Public evaluation

Target Prioritization Ranking

Evaluation will focus on the agent's ability to rank a list of targets correctly according to a specific scoring weighted formula provided in the prompt.

Evaluation type

task based

Challenge

Precision Target Prioritization Agent

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

Target Prioritization Ranking

Rank top 5 targets for 'Alzheimer's Disease' based on association score and tractability.

Input format

Disease name: 'Alzheimer's Disease'

Output format

Ordered JSON list of target symbols with justification

Linked challenge

Precision Target Prioritization Agent

Design a target-disease prioritization system that leverages the Claude Agents SDK's 'Extended Thinking' capabilities to reason over complex genetic evidence. Your agent will interface with the Open Targets GraphQL API to retrieve genetic constraint scores (pLI), target-disease association scores, and drug tractability data. Using the o4-mini model for rapid data parsing within the agent loop, the system must prioritize therapeutic targets for specific diseases based on evidence strength and clinical tractability. The challenge involves writing a GraphQL planner that dynamically constructs queries to minimize data transfer while maximizing information gain (e.g., fetching L2G scores for specific variants). Claude will then synthesize this data to explain 'why' a specific target is prioritized, citing genetic scores and clinical trial status.

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