Mapping Exposure-Induced Immune Effects: Connecting the Exposome and the Immunome
Partner in the spotlight: Biogenity
February 23, 2023
Today our partner in the spotlight is Biogenity – a Contract Research Organisation (CRO) focusing on making bioinformatics, Machine- and Deep Learning accessible. Converting data into biology is Biogenity’s mission, which is why explainability is one of the main focusses of development in Biogenity. This focus has made the Biogenity team experts in explainable Artificial Intelligence (AI), opening the black box of these models.
The organisation provides a full-service Omics Core Facility for proteomics, metabolomics, transcriptome, and multi-omics with the aim of turning these complex datasets into useful knowledge using Machine Learning and bioinformatics, helping researchers get from sample to biology. Omics have become a central driver in the R&D field of basic, medical and clinical research, making understanding this data critical. Biogenity’s founders have also created Omics Studio, an early-stage software that combines multi-omics, machine learning, network analysis, and bioinformatics to assist in the discovery of biomarkers for new diagnostics, prognostics, and therapeutics targets.
Within the broader scope of EXIMIOUS, Biogenity, represented in the project by Kenneth Kastaniegaard and Alessandro Ranieri, collaborates with NRCWE and Statistics Denmark to analyse the large datasets of the DOC*X cohort, containing over forty years of occupational and medical data of a large part of the Danish population. Although modern AI has advanced significantly in only a few years, health records remain relatively underused. By training machine learning models on such data, and combining the learned parameters with a variety of explanatory techniques, the outcome of the project will include generating hypotheses for targeted statistical analyses, build novel tools for interpreting the datasets, and finally to provide insight on the relationships between occupational exposures and autoimmune diseases.
To learn more about the work being done in EXIMIOUS and how AI is being used to help understand occupational exposures, check out the article Understanding work exposures: where AI and epidemiological analyses meet in the first issue of our EXIMIOUS newsletter.