Besides directly measuring microbial metabolites, quantitative metabolomics enables the investigation of the effects of the microbiome on the broader metabolic picture of the host. In my talk, I will present examples of applications of metabolomics in various sample matrices and how to use this powerful tool to study the effects of the microbiome on the host.

This presentation outlines biocrates’ standardized, quantitative metabolomics solutions for large-scale and population-based studies. Emphasizing reproducibility, scalability, and compliance with FAIR data principles, biocrates technology enables a robust and broad profiling method across diverse cohorts and laboratories. By supporting data harmonization and integration, biocrates facilitates cross-study collaborations. Proven applications span multiple diseases, with use cases in cancer and cardiometabolic research. The approach integrates genomics and metabolomics (mGWAS) to reveal functional links between genetic variants and disease phenotypes, accelerating biomarker discovery and translational multi-omics research. We highlight its potential to advance precision diagnostics, therapeutic stratification, and data-driven clinical decision-making.

Kit workflow in the laboratory and the WebIDQ™ software

Metabolomics is the most relevant tool to answer the multidimensional questions of system biology. From just a few microliters of sample material, the phenotype of an individual can be uncovered. Quantitative, standardized, and quality-controlled targeted metabolomics assays guarantee robust and reproducible results that are the cornerstones of all clinical research.
biocrates kit technology offers a streamlined, high-throughput solution for quantitative metabolomics, delivering highly reproducible metabolomics data. In this presentation, we provide insights into the underlying technology and chemistry.
During this talk, we introduce our streamlined kit technology alongside WebIDQ, the companion software designed for an easy and user-friendly workflow. WebIDQ supports plate layout registration, sample analysis, quantification, data quality assessment, normalization, and export for statistical evaluation.
A brief live demonstration of WebIDQ’s key features will showcase how it simplifies metabolomics data processing.