🧬 Spatial transcriptomics maps gene expression. Spatial proteomics maps proteins. Each modality provides valuable insights into how disease biology unfolds in affected tissues. But biology doesn’t happen in isolated layers. The same tissue section embeds morphology, transcripts, proteins, and functional changes simultaneously. Spatial multi-omics is the new platform technology that makes the various layers of biological organization accessible for coherent analysis.
🎯 This increasingly matters in multiple research fields and application areas, from immuno-oncology to biopharma R&D. The tumor microenvironment is defined by local alterations across several levels of biological organization – from tissue structure to molecular signaling. Spatial multi-omics connects these levels into one coherent image, something previously impossible by single-modality approaches. It identifies molecular structures for targeted therapies in direct relation to local tissue vulnerabilities that can be exploited for personalized treatments. This enables discovery and validation of novel composite biomarkers that better predict treatment response and reveals druggable pathways previously missed when analyzing molecular layers in isolation.
🛑 Spatial multi-omics generates three cost- and resource-intensive challenges for people and organizations using this platform technology. Data volumes are enormous – terabytes per experiment. Single-cell resolution requires precise segmentation across multiple imaging modalities. Complex data analysis must integrate morphology with diverse molecular layers.
✔️ Overcoming these challenges demands robust computational infrastructure for data storage and processing. It necessitates software tools designed specifically for multi-modal spatial analysis. It needs bioinformatics expertise to navigate the analytical complexity. These requirements create significant accessibility barriers and budget strains for many R&D teams.
✨ 𝐊𝐚𝐭𝐚𝐧𝐚 𝐄𝐝𝐠𝐞 from Katana Labs makes spatial multi-omics broadly accessible, by overcoming the above mentioned hurdles. Our AI-powered cloud platform provides the computational infrastructure R&D teams need. It handles terabyte-scale datasets automatically. AI-driven segmentation achieves single-cell resolution across modalities. Integrated workflows simplify multi-modal analysis – no coding required.
🆕 𝐊𝐚𝐭𝐚𝐧𝐚 𝐄𝐝𝐠𝐞 natively supports NanoString CosMx SMI and 10X Genomics Xenium platforms, as well as spatial proteomics platforms from established vendors. We enable R&D teams to analyze spatial multi-omics data in one unified environment – no extra bioinformatics team required. This empowers life scientists across biopharma, CROs, and academia to finally unlock the full potential of their spatial multi-omics data.