# Developing Data-Driven Cancer Researchers

> **NIH NIH T32** · UNIVERSITY OF WASHINGTON · 2021 · $412,931

## Abstract

Despite decades of research effort directed towards understanding the basic biology, etiology, prevention, and
means of treatment of malignancy, cancer remains one of the most serious health problems for the US
population, and is increasingly a global problem with over 14 million new cases of cancer and over 8 million
cancer deaths occur every year. Addressing the burden of cancer in the US and worldwide depends on
development of a cadre of population-oriented quantitative scientists with skills and knowledge to excel in an
increasingly data-rich world. The explosion of biomedical big data has dramatically and irrevocably changed
the landscape of cancer research. From molecular investigations studying genomic drivers of cancer to
population studies tracking health behaviors and utilization, new data resources are creating unprecedented
opportunities to solve the many unanswered questions about cancer. Optimizing the use of these resources
and many other
complex data—from `omics to administrative databases—
will require, in addition to the
standard “tools of the trade” garnered through training in the traditional quantitative disciplines of epidemiology
and biostatistics, a deep understanding of different types of data and how they are generated,
proficiency in
data management and visualization, and knowledge of statistical and machine learning approaches for data
analytics.
To prepare junior scientists to address the cancer research needs of a data-rich 21st century, we
propose to continue our 4 decade old training program for University of Washington (UW) pre-doctoral
students and post-doctoral fellows by focusing on “Developing Data-Driven Cancer Researchers.” Six pre-
doctoral and three postdoctoral positions will be filled from established, highly-ranked academic programs in
the UW Departments of Epidemiology, Biostatistics, Health Services, Health Metrics as well as interdisciplinary
programs such as Nutritional Sciences, Public Health Genetics, and Pharmaceutical Outcomes Research and
Policy. Through interdisciplinary didactic and practical experiences, trainees will learn to approach decisions
about cancer research strategies from the perspective of the strengths, weaknesses, value, and key analytic
features of different types of big data e.g., `omics, clinical, survey, social network, and personal wearable
technology-derived health metrics. Features of the training program will include: 1) existing UW courses (such
as “Cancer: Epidemiology and Biology,” “Biological Basis of Neoplasia,” “Advanced Health Services Research
Methods I: Large Public Databases: Big Data,” “Machine Learning for Biomedical and Public Health Big Data”);
2) a new, interactive “The Data of Cancer Research” seminar focused on the generation of cancer data; and 3)
completion of a “Big Data practicum” research exercise that build proficiency in working with cancer data.
Thus, the proposed training program will meld extant educational elements with original components un...

## Key facts

- **NIH application ID:** 10204714
- **Project number:** 5T32CA009168-44
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** RUTH D ETZIONI
- **Activity code:** T32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $412,931
- **Award type:** 5
- **Project period:** 1980-07-05 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10204714

## Citation

> US National Institutes of Health, RePORTER application 10204714, Developing Data-Driven Cancer Researchers (5T32CA009168-44). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10204714. Licensed CC0.

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