Fast-track to a solid dispersion formulation using multi-way analysis of complex interactions.

Area of Science:

• Pharmaceutical Sciences
• Materials Science
• Chemometrics

Background:

• Physical stability of solid dispersions is crucial and influenced by complex interactions.
• Traditional ANalysis Of VAriance (ANOVA) models, while useful in Quality by Design (QbD), often present interpretation challenges due to significant higher-order interaction terms.

Purpose of the Study:

• To propose the GEneralized Multiplicative ANOVA (GEMANOVA) model as a more interpretable alternative to traditional ANOVA for analyzing solid dispersion physical stability.
• To demonstrate the advantages of GEMANOVA in handling complex multivariate data and improving model understandability.

Main Methods:

• Application of the GEMANOVA model to two complex multivariate datasets.
• Data generated from monitoring solid dispersion physical stability using image analysis and X-ray powder diffraction (XRPD).
• Comparison of GEMANOVA model interpretability and functionality against traditional additive ANOVA models.

Main Results:

• The GEMANOVA model provided a more interpretable and understandable analysis compared to the additive ANOVA model.
• GEMANOVA successfully handled complex multivariate responses, including entire spectral datasets.
• Demonstrated advantages in model uniqueness and curve resolution capabilities.

Conclusions:

• GEMANOVA offers a powerful and user-friendly alternative for analyzing complex multivariate data in pharmaceutical stability studies.
• The model enhances the understanding of factors influencing solid dispersion physical stability, supporting QbD principles.
• GEMANOVA's ability to incorporate multivariate responses and provide unique solutions makes it valuable for advanced chemometric analysis.