# Developing PBPK-model based mechanistic IVIVC for PLGA implants

> **NIH FDA U01** · UNIVERSITY OF TEXAS AT AUSTIN · 2024 · $299,364

## Abstract

There is an immediate need to understand the critical formulation parameters that may affect product
performance in vitro and in vivo, with a goal of developing IVIVCs for long-acting injectables. In this proposal,
we will develop IVIVCs for a long-acting PLGA-based solid implant using a physiologically based
pharmacokinetic (PBPK) modeling approach. PBPK modeling “provides a unique opportunity to understand how
the physicochemical properties of drug molecules/polymer, implant specific properties, critical formulation
attributes, and physiology, among other things, influence the in vivo release mechanisms of LAI drug products
and their disposition characteristics. Successful execution of the project will entail (1) developing a bio-predictive
in-vitro release testing method and determining how critical formulation and physicochemical properties impact
the in-vitro release of PLGA-based buprenorphine implants; and (2) using a bottom-up PBPK approach to build
IVIVCs that predict in-vivo PK profiles of PLGA-based buprenorphine implants from in-vitro data.

## Key facts

- **NIH application ID:** 11063705
- **Project number:** 1U01FD008303-01
- **Recipient organization:** UNIVERSITY OF TEXAS AT AUSTIN
- **Principal Investigator:** MING HU
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** FDA
- **Fiscal year:** 2024
- **Award amount:** $299,364
- **Award type:** 1
- **Project period:** 2024-09-01 → 2027-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11063705

## Citation

> US National Institutes of Health, RePORTER application 11063705, Developing PBPK-model based mechanistic IVIVC for PLGA implants (1U01FD008303-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/11063705. Licensed CC0.

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