publication of a new analysis in Frontiers in Medicine highlighting numares’ urinary metabolite constellation as the first biomarker test to show reliable diagnostic accuracy for detecting acute kidney transplant rejection during the critical first 14 days after transplantation in recipients of living donor kidneys.

The study, “Diagnosis of Early Kidney Allograft Rejection: Influencing Factors in Metabolite‑Based Urine Analysis, confirms that while many biomarker platforms struggle in the immediate post‑transplant phase, the metabolite constellation developed and validated by numares performs with full diagnostic strength right from day 1 in living-donor recipients (AUC 0.72; 95% CI 0.62–0.82).

Acute rejection remains a major challenge in kidney transplantation, often requiring invasive biopsies for diagnosis. Traditional methods, such as serum creatinine monitoring, lack sensitivity and specificity, leading to missed cases or unnecessary procedures.

The game‑changing study, led by researchers at University Hospital Regensburg and numares, identified critical factors that influence the accuracy of numares’ non-invasive urine test for early detection of acute kidney allograft rejection – especially in the immediate phase after transplantation.

Prof. Dr. med. Miriam Banas, Department of Nephrology, University Hospital Regensburg, commented:“Unlike other biomarker approaches, which cannot be applied reliably in the first days after transplantation, this metabolite constellation retains its diagnostic strength in living‑donor recipients. This is a meaningful step toward continuous, non‑invasive monitoring from day one.

Florian Voss, Chief Executive Officer of numares Health, said: At numares, we use nuclear magnetic resonance (NMR) spectroscopy to quantify multiple biomarkers from a single serum sample. The paper’s findings are both a validation of our technology and a source of new hope for improving patient outcomes through personalized post-transplant monitoring.”

numaresHealth’surinary assay  leverages NMR metabolomics to support clinical decision making in the context of kidney transplant rejection. This non-invasive test analyzes and evaluates a metabolite biomarker constellation previously identified and validated and is suitable for outpatient monitoring to improve patient compliance, decreasing the need for invasive, painful and expensive biopsy.

The UMBRELLA study conducted at the Department of Nephrology, University Hospital Regensburg, Germany, analysed 682 urine samples from 109 kidney transplant recipients within the first 14 days post-transplant, using metabolomic profiling alongside 29 clinical and transplant-related parameters. Ten significant confounding factors were identified, including donor type, ischemia times, deceased donor status, recipient age, residual urine volume, eGFR, induction therapy, and HLA mismatches.

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