Mathematical models of dissolution testing: Challenges and opportunities toward real-time release testing.

Area of Science:

• Pharmaceutical Manufacturing
• Process Analytical Technology (PAT)

Background:

• Real-time release testing (RTRt) is crucial for efficient pharmaceutical manufacturing, especially with continuous manufacturing.
• Current RTRt often relies on data-driven models, which can be computationally fast but lack interpretability.
• Mechanistic models offer broader applicability and interpretability for dissolution testing.

Purpose of the Study:

• To explore the potential benefits and challenges of applying mechanistic models for RTRt of solid dosage forms.
• To provide a comprehensive literature review on mechanistic dissolution models and RTRt.

Main Methods:

• Comprehensive literature review of mechanistic dissolution models and RTRt.
• Analysis of benefits and challenges of mechanistic models compared to data-driven models.
• Discussion on computational time requirements for mechanistic model implementation.

Main Results:

• Mechanistic models require less experimental data, reducing time and cost for RTRt development.
• Interpretability and broader applicability are key advantages of mechanistic models.
• Computational efficiency is a critical factor for implementing mechanistic models in RTRt.

Conclusions:

• Mechanistic models present opportunities for robust and reliable RTRt in pharmaceutical manufacturing.
• Addressing computational time through simplified models or surrogate modeling is essential for practical RTRt implementation.
• Further research into mechanistic models can enhance product quality assurance without destructive testing.