# Core 1: Information Technology and Systems Integration

> **NIH NIH P01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2023 · $499,916

## Abstract

The adaptive, platform nature of the I-SPY trials places a number of additional requirements on the collection of clinical
and laboratory data and in the management and portability of the resulting data. In particular, the adaptive randomization
engine relies upon near real-time access to MRI and pathology assessments. However, as I-SPY and the field have grown
and evolved, so too have the requirements of the underlying data systems and architecture, particularly for the advanced
designs of I-SPY2.2. The Information Technology and Systems Integration core seeks not only to provide high quality
services to the projects, but also to engage in the development and validation of innovative tools that further the program
project’s ability to meet and or exceed their research goals. In the past grant period, the core has also exceeded the aims
laid out in the original proposal. We built out and deployed a robust electronic data capture (EDC) platform and
successfully migrated 10 years of trial data into the new system. In a pilot implementation, we demonstrated the
OneSource system that seamlessly permits data to be pulled directly from electronic health records into study case report
forms (CRF), can improve data fidelity and timeliness of CRF completion, giving program project teams quicker access to
higher quality data. We architected a biomarker repository platform on Amazon Web Services (AWS) that is fully
integrated with Google Big Query and leverages the Institute for Systems Biology (ISB) biomarker management and
visualization platform [ProBE]. Finally, we implemented systems for the collection and management of electronic Patient
Reported Outcomes that have vastly improved completion rates for quality of life and adverse event reporting by program
project investigators.
The IT and Systems Integration Core will continue to provide functionality to the I-SPY2.2 trial in a number of ways. We
will continue implementing OneSource across the majority of the 32+ clinical sites and integrate additional data types
including pathology/immune multiplex, imaging, whole exome, ctDNA, RNA seq into our cloud repository. Over the
course of the proposed work, we will develop a resource for investigators so they can interactively view and query all the
various types data in an integrated fashion, and connect to external data sources such as TCGA, to allow comparisons
between I-SPY and other breast cancer cohorts. This repository will be enhanced by integrating machine learning,
contextual-level visualizations, and other external database tools.

## Key facts

- **NIH application ID:** 10628614
- **Project number:** 2P01CA210961-06A1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Adam Asare
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $499,916
- **Award type:** 2
- **Project period:** 2017-09-08 → 2028-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10628614

## Citation

> US National Institutes of Health, RePORTER application 10628614, Core 1: Information Technology and Systems Integration (2P01CA210961-06A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10628614. Licensed CC0.

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