The effects of material attributes on capsule fill weight and weight variability in dosator nozzle machines.

The goal of this work is to identify and understand the complex relationship between the material attributes, capsule fill weight and weight variability of capsules filled with a dosator nozzle machine. Six powders were characterized and filled into size-3 capsules in three volumes of dosing chambers and at two filling speeds. Subsequent multivariate data analysis was used to identify the influence of the material attributes on the capsule fill weight and weight variability. We observed a clear correlation between the capsule fill weight and the particle size, the air permeability and the compressibility. As the fill weight decreases, more factors affect capsule fill weight. For example, the wall friction angle, the tapped density, and the particle shape proved to be important factors. Larger fill weights were more affected by density while lower fill weights by flow and friction characteristics. No correlation was found between the material attributes and the weight variability. Rather, we could also see the major effect of process parameters on capsule fill weight and weight variability.

An integrated Quality by Design (QbD) approach towards design space definition of a blending unit operation by Discrete Element Method (DEM) simulation.

A combined Quality by Design (QbD) and Discrete Element Model (DEM) simulation-approach is presented to characterize a blending unit operation by evaluating the impact of formulation parameters and process variables on the blending quality and blending end point. Understanding the variability of both the API and the excipients, as well as their impact on the blending process are critical elements for blending QbD. In a first step, the QbD-methodology is systematically used to (1) establish the critical quality attribute content uniformity and to link this CQA to its surrogate blend homogeneity, (2) identify potentially critical input factors that may affect blending operation quality and (3) risk-rank these factors to define activities for process characterization. Subsequently, a DEM-simulation-based characterization of the blending process is performed. A statistical evaluation is finally presented, relating blend homogeneity of systems with low particle number to the regulatory requirements. Data are then used to map out a three-dimensional knowledge space, providing parameters to define a design space and set up an appropriate control strategy.