Towards the understanding and prediction of material changes during micronisation using atomic force microscopy.

Area of Science:

• Materials Science
• Pharmaceutical Science
• Physical Chemistry

Background:

• Carbamazepine exists in multiple polymorphic forms, each with distinct physical and chemical properties.
• Understanding the mechanical properties and surface energy of these polymorphs is crucial for controlling their behavior during pharmaceutical processing, particularly micronization.
• Atomic Force Microscopy (AFM) offers nanoscale insights into material properties relevant to powder processing.

Purpose of the Study:

• To investigate the relationship between the mechanical properties (hardness, Young's modulus) and surface energy of carbamazepine polymorphs (Forms I, II, III).
• To correlate these nanoscale properties with the behavior of carbamazepine during micronization.
• To assess the potential of AFM-based measurements for predicting micronization outcomes.

Main Methods:

• Preparation and confirmation of carbamazepine Forms I, II, and III using X-ray powder diffraction (XRPD).
• Atomic Force Microscopy (AFM) measurements of indentation hardness, Young's modulus, and surface energy on the starting materials.
• Measurement of surface energy immediately after micronization and after four weeks of storage.

Main Results:

• Carbamazepine polymorphs were successfully ranked based on Young's modulus and hardness.
• Micronization led to an increase in surface energy for all forms, with varying degrees of relaxation upon storage.
• Form I exhibited a narrower particle size distribution post-micronization, suggesting more effective particle size reduction.
• A significant correlation was found between the hardness/Young's modulus ratio and micronization behavior (particle size reduction, surface energy changes).

Conclusions:

• The mechanical properties, particularly the hardness/Young's modulus ratio, are predictive of carbamazepine polymorphs' micronization behavior.
• AFM-based nanoscale characterization provides valuable insights into material properties influencing micronization.
• This approach enhances understanding of material behavior during micronization and holds potential for process optimization.