Prediction of tablet weight variability in continuous manufacturing.

This paper provides a method for prediction of weight variability of tablets made in rotary tablet presses as a function of material attributes and processing parameters. The goal was to be able to predict whether or not a formulation is suitable for direct compaction continuous manufacturing using the tablet weight variability as a criterion. The work focused on identifying the significant factors affecting the weight variability in tablets, within the design space studied. A wide range of blends with different powder properties were prepared. It was shown that among powder properties, cohesion, bulk density, and particle size were the most significant and sufficient material attributes to explain tablet weight variability. A response surface model was built and validated with three different blends. The model is not formulation dependent and can be expanded to include other blend properties or processing parameters effects.

Modeling of Semicontinuous Fluid Bed Drying of Pharmaceutical Granules With Respect to Granule Size.

In the transition of the pharmaceutical industry from batchwise to continuous drug product manufacturing, the drying process has proven challenging to control and understand. In a semicontinuous fluid bed dryer, part of the ConsiGma™ wet granulation line, the aforementioned production methods converge. Previous research has shown that the evolution of moisture content of the material in this system shows strong variation in function of the granule size, making the accurate prediction of this pharmaceutical critical quality attribute a complex case. In this work, the evolution of moisture content of the material in the system is modeled by a bottom-up approach. A single granule drying kinetics model is used to predict the moisture content evolution of a batch of material of a heterogeneous particle size, where it is the first time that the single granule drying mechanism is validated for different granule sizes. The batch approach was validated when the continuous material inflow rate and filling time of the dryer cell are constant. The original single granule drying kinetics model has been extended to capture the granules' equilibrium moisture content. Finally, the influence of drying air temperature is captured well with a droplet energy balance for the granules.

Model development and prediction of particle size distribution, density and friability of a comilling operation in a continuous pharmaceutical manufacturing process.

The comilling process plays an important role in solid oral dosage manufacturing. In this process, the granulated products are comminuted to the required size distribution through collisions created from a rotating impeller. In addition to predicting particle size distribution, there is a need to predict other critical quality attributes (CQAs) such as bulk density and tapped density, as these impact tablet compaction behavior. A comprehensive modeling approach to predict the CQAs is needed to aid continuous process modeling in order to simulate interaction with the tablet press operation. In the current work, a full factorial experiment design is implemented to understand the influence of granule strength, impeller speed and residual moisture content on the CQAs. A population balance modeling approach is applied to predict milled particle size distribution and a partial least squares modeling approach is used to predict bulk and tapped density of the milled granule product. Good agreement between predicted and experimental CQAs is achieved. An R2 value of 0.9787 and 0.7633 is obtained when fitting the mean particle diameters of the milled product and the time required to mill the granulated material respectively.

Environmental sustainability assessments of pharmaceuticals: an emerging need for simplification in life cycle assessments.

The pharmaceutical and fine chemical industries are eager to strive toward innovative products and technologies. This study first derives hotspots in resource consumption of 2839 Basic Operations in 40 Active Pharmaceutical Ingredient synthesis steps through Exergetic Life Cycle Assessment (ELCA). Second, since companies are increasingly obliged to quantify the environmental sustainability of their products, two alternative ways of simplifying (E)LCA are discussed. The usage of averaged product group values (R(2) = 3.40 × 10(-30)) is compared with multiple linear regression models (R(2) = 8.66 × 10(-01)) in order to estimate resource consumption of synthesis steps. An optimal set of predictor variables is postulated to balance model complexity and embedded information with usability and capability of merging models with existing Enterprise Resource Planning (ERP) data systems. The amount of organic solvents used, molar efficiency, and duration of a synthesis step were shown to be the most significant predictor variables. Including additional predictor variables did not contribute to the predictive power and eventually weakens the model interpretation. Ideally, an organization should be able to derive its environmental impact from readily available ERP data, linking supply chains back to the cradle of resource extraction, excluding the need for an approximation with product group averages.