# A-STOR Cancer Clinical Trial Artificial Intelligence & Machine Learning Readiness

> **NIH NIH U10** · BRIGHAM AND WOMEN'S HOSPITAL · 2022 · $207,570

## Abstract

PROJECT SUMMARY
High-dimensional molecular profiling, including genomic sequencing and digital pathology, has revolutionized
our understanding of cancer and has led to the identification of multiple new targets and biomarkers. However,
barriers impede unlocking the full potential of these data because most ‘omic data generated from National
Cancer Institute’s National Clinical Trials Network (NCTN) clinical trials are decentralized, with data housed at a
variety of sites and analyses taking place locally. To overcome these barriers for Alliance NCTN cooperative
group trials, in 2020 we established A-STOR: Alliance Standardized Translational Omics Resource, a secure,
HIPAA-compliant centralized repository of raw, and processed genomic and pathology image data from Alliance
clinical trials, with standardized genomic data harmonization to facilitate cross-study analyses. In this proposal
(a supplement to the Alliance U10 grant), we aim to realize the potential of A-STOR for artificial intelligence
(AI)/machine learning (ML) modeling by rapidly expanding our existing infrastructure to: host data from over a
dozen existing or ongoing Alliance/NCTN clinical trials (Aim 1), optimize infrastructure for cloud-based AI/ML
analyses including engagement with and feedback from AI/ML applications (Aim 1-2), ensure FAIR principles in
developing a unified clinical and adverse event (AE) data dictionary to facilitate clinical data harmonization (Aim
2), and complete an already-approved pooled multi-modal ML-based predictor as a pilot study (Aim 3). The
impact of these aims will collectively capitalize on the expertise of Alliance A-STOR Co-Chairs Dr. Daniel Stover
(clinical informatics, genomics) and Dr. James Blachly (computational biology, computer science), to optimize
foundational infrastructure, clinical/AE harmonization to facilitate data reuse as part of AI/ML efforts, and cloud-
based AI/ML compute optimization for data generated through Alliance NCTN cancer clinical trials.

## Key facts

- **NIH application ID:** 10593808
- **Project number:** 3U10CA180821-09S4
- **Recipient organization:** BRIGHAM AND WOMEN'S HOSPITAL
- **Principal Investigator:** Suzanne George
- **Activity code:** U10 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $207,570
- **Award type:** 3
- **Project period:** 2014-04-17 → 2025-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10593808

## Citation

> US National Institutes of Health, RePORTER application 10593808, A-STOR Cancer Clinical Trial Artificial Intelligence & Machine Learning Readiness (3U10CA180821-09S4). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10593808. Licensed CC0.

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