Modeling Pharmaceutical Powder-Flow Performance Using Particle-Size Distribution Data

The authors present a simple and material-sparing approach for estimating the powder-flow performance of previously uncharacterized single-component bulk powders when only particle-size distribution data are available.
Mar 02, 2009

Pharmaceutical powders can be very different in their particle chemistry, morphology, and size, which can significantly affect their bulk-flow properties. Free-flowing powders are desirable to enable robust powder processing operations such as bin filling, hopper discharge, and capsule and die filling. It is well established that particle size (mean and distribution) is one of the most significant factors that affects the flow behavior of powders (1, 2). Small particles (<20 μm) have a relatively high surface area to volume ratio, causing interparticulate attractive forces to dominate and resist bulk flow when a shear stress is applied. Larger particles (>100 μm) tend to roll or slide over one another when a shear stress is present and, thus, exhibit superior bulk flow properties compared with small particles. This is because gravity forces significantly exceed interparticle forces such as those caused by electrostatic or van der Waals interactions for particles in this size range. In addition, a broad particle-size distribution (PSD) with both large and small particles enables more efficient particle packing, which leads to an interlocking effect as the small particles fill in the gaps between the contact surfaces of larger particles. The absolute size and distribution of particles in a powder sample, therefore, collectively contribute to the sample's bulk powder-flow behavior.

The quantification of powder-flow properties with a small quantity of material (<20 g) is essential for material sparing and cost-saving predictive assessments. Amidon and Houghton remark that useful powder-flow evaluation tools should be reproducible, sensitive, yield meaningful results, and require small amounts of material (3). Because only small (expensive) quantities of powder are available during early dosage-form design and because the synthetic process may not be finalized, having a simple material-sparing screening tool that can rapidly evaluate the powder flow of these samples is attractive (3). Even with small-scale tools such as shear cells for the evaluation of powder-flow performance, however, it is desirable to predict powder-flow performance using less than 1 g material during prototype active pharmaceutical ingredient (API) or drug-product design.

Particle-size analysis tools such as laser diffraction can measure the PSD of less than 1 g of material. It is beneficial to prototype API and solid-dosage formulation design if the flow performance of powders can be predicted using particle-size data. This method offers a significant advantage to a material-sparing approach because bulk property measurements such as flow cannot be scaled down much below a few grams due to the fact that they are dominated by interparticle interactions.

The authors hypothesize that the relative powder-flow performance of a bulk powder sample is influenced by and can be predicted from its PSD. The objective of this investigation is to develop a quantitative empirical model for predicting an established single flow-performance parameter, the flow-function coefficient (FFC), from input PSD statistics. This model may then be used to predict the flow behavior of new powdered pharmaceutical materials.


Table I: Linear-regression data for measured versus predicted flow-function coefficient (FFC) values using the partial-least squares (PLS) model.
A proprietary database containing PSD and powder-flow data was queried for all powders containing PSD and FFC data. The query produced a representative sample of 185 pharmaceutical powders tested during a three-year period (see Table I). The volume mean diameter (VMD, D[4,3]) and FFC values ranged from 2 to 457 μm and 1.2 to 28.5, respectively. These are typical ranges for powdered bulk materials (4).