Taming Frontier Data Part 4: How to make frontier data FAIR-compliant and usable by AI and ML applications and models

Generative AI and machine learning hold transformative potential for the life sciences sector, with 66% of companies experimenting with these technologies and AI contributing to the development of 19 drugs in 2023. However, to fully leverage AI and ML applications, life sciences organizations must ensure their data is FAIR-compliant (Findable, Accessible, Interoperable, and Reusable), which is crucial for effective clinical diagnostics and accelerated research breakthroughs. Quest Diagnostics faced challenges in building an enterprise-wide multi-omics data mesh that complied with the Global Alliance for Genomics and Health's Data Use Ontology standards. To meet these challenges, Quest collaborated with TileDB to create a robust data infrastructure that supports large-scale data analysis, offering a unified data mesh capable of handling millions of samples and reducing storage costs. TileDB's solution enabled Quest to optimize its bioinformatics goals by integrating ML-ready genomics data, thereby enhancing the use of AI applications.