# Analytics, trial methods and modeling

> **NIH NIH U54** · STANFORD UNIVERSITY · 2020 · $214,225

## Abstract

A common criticism of precision medicine is that it may offer treatment benefits to individuals, but fail to 
address broader population disparities in health; precision medicine may even exacerbate health disparities if 
disadvantaged populations have disproportionately low utilization of novel screening and treatment 
technologies.1,2 In response to this criticism, the charge of the Analytics and Modeling (A&M) Core is to bridge 
the divide between individual-level precision medicine and population-level health disparities by leveraging two 
major strengths at Stanford University: (i) expertise in using omics data at the individual level to design and 
evaluate disease screening and treatment strategies, and (ii) expertise in computer modeling methods 
collectively referred to as “systems science”, which integrate 
data from individuals (omics data, clinical data, 
behavioral survey data) with data on key contextual factors (social and economic barriers to healthcare access, 
cultural factors, environmental factors, health-related policies) to study the distribution of health in the 
population. 
Leveraging Stanford's unique expertise in these areas, the A&M core will pursue the following 
objectives: (1) to integrate data from the Native American arthritis and multi-ethnic breast cancer R01 projects 
into problem–specific systems science models to perform leverage point analysis, which involves integrating 
individual-level omics data with clinical, biological, and contextual data to identify which precision medicine 
interventions are best for improving individual patient outcomes, population-level health disparities, or both;5,6 
(2) conduct cost-effectiveness analyses for the Latino obesity R01 project, by studying the cost-effectiveness 
of integrating personalized –omics profiling (iPOP) into a multi-component, multi-setting intervention to reduce 
weight gain among Latino youth; and (3) serve as a center for excellence for the deployment of innovative data 
integration, analysis and modeling strategies to bridge the divide between precision medicine and population 
health. Our models will integrate multi-level data on omic risk variations within each studied population, social 
and cultural barriers that influence screening and treatment, screening performance, patient responses to test 
results, clinical gains to therapeutic efficacy from screening results, patient responses to suggested therapies, 
and patient outcomes from therapy. By integrating these diverse data into simulation models that link these 
individual-level factors to population disparities in disease risk and outcomes, we can identify the impact of 
altering key components – the levers – of patient outcomes and of population disparities, to inform the 
targeting and development of future precision medicine programs. Use systems science techniques, the A&M 
Core will create, validate, and implement models that identify how screening and treatment based on omics 
data can...

## Key facts

- **NIH application ID:** 9896672
- **Project number:** 5U54MD010724-05
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** SANJAY BASU
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $214,225
- **Award type:** 5
- **Project period:** — → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9896672

## Citation

> US National Institutes of Health, RePORTER application 9896672, Analytics, trial methods and modeling (5U54MD010724-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9896672. Licensed CC0.

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