An Open Platform and AI Agent for Clinically Validated Precision Oncology Reporting
Precision oncology requires the accurate interpretation of next-generation sequencing data to inform therapeutic decisions, yet the translation of complex genomic profiles into actionable clinical reports remains a critical bottleneck confined to well-resourced academic centers and commercial laboratories. Applying general-purpose large language models directly to clinical genomic data introduces substantial risks, including hallucination, lack of provenance, and incompatibility with regulatory standards governing molecular diagnostics. Here we present Turnkey Precision Oncology, an open-source, cloud-first clinically validated platform that standardizes heterogeneous DNA and RNA sequencing data into a unified relational model, and deploy the first artificial intelligence agent purpose-built for molecular pathology. Rather than generating unconstrained free-text, the agent operates exclusively against the validated data model, autonomously querying structured patient results and cross-referencing authoritative knowledge bases to produce draft clinical reports in which every assertion is traceable to its source evidence. A human-in-the-loop reporting interface enables pathologist verification prior to sign-off, preserving regulatory compliance while substantially reducing interpretive burden.
The platform will be validated under clinical laboratory standards across two hundred retrospective cases enriched for rare and pediatric cancers, evaluating high concordance with expert pathologist interpretations, accurate variant tiering, and reductions in reporting time. By coupling rigorous analytical guardrails with autonomous clinical reasoning, this work establishes a framework for safe, scalable, and transparent AI-assisted genomic reporting accessible to laboratories of all sizes.