An investigation into the rheology of pharmaceutical inter-granular material bridges at high shear rates.

PURPOSE: This study was undertaken to investigate the rheological properties of inter-granular material bridges on the nano-scale when strained at high shear rates. MATERIALS AND METHODS: Atomic force microscopy (AFM) was used as a rheometer to measure the viscoelasticity of inter-granular material bridges for lactose:PVP K29/32 and lactose:PVP K90 granules, produced by wet granulation. RESULTS: The loss tangent (tan delta) and both the storage (G') and loss shear moduli (G'') of inter-granular material bridges were measured as a function of the probe-sample separation distance, oscillation frequency and relative humidity (RH). As the probe was withdrawn from the granule surface tan delta initially increased rapidly from zero to a plateau phase. G'' became increasingly dominant as the bridge was further extended and eventually exceeded G'. At high RH, capillary forces were foremost at bridge rupture, whereas at low RH elastic forces dominated. The effect of increasing frequency was to increase the effective elasticity of the bridge at high RH. CONCLUSIONS: AFM has been employed as a rheometer to investigate the nano-scale rheology of inter-granular material bridges. This novel method may be used to obtain a fundamental understanding how different binders, granulated with different diluent fillers, behave at high shear rates.

A decision-support tool for the formulation of orally active, poorly soluble compounds.

Physicochemical data for a set of potentially poorly soluble compounds was analysed in relation to suitable formulations for these compounds. Physical chemistry was found to be a key determinant of formulation class expressed in terms of conventional, solid dispersion, lipidic/surfactant, and crystalline nanoparticle systems. This relationship was used to build a decision-support tool aimed to guide formulation selection for poorly soluble compounds during product development. Tool components included a user interface, a database of compound cases together with known formulations, and predictive modules based on statistics, decision trees, and case-based reasoning. The tool was tested and exhibited significant and consistent predictive ability across testing conditions. This type of tool has the potential to improve the efficiency and predictability of the formulation development process.

Predictive and correlative techniques for the design, optimisation and manufacture of solid dosage forms.

There is much interest in predicting the properties of pharmaceutical dosage forms from the properties of the raw materials they contain. Achieving this with reasonable accuracy would aid the faster development and manufacture of dosage forms. A variety of approaches to prediction or correlation of properties are reviewed. These approaches have variable accuracy, with no single technique yet able to provide an accurate prediction of the overall properties of the dosage form. However, there have been some successes in predicting trends within a formulation series based on the physicochemical and mechanical properties of raw materials, predicting process scale-up through mechanical characterisation of materials and predicting product characteristics by process monitoring. Advances in information technology have increased predictive capability and accuracy by facilitating the analysis of complex multivariate data, mapping formulation characteristics and capturing past knowledge and experience.