If you need specific data from one of our assays, our team can generate reproducible measurements with any of our technologies. Contact us to learn more and get the training data needed for AI success.
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for AI Success
Do you need high-quality data for AI-powered drug discovery? Leveraging our years of experience in profiling key aspects of RNA biology, eVERSE provides the data needed for target discovery and drug design.
AI-Ready Datasets
AI is becoming foundational to drug development, from fine-tuning gene editing therapies to be stable in specific cell types to designing more potent siRNAs. eVERSE provides the reproducible data needed to train accurate AI models for drug discovery.
Request accessRNA-Based Vaccines
RNA-Based Therapies
Small Oligonucleotides
Small Molecules
Multidimensional data for AI success
Developing next-generation therapeutics with AI demands data that’s reproducible and captures every key aspect of RNA biology. With eVERSE, our partners gain access to a comprehensive suite of RNA profiling technologies—from revealing secondary structures that influence siRNA potency to quantifying translation rates critical for RNA vaccine efficacy. Discover below how eVERSE delivers the essential data for AI-driven success.
High-quality reference data for all aspects of RNA biology
With eVERSE, we transform raw biological data into high-quality, AI-ready datasets for RNA-based medicines, small oligonucleotides, and small molecule therapeutics. Our sequencing assays and bioinformatics workflows capture RNA biology’s complexities, enabling precise AI model training.
RNA secondary structure revealed
eSHAPE directly measures RNA secondary structure in buffer conditions and in cells, providing the data needed to train AI models to:
- Improve RNA therapeutic stability by improving structure predictions
- Design effective siRNAs by targeting accessible regions
- Develop small molecule therapies that target druggable pockets
eSHAPE-supported structure of a gene in the context of cellular factors such as RNA-binding proteins.
Discover the UTR landscape
UTRs are uniquely expressed in disease states and regulate the stability and translation of genes. By including data on UTR usage into AI models, drug developers can improve:
- Cell-specific regulation of RNA-based therapies
- The selection of small molecules against disease-specific targets
- The design of small oligonucleotides to specific isoforms
A 5’ UTR is more active in cancerous samples and not in healthy samples, making it a potential target for selective regulation in cancer.
Map miRNA binding
miRNAs regulate the stability of RNA molecules and are implicated in a number of diseases. Incorporation of miRNA data into AI models allows drug developers to:
- Fine-tune RNA activity into specific cell types
- Design ASOs to limit miRNA binding
- Avoid competition for siRNA therapies
Direct detection of miRNA binding in the 3' UTR of E2F3. Each row is a different miRNA. Peaks are where that specific miRNA binds.
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What our
partners say
"Eclipsebio has been an invaluable partner to Deep Genomics. They've helped us generate massive miRNA-related datasets for training AI models, and have designed and conducted bespoke assays to illuminate the mechanism underlying some of our lead therapeutic compounds."
"End-Seq assays are an invaluable part of our target assessment process at Ribometrix. The data are robust and often reveal novel 5’ and 3’ ends that aren’t reflected in public databases. Having this knowledge significantly influences strategic decisions around target selection in our RNA-targeting drug development process."