NCI Office of Data Sharing (ODS) Data Jamboree (Abstract Submissions): Submission #19

Presenter Information
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First Name: Doug









Middle Initial: B









Last Name: Fridsma









Degree(s): MD, PhD









Position/Title/Career Status: Chief Medical Officer









Organization: Health Universe









Organization Address:
San Francisco, CA










Email: Doug.Fridsma@healthUniverse.com









Other (Please Specify): {Empty}













Abstract Information
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Abstract Category: Development or refinement of analysis pipelines or AI/ML algorithms









Abstract Keywords: Agentic AI, MCP, A2A,  Clinical Trials, 









Abstract Title: Accelerating Pediatric Cancer Research Through Modular Agentic Workflows









Abstract Summary:
We propose leading a team to develop a suite of innovative AI agents leveraging the MCP (Model Context Protocol) and A2A (Agent-to-Agent) architecture within Health Universe to transform pediatric cancer research workflows. Our solution will create composable, intelligent agents that seamlessly integrate NCI's vast data resources—including TARGET, CCDI, and clinical trial databases—to accelerate the bench-to-bedside pipeline.

Core Innovation: We'll build specialized agents that can be assembled into dynamic workflows. For example, a "Genomic Insight Agent" could analyze TARGET sequencing data to identify novel fusion proteins in pediatric leukemias. This discovery automatically triggers a "Drug Repurposing Agent" that queries ChEMBL and NCI's compound libraries for potential inhibitors. A "Clinical Trial Design Agent" then evaluates patient stratification strategies using CCDI demographic data, while a "Protocol Optimization Agent" ensures age-appropriate dosing and monitoring requirements.

Key Workflows We'll Enable:
Discovery-to-Trial Pipeline: Automated identification of therapeutic targets → in silico drug screening → trial protocol generation with pediatric-specific considerations
Real-time Trial Matching: Patient genomic profiles → eligible trial identification → enrollment feasibility assessment across multiple sites
Biomarker Validation: Multi-cohort analysis across NCI datasets → statistical validation → clinical implementation pathways
Technical Approach: Each agent will expose standardized MCP interfaces, enabling researchers to compose custom workflows through simple configuration. A "Pediatric Oncology Copilot" will orchestrate agent interactions, ensuring data privacy and regulatory compliance throughout.

Team Needs: Seeking collaborators with expertise in pediatric oncology, bioinformatics, clinical trial design, and MCP/LLM development. Together, we'll create a transformative platform where individual contributions multiply through intelligent agent collaboration, ultimately accelerating life-saving treatments for children with cancer.










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