Particle size and morphology influence critical quality attributes (e.g., bioavailability, blend uniformity, dissolution profile, flowability) that impact the manufacturability, quality, safety and efficacy of solid dosage forms.

Traditional methods of analysis, such as laser diffraction, provide useful particle size information, but are unable to yield morphological information such as shape, roughness or agglomeration, that are critically important during the development, formulation and manufacturing of solid dosage forms.

Static image analysis (SIA) using microscopy precisely characterizes individual particles of dry powders, wet suspensions, granulations and particulates deposited on substrates to provide a comprehensive description of the morphological properties of a drug product formulation. By combining particle size measurements with particle morphology, SIA enhances product knowledge, while cross-validating traditional particle sizing techniques to improve manufacturing capability.

In the age of big data, data is a raw material of drug product formulation and production, and artificial intelligence (AI)/Machine Learning (ML) modeling of particulate matter is a predictive source for product properties and performance characteristics.

Learn from a panel of pharmaceutical industry leaders about the importance of particle analysis and advances in AI/ML in the formulation and manufacture of solid dosage forms to effect better health outcomes.

Who should attend:

• R&D
• Formulation development
• Manufacturing
• PAT
• QA/QC