Related Experiment Video
Updated: Aug 7, 2025

05:37
Intravitreous Injection for Establishing Ocular Diseases Model
Published on: October 1, 2007
36.9K
Preclinical modeling of intravitreal suspensions
1Small Molecule Pharmaceutical Sciences, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA.
International Journal of Pharmaceutics
|March 10, 2023
Summary
This study introduces a new model to predict drug release from intravitreal suspension formulations. This tool helps preclinical developers decide between simple suspensions and complex depots for small molecule therapies.
Area of Science:
- Ophthalmology
- Pharmaceutical Sciences
- Drug Delivery
Background:
- Developing intravitreal small molecule therapies faces challenges, including the need for complex polymer depot formulations.
- Complex formulations require significant time and material investment, often unavailable during early preclinical development.
Purpose of the Study:
- To present a diffusion-limited pseudo-steady state model for predicting drug release from intravitreal suspension formulations.
- To aid preclinical formulators in determining the necessity of complex formulations versus simple suspensions.
Main Methods:
- A diffusion-limited pseudo-steady state model was developed and applied.
- The model predicted the intravitreal performance of triamcinolone acetonide and GNE-947 in rabbit eyes.
- Model predictions were also made for a marketed formulation of triamcinolone acetonide in humans.
Main Results:
- The model provides predictions for drug release kinetics from intravitreal suspensions.
- It allows for evaluation of different molecules and dose levels in preclinical models.
- The model can forecast the performance of established formulations in human subjects.
Conclusions:
- The presented model offers a valuable tool for preclinical drug formulation development for intravitreal therapies.
- It can guide decisions regarding formulation complexity, potentially saving time and resources.
- This approach supports more confident formulation selection for supporting study designs.

