# Biostatistics & Mathematical Oncology

> **NIH NIH P30** · BECKMAN RESEARCH INSTITUTE/CITY OF HOPE · 2023 · $68,161

## Abstract

Abstract Shared Resource 03: Biostatistics & Mathematical Oncology (BMO-SR)
The overall objective of the City of Hope Comprehensive Cancer Center (COHCCC) is to foster and integrate
cancer research activities, thereby ensuring the successful forward and reverse translation of discoveries across
the translational science spectrum, including prevention, control, and population science research. To help fulfill
this objective, and maximize the impact of research activities, the Biostatistics and Mathematical Oncology
Shared Resource (BMO-SR) works collaboratively with all COHCCC Members to provide essential and
continuous biostatistical, mathematical, epidemiological, bioinformatics, and computational biology support, with
tailored guidance given to each program/project.
Specific Aims of the BMOC-SR:
Aim 1. (Design and Analysis): Provide biostatistical, mathematical modeling, and computational biology
 expertise to enhance research activities.
Aim 2. (Consultation/Collaboration (2A) and Training/Service (2B)): Provide consultation, collaboration,
 training, and regulatory support service to facilitate the advancement of cancer research and
 novel therapeutics.
The BMO-SR, comprised of 25 faculty/staff, provides COHCCC Members (e.g., basic scientists, clinical
investigators, behavioral scientists, epidemiologists involved in cancer research) with access to a group of
specialized biostatisticians, mathematicians, and computational biologists who collectively possess a diverse set
of skills and expertise. Access to and collaborations with BMO-SR faculty are facilitated by: i) BMO-SR alignment
with the disease/modality research team organizational structure and ii) educational, training and mentorship
activities available to COHCCC Members (e.g., courses, virtual and walk-in BMO-SR clinics, statistical
workshops, and seminars). The overall objective of BMO-SR is to ensure that pre-clinical studies, basic science
experiments, clinical trials, mathematical/machine learning models, and observational/population studies are:
i) designed in an efficient and rigorous manner, ii) that high-quality data are collected, and iii) that unbiased data
analysis methods are employed, such that the reported results are valid, robust, and reproducible.
Members Utilization by %Revenue 2017–21: 98.3 Total (3.1 MCBC, 13.6 DCT, 27.5 CI, 50.4 HM, 3.7 CCPS)
Publications by Members: 178, 37 with Impact Factor >10
Grants Supported: 72 Total (2 ACS, 9 CIRM, 5 DoD, 2 LLS, 41 NCI of 49 NIH (33R01, 1U01))

## Key facts

- **NIH application ID:** 10628587
- **Project number:** 2P30CA033572-40
- **Recipient organization:** BECKMAN RESEARCH INSTITUTE/CITY OF HOPE
- **Principal Investigator:** Joycelynne M. Palmer
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $68,161
- **Award type:** 2
- **Project period:** 1997-08-01 → 2027-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10628587

## Citation

> US National Institutes of Health, RePORTER application 10628587, Biostatistics & Mathematical Oncology (2P30CA033572-40). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10628587. Licensed CC0.

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