# Core C - Integrated Quantitative Science (IQS)

> **NIH NIH P50** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2022 · $187,120

## Abstract

CORE C: ABSTRACT
The mission of the Integrated Quantitative Science (IQS) Core is to provide state-of-the-art data management,
study design, and statistical analysis support for the UNC Pancreatic Cancer SPORE translational research
projects. This centralized core will provide the technical skills for the statistical analysis of clinical, translational,
and multi-platform genomic data from individual research projects to provide a broad clinical and molecular
portrait of pancreatic cancer. Results from each project will inform the design and analysis of a future SMART
trial, which will involve state-of-the-art clinical trial design and machine learning methods to determine the best
sequence of treatments, tailored to individual patient-level characteristics. Complementary skills possessed by
the Core faculty will also lead to the application and development of (as needed) cutting-edge approaches for
cross-platform data integration and high-dimensional biomarker discovery to facilitate patient subtyping and
optimize clinical decision-making. This Core will provide appropriate input into design, management, and
analysis to ensure that SPORE investigators pursue the most promising lines of translational research.

## Key facts

- **NIH application ID:** 10334087
- **Project number:** 1P50CA257911-01A1
- **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL
- **Principal Investigator:** MICHAEL R KOSOROK
- **Activity code:** P50 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $187,120
- **Award type:** 1
- **Project period:** 2022-09-16 → 2027-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10334087

## Citation

> US National Institutes of Health, RePORTER application 10334087, Core C - Integrated Quantitative Science (IQS) (1P50CA257911-01A1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10334087. Licensed CC0.

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