Material Analysis Software
Luma is a material management software designed for data-driven R&D that offers low-code ontology modeling, unified multimodal data management with full traceability, AI-ready data preparation, advanced data harmonization, and upcoming BioGlyph integration to enhance material classification, streamline schema creation, and optimize antibody design workflows.
Material management software built for data-driven R&D
Luma simplifies material and ontology management with low-code modeling, full traceability, and AI-ready data preparation, delivering scientific depth and precision.
Revolutionize material data management with Luma
Enhance material classification with extensible ontologies
With Luma’s advanced ontology management, R&D teams can streamline complex data classification and retrieval, minimizing wasted time searching for critical information.
Simplify data modeling with low-code tools
Empower your team with low-code data modeling tools that streamline schema creation and support full versioning, ensuring long-term data integrity.
Unified entity management with full data traceability
Luma centralizes multimodal data management, allowing you to manage different types of research data within a single platform, with full traceability for compliance and reporting.
Coming soon: registration capabilities
AI-ready data preparation
Get your data AI-ready with automated preparation tools that enhance consistency and pave the way for advanced analytics and machine learning.
Advanced data harmonization
Seamlessly correlate registration data, results, and task information between multiple softwares to improve consistency across all stages of research and reduce manual efforts.
BioGlyph integration
Introducing the ability to draw and register antibody glyphs from BioGlyph, enhancing your end-to-end antibody design workflows.
Experience Luma’s powerful material data management firsthand
Ready to optimize your material data management? Request a demo today and see how Luma can streamline your R&D workflows.
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The pharmaceutical industry is shifting from single-mode to multimodal drug discovery, incorporating diverse therapeutic modalities like biologics, gene therapies, and small molecules, but this evolution presents significant challenges in integrating heterogeneous R&D data and technologies, necessitating advanced, compatible platforms to enable efficient collaboration and leverage AI-driven insights for faster, cost-effective drug development.
Limitations of Existing Life Science Software—and the Opportunity to Evolve
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