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Targeted Genome Editor Delivery (TARGETED) Challenge
National Institute of Diabetes and Digestive and Kidney Diseases
1 Registrants
$100,000
Revolutionizing technology development of delivery systems for in vivo genome editing.
View additional information at USA.gov.
OPEN
Challenge Image

Overview

A $6,000,000 competition to improve in vivo delivery technologies for genome editors in two Target Areas: 1. Programmable delivery systems, and 2. Non-viral delivery across the blood-brain barrier.

Timeline

  • Start: 1/1/2026 1:00 PM ET
    End: 7/1/2026 9:00 PM ET
  • 6/14/2026 1:00 PM ET
  • 11/1/2026 9:00 PM ET
  • 12/30/26
  • 12/31/26

Prize

Total cash prize: $100,000

Rules

Eligibility and Participation rules for challenges can be found here.

Judging Criteria

Submissions will be judged through a combination of human review by 1) AI/ML and clinical experts to ensure usefulness of data and documentation for secondary research, and 2) formula metrics to ensure accuracy, completeness, consistency, and validity of AI-ready dataset.

Data Enhancement - null Evaluation
40 points

The repository includes clear, accessible scripts used to generate both the raw and AI-ready datasets, and they were made available by the stated deadline. The code is well organized and sufficiently documented to support reproducibility and independent review.

20 points

Both the Raw and AI-Ready datasets were made available in the team’s private GitHub repository by the posted submission deadline, and were clearly labeled and accessible for review.

20 points
Proposal Quality - null Evaluation
30 points

The submission form is clear, descriptive, and informative. Responses provide sufficient detail to understand the approach, decisions, and outcomes, enabling effective evaluation without unnecessary ambiguity.

10 points

The submission demonstrates a high level of accuracy. The data is consistent, well-validated, and free from obvious errors, supporting reliable analysis and downstream use.

20 points
Utility and AI-Readiness - null Evaluation
30 points

The code is well-documented and informative. Structure, naming, and in-line comments clearly convey intent and logic, making the implementation easy to understand, review, and reuse.

20 points

The proposed use cases are thoughtful and well articulated. They demonstrate a strong understanding of the dataset, the AI-readiness steps applied, and how those enable meaningful applications across medicine, public health, and data science/AI contexts. The examples emphasize quality and depth over quantity, reflecting clear potential for real-world impact and researcher training.

10 points
Total Score
100 points

Challenge Materials

Challenge Materials