Quark Knowledge Graph Solution

Drug Discovery, Target Identification, Biomarker Discovery and Drug Repurposing require analysis of complex associations between genes, proteins, molecular pathways, diseases and drugs. The growing volume of continuously updated public and proprietary data makes it challenging to extract relevant information from fragmented and siloed data resources.

Our Knowledge graph (KG) solution utilizes graph database and advanced GenAI agentic workflows to address these issues by

• Multimodal Data Integration: Knowledge graphs integrate multimodal data from diverse sources, providing researchers with a unified integration layer for all their internal and external data. Our KG solution provides integration of custom data resources including but not limited to GO terms, Reactome Pathways, WikiPathways, Human Phenotype Ontology (HPO), CIViC, MeSH terms based on customers’ unique use cases.
• Continuous integration of new data: Our KG solution also helps in automatically updating the public and proprietary data resources. Ontology integration: Built on an ontological backbone which supports seamless merging of similar ontologies to avoid redundancy. Scalable infrastructure: Powered by scalable AWS infrastructure and services such as Neptune and Bedrock.
• GenAI-driven Drug Discovery: Natural language querying capability over KG using advanced GenAI agentic workflows. These agentic workflows ensure the accuracy of responses and help users extract complex hidden patterns from the KG with simple natural language queries.

Read more about our KG solution: Accelerating Precision Insights with AI-Powered Knowledge Graphs