# Stat4Onc Annual Symposium

> **NIH NIH R13** · STANFORD UNIVERSITY · 2024 · $5,000

## Abstract

Project Summary/Abstract
Cancer is the 2nd leading cause of death in US. Statistical designs and data analytics approaches
are instrumental in recent development of more effective treatments for cancer. While successes
like the I-SPY2 trial highlight the advancement, most oncology trials do not fully utilize powerful
statistical innovations and there remains a lack of effective communications between oncologists
and statisticians. To address these issues, we propose the Stat4Onc symposium which provides
a unique platform for oncologists and statisticians to discuss and exchange ideas for pressing
issues in cancer clinical trials, disease diagnosis, patient care, and decision making for drug
development. This symposium will further drive innovations in statistical methodology and data
analytics dedicated for oncology research and translate these innovations to research practice. It
also provides a venue for trainees in oncology and statistics to learn inter-disciplinary
collaborations. The symposium will be rotated among the four participating universities in a five-
year funding period. The symposium is a three-day event, with first day of short courses relevant
to the theme of the year, and then a two-day single-track scientific program. The symposium is
inclusive, with respect to scientific expertise in oncology, statistics, regulatory and data sciences,
to their professional associations from academia (faculty, staff, and students), biopharma and
biotech industry, government agencies, and non-profit organizations, and to gender and ethnicity,
in particular for the inclusion of underrepresented minority groups. The symposium size will be
around 200 participants, allowing adequate and focused discussions. The symposium will be
single tracked to allow participants to be in all the sessions. Keynote talks and all the sessions
will have speakers from academic, government, and industry and with expertise in oncology and
statistics. Trainees in both oncology and statistics disciplines will be supported for attending the
symposium and offers opportunities to present in poster and mixer sessions. Symposium talks
will be published in JCO Precision Oncology and New England Journal of Statistics in Data
Science.

## Key facts

- **NIH application ID:** 10837013
- **Project number:** 5R13CA261077-04
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** YING LU
- **Activity code:** R13 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $5,000
- **Award type:** 5
- **Project period:** 2021-05-01 → 2026-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10837013

## Citation

> US National Institutes of Health, RePORTER application 10837013, Stat4Onc Annual Symposium (5R13CA261077-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10837013. Licensed CC0.

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