# Core 01 - Information Technology and Systems Integration

> **NIH NIH P01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2021 · $328,330

## Abstract

This Program Project comprises four individual projects, which will: implement evidence-based sequential 
multiple treatment assignment strategies for patients predicted to have insufficient response to their initial 
neoadjuvant targeted and/or chemotherapy, (Project 1); qualify non-invasive imaging methods as early markers 
of non-response (Project 2); characterize the biology of non-responders to inform treatment selection (Project 3); 
and develop a portfolio of agents and decision tools for treatment re-assignment matched to biology of non- 
responding tumors (Project 4). The overarching goal of the Information Technology (IT) and Systems Integration 
Core is to develop an informatics infrastructure for the storage, integration and dashboard visualization of clinical, 
molecular and imaging data collected within the proposed I-SPY 2+ Program Project framework. Specifically, we 
will review and leverage the existing I-SPY 2 data infrastructure to design and implement a functional user 
interface that will enable role-based access and integrated visualization of data within and across projects with 
the I-SPY 2+ Program Project framework. 
This dashboard visualization will be extensible and capable of providing relevant data summaries and reports in 
support of all Projects in the Program. In addition, the dashboard will provide flexible integration of algorithms 
from other environments such as R code generated by the Bioinformatics and Statistics Core for longitudinal 
modeling of non-response based on imaging (Project 2) and molecular biomarkers (Project 3), and will allow for 
visualization of predictive modeling results of breast cancer data within and across project teams within the I-SPY 
2+ Program Project Framework via secure, role-based access. Integration of tools to report patient adverse event 
and quality of life will reduce the time spent extracting information manually from disparate sources, reduce 
errors, and potentially allow real-time monitoring. Collectively, the capabilities enabled by the data visualization 
dashboard will be a critical component towards achieving the overall Program Project goal of building and 
implementing robust, evidence-based decision algorithms to enable treatment to be adapted for individual 
women with high risk breast cancer.

## Key facts

- **NIH application ID:** 10249159
- **Project number:** 5P01CA210961-05
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Adam Asare
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $328,330
- **Award type:** 5
- **Project period:** 2017-09-08 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10249159

## Citation

> US National Institutes of Health, RePORTER application 10249159, Core 01 - Information Technology and Systems Integration (5P01CA210961-05). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10249159. Licensed CC0.

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