# Addressing health disparities through a quantitative physiological database and precision systems modeling

> **NIH NIH R41** · PRECISION QUANTOMICS INC · 2024 · $294,450

## Abstract

ABSTRACT
PROJECT SUMMARY In the realm of drug development and clinical evaluation, clinical data from children, women, specific genetic groups, elderly individuals, and disease-specific groups is often sparce, and can result in negative health outcomes such as disproportionate occurrences of unforeseen adverse events and reduced efficacy of already approved drugs. In the absence of wide-spread participation in clinical studies, a recent paradigm shift at the FDA allows for new drug application submissions to utilize physiologically-based pharmacokinetic (PBPK) modeling to describe the pharmacokinetic properties of a drug in specific populations. Although PBPK modeling is promising, two fundamental challenges make these models less applicable to specific patient populations. First, the physiological data within current PBPK modeling tools have been derived from a narrow reference population. These inputs also include the levels of drug metabolizing enzymes, transporters, and receptors (drug target proteins, DTPs). Second, the in vitro reagents used to model drug-specific data are not characterized across widely defined genetic populations, thus limiting the accuracy of in vitro in vivo extrapolation (IVIVE) predictors. In Phase I of our proposal, Precision Quantomics Inc. aims to fill these critical knowledge gaps, first through the development of the population Drug Target Protein Database (popDTPdb), a physiological protein abundance database and analytics platform, and second, through the creation of meticulously characterized population-specific in vitro reagents (PQ-ivR). Together, these advancements will enable the generation of key data and reagents for PBPK models that will more accurately predict drug pharmacokinetics and tissue drug concentration as surrogates of drug safety and efficacy across all populations. The successful completion of Phase I will serve as a proof of concept, setting a strong foundation for an expanded Phase II, where we will i) expand the popDTPdb to include other tissues, populations, and animal models for PBPK modeling, ii) develop custom reagents with precise scaling factors for pharmaceutical and biotech companies, and iii) validate commercially available reagents with precise scaling factors for drug testing. In conclusion, our technology has potential to advance drug development practices, elevate predictive accuracy, and ultimately contribute to improved patient care across all US patient populations.

## Key facts

- **NIH application ID:** 10923431
- **Project number:** 1R41MD019585-01
- **Recipient organization:** PRECISION QUANTOMICS INC
- **Principal Investigator:** Bhagwat Prasad
- **Activity code:** R41 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $294,450
- **Award type:** 1
- **Project period:** 2024-08-11 → 2026-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10923431

## Citation

> US National Institutes of Health, RePORTER application 10923431, Addressing health disparities through a quantitative physiological database and precision systems modeling (1R41MD019585-01). Retrieved via AI Analytics 2026-06-12 from https://api.ai-analytics.org/grant/nih/10923431. Licensed CC0.

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