Challenge

Vaccine Clinical Trial Literature Synthesizer with CrewAI and Daytona

Public health advisory committees require rapid synthesis of emerging vaccine research and safety profiles across heterogeneous literature. Orchestrate a crew of specialized research agents using CrewAI in isolated Daytona sandbox environments to summarize trials and flag potential study biases. Achieve zero missing key safety signals across benchmark trial corpora.

Data ScienceHosted by Vera
Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Orchestrate an autonomous multi-agent literature synthesis crew using CrewAI and Daytona isolated execution sandboxes.

Delivery guide

How work is evaluated

Evaluation

Evaluates recall of identified adverse event safety signals from vaccine clinical trial papers.

Datasets

Shared data for this challenge

Review public datasets and any private uploads tied to your build.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
2 scoring checks
Binary
2 pass or fail dimensions
Ordinal
0 scaled dimensions
Dimension 1

zero_missed_signals

Ensures all known critical safety signals are extracted.

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 2

safety_signal_recall

Recall metric for detecting documented trial adverse events • target: 1 • range: 0-1

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Design autonomous agent roles and tasks using CrewAI framework

  • Deploy code execution tasks safely inside Daytona workspace environments

  • Extract clinical outcome endpoints and adverse event signals from PubMed articles

  • Generate unified evidence tables for federal advisory review briefs

Resources and assets

Reference links and supporting material

Dataset notes

Curated set of 50 PubMed abstracts and clinical trial reports related to childhood vaccine safety monitoring.

How this agent runs

Evaluates recall of identified adverse event safety signals from vaccine clinical trial papers.

Challenge input

JSON containing PubMed text abstracts of 5 vaccine trials.

CrewAI

Framework specified for role-playing multi-agent collaboration.

Daytona

Isolated development environment provider for safe code execution.

Evaluated output

JSON object with safety_signals list, risk_of_bias_assessment, and strategic_summary.

Checks for
  • Ensures all known critical safety signals are extracted.
  • Recall metric for detecting documented trial adverse events • target: 1 • range: 0-1
Proof of success
  • Benchmark: Clinical Trial Systematic Review Benchmark
  • Safety Signal Recall target: 1
  • 1 public reference case
Runtime evidence
  • Python execution harness
  • Python sandbox (unavailable on Versalist)
View technical recipe

Configured tools

Environment
  • Daytona · Required
Action Space
  • Daytona · Required
  • CrewAI · Optional
  • Zed · Optional

Evaluation contract

  • zero_missed_signals · Weight 1
  • safety_signal_recall · Weight 1

Recipe state

This is a preview. The configuration can change before the evaluation recipe is locked.

Frequently Asked Questions about Vaccine Clinical Trial Literature Synthesizer with CrewAI and Daytona