Unifying Diverse Data into Interactive Maps to Fast-Track Biomedical Discovery

Leveraging deep expertise in advanced mathematics, we encode complex biomedical data into intuitive visual maps. This disruptive approach has the pottential to address a myriad of unmet clinical needs through the seamless integration of diverse biomedical data sources, including multi-omics and routine hospital records such as diagnosis, treatments, and patient outcomes.

By leveraging advanced mathematical methods that include topological data analysis, we accelerate the ability to:

• Identify biomarkers and disease subtypes

• Improve patient stratification

• Explore treatment outcomes across patient cohorts

• Facilitate the development of data-driven, personalised care strategies

We have established and proven methodologies, that bridge the gap between the massive volumes of data generated from high-throughput biomedical technologies and the urgent need for clear, actionable insights to improve patient outcomes. Our goal, to devise robust methods that enable faster discoveries, support clinical decisions, and the development of targeted therapeutic strategies.

We are open to international collaborations across the EU and globally, particularly in regions that are advancing in the field of personalised medicine and digital health. To include -

• Research institutions and universities

• Digital health innovators

• Healthcare providers and biotech/pharma companies

We are interested in R&D partnerships, technical cooperation, and where appropriate commercial agreements.

Keywords: Data integration, personalised medicine, healthcare innovation, multi-omics, visual analytics, hypothesis generation, topological data analysis, biomedical data, empowered clinical decisions