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Poster: 8th Theodor Escherich Symposium / 4th AMICI Symposium

By October 27, 2021January 24th, 2022No Comments

BiomeDx presents newest findings on microbiome signatures predicting immune checkpoint inhibitor therapy response.

GRAZ, October 21st/22nd: At the 8th Theodor Escherich Symposium / 4th AMICI Symposium (https://www.medunigraz.at/theodor-escherich-symposium), the BiomeDx team presented their newest results from a meta-analysis on microbiome signatures predicting immune checkpoint inhibitor therapy response in NSCLC and melanoma patients. The findings were presented in the form of a poster and discussed with academic microbiome experts and pharmaceutical representatives alike.

Our findings were met with great interest. It was enriching to discuss with experts from academia on the newest scientific developments and technologies, as well as get input from the pharmaceutical point of view on the requirements for such a biomarker in a clinical setting.

Christian Jansen from BiomeDx

About BiomeOne®

BiomeOne describes the current efforts of BiomeDx towards the world’s first stool-based response prediction test for immunotherapy (ICI). Currently, the biomarker is tested in three tumor types: non-small-cell lung cancer, renal cell carcinoma and malignant melanoma. Early research efforts support the idea of a tumor agnostic biomarker that can be used for any tumor type. Read more on BiomeOne.

About BiomeDx®

Biome Diagnostics GmbH (BiomeDx) is world leader in microbiome diagnostic products for oncology. The Austrian based MedTech company is committed to advance precision medicine by pioneering microbiome-based technologies that transform cancer care. The company is strategically positioned at the intersection of state-of-the-art DNA sequencing and advanced machine learning algorithms to develop first in class technologies for routine clinical practice. It is the world first microbiome company certified according to ISO 13485:2016 and ISO 9001:2015.

Presented poster: Meta-analysis on the specificity of microbiome-based signatures for predicting immune checkpoint inhibitor therapy response in non-small cell lung cancer patients

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