Public evaluation

Variant Actionability Triage

The evaluation measures the agent's ability to identify actionable variants and provide the correct clinical trial matches.

Evaluation type

task based

Challenge

Autonomous Oncology Triage: Multimodal Variant Interpretation with Google ADK

Difficulty

Advanced

Rigor

Unspecified

Open linked challenge

Evaluation overview

How the linked challenge is judged: tasks, benchmarks, and criteria count.

Tasks

Benchmarks

Criteria

Task templates

Inputs and expected outputs.

Task 1

Variant Actionability Triage

Identify if a patient with a BRCA2 mutation and specific noncoding variants is eligible for PARP inhibitor trials.

Input format

VCF file + Clinical History PDF

Output format

Trial Eligibility Report (JSON)

Linked challenge

Autonomous Oncology Triage: Multimodal Variant Interpretation with Google ADK

With oncology businesses like Guardant Health and Tempus AI reporting massive revenue growth, the bottleneck in precision medicine has shifted from sequencing to data interpretation. Germany's new Precision Medicine Pilot emphasizes robust data infrastructure to handle this surge. In this challenge, you will use the Google Agent Development Kit (ADK) and the o3-mini model to build an autonomous lab agent capable of triaging genomic variants and matching them to clinical trials. Your agent must handle multimodal inputs, including raw VCF (Variant Call Format) files, pathology PDFs, and structured EHR data. Using Google ADK’s integration with Vertex AI, you will implement a 'Reasoning-and-Acting' (ReAct) loop that queries the COSMIC database and clinicaltrials.gov. The goal is to automate the extraction of 'Actionable Alterations' and flag cases where high-fidelity WGS (like PacBio HiFi) is required for resolving ambiguous structural variants in noncoding regions, as highlighted in recent Nature Genetics research.

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