# University of Colorado Cancer Center Support Grant

> **NIH NIH P30** · UNIVERSITY OF COLORADO DENVER · 2020 · $294,029

## Abstract

Project Summary / Abstract
The conduct of clinical research is essential to improving the treatment options of cancer patients. Many
treatment protocols are complex and prescribed using electronic health record systems where the treatment
protocol orders have been built previously. The work of building these treatment protocols is a complex
process involving many steps, substantial time, and can be the limiting step in opening clinical trials. Multi-arm
and protocol amendments can be particularly time consuming to build. Unfortunately for multi-site clinical trials,
this build process is duplicated at each site representing a lack of efficiency in the overall clinical research
system. This project seeks to bring together a consortium of NCI-designated cancer centers who are leaders
in both the conduct of clinical research and in clinical informatics, along with coordination with EHR companies,
to establish standardized build conventions, develop means to make clinical trial protocol builds interoperable
across sites, and ultimately to make the conduct of clinical research substantially more efficient. In this way
we will be able to better leverage the power of clinical informatics systems to accelerate the conduct of clinical
cancer research.

## Key facts

- **NIH application ID:** 10225725
- **Project number:** 3P30CA046934-32S6
- **Recipient organization:** UNIVERSITY OF COLORADO DENVER
- **Principal Investigator:** RICHARD D SCHULICK
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $294,029
- **Award type:** 3
- **Project period:** 1997-04-04 → 2022-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10225725

## Citation

> US National Institutes of Health, RePORTER application 10225725, University of Colorado Cancer Center Support Grant (3P30CA046934-32S6). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10225725. Licensed CC0.

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