AI² = Artificial Intelligence x Autoimmune Diseases

RHEA (“rhe-ah”) decoding the complex landscape of transcriptomic data by facilitating no-code analysis and integration of RNA sequencing data. RHEA enables researchers to identify drug targets, key biomarkers, and molecular pathways involved in disease progression and treatment response. RHEA accelerates the identification of novel therapeutic targets improving drug efficacy and supporting the development of personalized treatments.

TETHYS (“tee-thiss”) reveals the protein-level dynamics driving disease and treatment outcomes by a no-code solution that analyses and interprets large-scale proteomics data (protein expression, modifications, and interactions in biological systems). TETHYS enables the identification of protein prognostic and diagnostic biomarkers, drug targets, and protein pathways by processing mass spectrometry data. With features for data visualization, quantification, and pathway analysis, it provides critical insights into disease mechanisms and drug effects. TETHYS enables drug discovery acceleration and development, precision medicine enhancement, and therapeutic targets discovery.

Leveraging data from both RHEA and TETHYS, DIONE (“dee-own”) integrates and processes vast multi-omic, clinical trial, and real-world datasets to accelerate the discovery of novel drugs, improve clinical trial outcomes, and advance personalized medicine. The system provides accurate, data-driven predictions and insights into disease biology and treatment efficacy by leveraging advanced algorithms to analyze complex biomedical data. DIONE identifies patterns and relationships that are often missed by traditional methods, thereby enabling actionable insights for drug discovery, repurposing, patient stratification, biomarker identification, and predictive modeling.