# Biostatistics Core

> **NIH NIH P01** · UNIVERSITY OF MINNESOTA · 2020 · $164,903

## Abstract

The primary objective of the Biostatistics Core is to contribute to the science and operation of the program 
project by participating fully in its activities as it has for the preparation of this application. This includes 
assistance and direction in experimental design, quality control, data collection and management, and 
statistical data analysis through consultation and collaboration. The team that helps prepare the application 
and will provide biostatistical supports for this program project consists of the following statisticians from the 
University of Minnesota and the Masonic Cancer Center: Chap Le (Core Director), Xianghua Luo (core Co- 
Director), Todd DeFor, and Yen-Yi Ho, an expert in Biostatistics and in Computational Biology. For the A1 
revised application, Dr. Koopmeiners has been added for his expertise in trial monitoring and adaptive design. 
This team is strengthened with the addition of the team from Tao Wang, a statistical geneticist from the 
Medical College of Wisconsin and CIBMTR. Dr. Wang will contribute to provide statistical supports for Projects 
1 and 3. The assignment of biostatistician support is logical and based on whether the data is collected and 
stored at the University of Minnesota or transplant data through the National Marrow Donor Program and the 
CIBMTR at the Medical College of Wisconsin.

## Key facts

- **NIH application ID:** 9905396
- **Project number:** 5P01CA111412-15
- **Recipient organization:** UNIVERSITY OF MINNESOTA
- **Principal Investigator:** CHAP T. LE
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $164,903
- **Award type:** 5
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9905396

## Citation

> US National Institutes of Health, RePORTER application 9905396, Biostatistics Core (5P01CA111412-15). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/9905396. Licensed CC0.

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