Oligonucleotide Toxicity (OligoTox) Open Data Challenge
NIH Challenges' Oligonucleotide Toxicity (OligoTox) Open Data Challenge funds open, human cell-based datasets to advance AI-driven prediction of oligonucleotide toxicity.
Funder: NIH Challenges
Due Dates: February 28, 2026 (Phase 1 Submission End) | December 31, 2026 (Phase 2 Submission End)
Funding Amounts: Total prize purse: $500,000 across both phases; Phase 1: up to $100,000 (up to $10,000 each for 10 winners); Phase 2: up to $400,000 (up to $100,000 each for 2 winners, up to $50,000 each for 4 runners-up)
Summary: Supports creation and open dissemination of high-quality human cell-based datasets to advance AI-driven prediction of oligonucleotide toxicity.
Key Information: Non-U.S. citizens/residents may participate but are not eligible for cash prizes; open datasets must be made publicly available.
Description
This two-phase prize competition seeks to catalyze the generation and public sharing of high-quality datasets from in vitro human-based systems to predict oligonucleotide toxicity. The initiative aims to reduce reliance on animal testing, promote the development of advanced in silico (AI/ML-driven) models for toxicity prediction, and foster transparency in preclinical drug safety assessment.
The challenge is organized by the NIH National Center for Advancing Translational Sciences (NCATS) under the NIH Challenges program. Participants are incentivized to propose, generate, and openly disseminate datasets that address key toxicities relevant to oligonucleotide therapeutics, such as hepatotoxicity, kidney toxicity, and immunotoxicity, among others.
The competition unfolds in two phases:
- Phase 1 (Ideation): Participants propose valuable datasets to be generated, focusing on scientific value, experimental approach, data management, and relevance for predictive modeling.
- Phase 2 (Data Generation): Participants generate and release open, AI-ready datasets based on their proposals or new ideas, with emphasis on public accessibility, rigorous methodology, and broad utility for the scientific community.
