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Coherent anti-Stokes Raman Scattering CARS Microscopy Visualizes Pharmaceutical Tablets During Dissolution
Published on: July 4, 2014
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A novel approach for predicting the dissolution profiles of pharmaceutical tablets
Raphael Paus1, Elena Hart1, Yuanhui Ji1
1TU Dortmund, Department of Biochemical and Chemical Engineering, Laboratory of Thermodynamics, Emil-Figge Str. 70, D-44227 Dortmund, Germany.
Summary
This study modeled the dissolution profiles of naproxen (NAP) and trimethoprim (TMP) tablets. The PC-SAFT model accurately predicted drug dissolution under various conditions, aiding pharmaceutical development.
Area of Science:
- Pharmaceutical Sciences
- Physical Chemistry
- Chemical Engineering
Background:
- Understanding drug dissolution is crucial for predicting in vivo performance.
- Naproxen (NAP) and trimethoprim (TMP) are common active pharmaceutical ingredients (APIs) with varying physicochemical properties.
- Accurate dissolution modeling can optimize tablet formulation and manufacturing.
Purpose of the Study:
- To measure and model the intrinsic dissolution profiles and pH-dependent solubilities of NAP and TMP.
- To predict the dissolution profiles of NAP and TMP from cylindrical tablets under diverse conditions (pH, temperature, stirring speed).
- To validate a predictive model for drug dissolution based on intrinsic properties and surface area changes.
Main Methods:
- Measured intrinsic dissolution rates of NAP and TMP at various pH values.
- Determined dissolution profiles of NAP and TMP tablets across different temperatures, stirring speeds, and pH levels.
- Applied the chemical-potential-gradient model with perturbed-chain statistical associating fluid theory (PC-SAFT) for dissolution prediction.
Main Results:
- Intrinsic dissolution profiles and pH-dependent solubilities of NAP and TMP were characterized.
- Experimental dissolution data from cylindrical tablets were collected under varied conditions.
- The PC-SAFT model demonstrated good agreement between predicted and experimentally observed tablet dissolution profiles.
Conclusions:
- The PC-SAFT model effectively predicts drug dissolution behavior for NAP and TMP tablets.
- Accurate prediction of dissolution profiles is achievable by integrating intrinsic dissolution data and surface area reduction.
- This modeling approach provides a valuable tool for pharmaceutical formulation and process optimization.
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