Development of polyvinylpyrrolidone-based spray-dried solid dispersions using response surface model and ensemble
Ashwinkumar D Patel1, Anjali Agrawal2, Rutesh H Dave1
1Division of Pharmaceutical Sciences, Arnold and Marie Schwartz College of Pharmacy and Health Sciences, Long Island University, Brooklyn, New York 11201.
Journal of Pharmaceutical Sciences
|April 10, 2013
Summary
A predictive model was developed for spray drying processes using polyvinylpyrrolidone (PVP) to forecast quality attributes of solid dispersions (SDs). This approach aids formulation scientists in optimizing spray-dried SD development, saving time and resources.
Area of Science:
- Pharmaceutical Technology
- Process Engineering
- Materials Science
Background:
- Spray drying is a crucial technique for producing solid dispersions (SDs).
- Predicting quality attributes of SDs during spray drying is challenging.
- Polyvinylpyrrolidone (PVP)-K29/32 serves as a model excipient for process development.
Purpose of the Study:
- To develop and validate predictive models for spray drying processes.
- To forecast key quality attributes of binary solid dispersions (SDs).
- To evaluate the impact of process parameters on SD quality.
Main Methods:
- Utilized polyvinylpyrrolidone (PVP)-K29/32 as a placebo formulation.
- Employed response surface modeling and artificial neural networks (ANNs).
- Analyzed powders using DSC, TGA, XRD, PLM, and particle size analysis.
Main Results:
- Both response surface and ANN models demonstrated significant correlation with experimental data.
- Models accurately predicted process yield, outlet temperature, and particle size.
- Validation datasets confirmed the reliable predictivity of both developed models.
Conclusions:
- The developed models offer a reliable tool for spray drying process design.
- This methodology can optimize the development of spray-dried SDs.
- The approach helps save time, drug substance, and resources in formulation development.
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