
ACCELERATING TIME


Disrupting Drug Discovery Times & Costs at All Stages

Purpose Built for Multi-Omics and Medicine Data
Our platform can parse multi-omics data, including Genomics, Transcriptome, Metagenome, Proteome, Metabolome, Phenotype/Clinical Data and Images, enabling you to discover the insights you need fast and efficiently.

Machine Learning for Precision Health & Medicine
Real-World Examples of Multi-Omics Data Analysis
Rare Disease Diagnosis
Integrated genomic, transcriptomic, and proteomic data to identify novel biomarkers in patients with undiagnosed rare diseases, reducing diagnostic time from years to weeks.
Cardiovascular Risk Prediction
Combined genomic, metabolomic, and clinical data to develop a more accurate cardiovascular risk prediction model, identifying high-risk patients before symptoms appear.
Cancer Treatment Response
Analyzed tumor genomics, transcriptomics, and immune profiles to predict patient response to immunotherapy, enabling personalized treatment selection.
Drug Repurposing
Integrated transcriptomic, proteomic, and metabolomic data to identify existing drugs that could be repurposed for inflammatory bowel disease treatment.
