NLP + Multiomics Informatics

A better way to identify and prioritize drug targets

Identify therapeutic candidates via multiomics informatics and evaluate top candidates against published literature to prioritize the best targets for drug development
The challenge

A cancer therapeutics company has a high volume in-vitro system that mimics tumor microenvironments. Their scientists need to identify novel drug targets, and if they have been previously studied. The challenge was to create a data-driven process to identify and prioritize which therapeutic candidates should move forward in the drug development pipeline. A platform is needed to analyze large libraries of therapeutic candidates against the body of scientific literature and public data to provide context and insights.

Our Solution

Our team developed a comprehensive target identification (multiomics informatics) and validation (Biomedical NLP) platform. The multiomics informatics pipeline was built using publicly available -omics databases in order to generate signatures for pathways analysis to identify novel targets for drug discovery. The biomedical NLP engine extracts gene to disease relationships from ~2 TB of scientific literature. Our platform enabled their scientists to prioritize the highest quality targets for further research. As a result, our clients were able to sign collaboration agreements with new pharmaceutical partners based on the quality of the drug targets as highlighted in the data platform.

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