BiomeOne®– ICI response prediction
BiomeOne® is the world’s first stool-based response prediction test for immunotherapy (ICI). With BiomeOne® we are able to analyze the patient’s unique intestinal microbiome signature and provide a single biomarker that informs the oncologist’s treatment decision on whether or not cancer immunotherapy benefits the patient.
Predicts response & tolerability to cancer immunotherapy
Supports decision making at the point of care
Non-invasive & performed on a single stool sample
”Microbiome diagnostics is certainly one of the most promising research areas of our time. This project should provide us with deeper insights into the interaction between the body's own microbiome and cancer immunotherapy. This could help us in the future to tailor cancer treatment more specifically to affected patients and to individualize the risk-benefit profile of the therapy as much as possible.Prim. Doz. Dr. Arschang ValipourHead of Karl Landsteiner Institute for Lung Research and Pulmonary Oncology, Austria
Receive valid results from a single sample
Only one stool sample is required to perform a thorough DNA analysis and predict the probability of response to cancer immunotherapy for an individual patient.
Currently, BiomeOne® has a prediction accuracy of >80% based on samples from cancer patients across middle Europe and the US.
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BiomeOne® delivers consistent results for PD-1/PDL-1 and CTLA-4 inhibitors
BiomeOne® is based on extensive in-house research and results from multiple international studies in which patients received PD-1/PDL-1 as well as CTLA-4 inhibitors. The effect has proven to be pathway independent.
It took over thousands of different variations of machine learning algorithms to identify the best suited methods to analyse the response and tolerability prediction to immune checkpoint inhibitors.
Reliable and consistent across three different types of cancer
BiomeOne® is based on robust data from non-small-cell lung cancer, renal cell carcinoma and malignant melanoma patients. Our biomarker has proven to deliver reliable and consistent results across all three cancer types.
Comparison with other cancer types strongly suggest that the immune modulating effect of the intestinal microbiome is systemic and therefore not limited to a specific disease, but rather tumor agnostic.
BiomeCRC®– Early detection microbiome test for colorectal cancer
BiomeCRC is a colorectal cancer preventive screening test based on the intestinal microbiome. The tool is powered by the proven BiomeDx platform and data from numerous clinical trials. Ongoing research in collaboration with the Medical University of Vienna includes over 1000 probands.
Cost efficient & non invasive
Able to differentiate tumour stages
Easily scaleable via screening programs
BiomeFMT – Stool donor identification for non-responders to cancer immunotherapy
BiomeFMT is a novel stool sample test – in development. BiomeFMT will be used to identify ideal donors for fecal microbiota transplantation for non-responders to cancer immunotherapy (ICI). For the first time it will be possible to screen large amounts of samples from biobanks in order to find potential super-responders to ICI.
Identifies donors for fecal microbiota transplantation
Unlock the full power of cancer immunotherapy
Scalable for broad clinical use
myBioma®– Because your health starts in the gut
Available on mybioma.com
Our well-established lifestyle product myBioma® is available for any European citizen to analyse one’s gut health. The microbiome report is available via PDF and mobile app on iOS and Android. The results include information on diversity, nutrition, health and dietary recommendations as well as a large network of therapists.
More information about myBioma® can be found at www.mybioma.com.
Partner solution – End-to-end solution for microbiome analysis
Clinical trials, pilot projects, discovery
As a research-driven company, we collaborate with academic institutions and partners to uncover new correlations in the microbiome. For this purpose, we have developed an own study pipeline that performs statistical and machine learning algorithms in regards to the main hypothesis of the project.