# Smokescreen Translational (TL) Analysis Platform

> **NIH NIH R44** · BIOREALM · 2020 · $138,859

## Abstract

Project Summary
Tobacco-attributable disease remains the largest potentially modifiable cause of mortality. Strategies to reduce
smoking prevalence include developing more effective smoking cessation treatments. Nicotine metabolism
and dependence are predictors of smoking behaviors, including response to smoking cessation treatments.
The goal of this Phase II project is to develop prediction models of nicotine metabolism, nicotine dependence
and smoking cessation from clinical and genomic data. An optimized set of models will be implemented in
the “Smokescreen®Translational (TL) Analysis Platform”, and applied to clinical cohorts of treatment-seeking
smokers.
 We have previously designed Smokescreen®GTA, a genome-wide array that deeply captures variation in
over 1,000 addiction genes, including the most important loci for nicotine metabolism and nicotine dependence.
We have identified multiple metabolic and regulatory genes, that with relatively few markers, can predict an
individual's nicotine metabolic activity. We will use existing cohorts and a clinical treatment trial of smokers
to discover and test integrated models with the goal of providing estimates of nicotine metabolism, nicotine
dependence and cessation probability. These models will incorporate ancestry, clinical, genomic and social vari-
ables to maximize prediction of smoking cessation. We will develop a compact laboratory assay for genotyping
DNA samples with specific markers and software to analyze clinical and genomic data. Smokescreen®TL will
be validated in smokers in clinical care. The results will be delivered in flexible reporting formats. Ultimately,
Smokescreen®TL will be available for use by health care providers interested in helping treatment seeking
smokers quit.

## Key facts

- **NIH application ID:** 9851043
- **Project number:** 3R44AA027675-03S1
- **Recipient organization:** BIOREALM
- **Principal Investigator:** ANDREW W BERGEN
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $138,859
- **Award type:** 3
- **Project period:** 2016-06-01 → 2021-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9851043

## Citation

> US National Institutes of Health, RePORTER application 9851043, Smokescreen Translational (TL) Analysis Platform (3R44AA027675-03S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9851043. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*