Large-scale multimodal data has become a driving force in life sciences research, and your organization can’t afford to miss this opportunity. How is large-scale multimodal data fitting into your plan and budget for 2025? Do you have the right technology to advance this work effectively and efficiently across researchers, informatics and ML teams? How will you prioritize a FAIR multi-omics platform to best leverage AI and machine learning? If you’re looking for  answers to these questions, you’re not alone. In this webinar, we will explore the complex infrastructure map for -omics data and learn key evaluation criteria to inform durable decisions for your data platform that will drive drug discovery and development.

Speaker

Seth Shelnutt

Chief Technology Officer, TileDB

Key takeaways

• Learn the essential criteria for selecting a multimodal data platform that can scale effectively with your team’s needs, addressing data integration, scalability and cross-functional collaboration.
  
  
• Understand how to prioritize a FAIR (Findable, Accessible, Interoperable, and Reusable) multi-omics platform to ensure long-term value for researchers, informatics and machine learning teams.
  
  
• Discover how to future-proof your data infrastructure by choosing technology solutions that will support your drug discovery and development initiatives for years to come.

TileDB - Designed for Discovery

TileDB is foundational software designed by scientists for scientific discovery. TileDB structures all data types, including data that does not fit into relational databases designed for structured tabular data. Built on a powerful shape-shifting array database, TileDB handles the complexities of non-traditional “unstructured” multimodal data, such as genomic variants, bulk and single-cell transcriptomics, proteomics and, biomedical imaging, as well as the frontier data of the future. Used by science and data teams within big pharma and biotechs to power their multiomics FAIR data platforms, TileDB is the destination for scientific breakthroughs where frontier multimodal data is driving drug discovery.