Impact of blend properties on die filling during tableting

Abstract

Based on characterization of a wide range of fillers and APIs, thirty divergent blends were composed and subsequently compressed on a rotary tablet press, varying paddle speed and turret speed. The tablet weight variability was determined of 20 grab samples consisting of each 20 tablets. Additionally, the bulk residence time, ejection force, pre-compression displacement, main compression force, die fill fraction and feed frame fill fraction were determined during each run. Multivariate data analysis was applied to investigate the relation between the process parameters, blend characteristics, product and process responses. Blends with metoprolol tartrate as API showed high ejection forces. This behavior could be linked to the high wall friction value of metoprolol tartrate. The main responses related to the die filling could be predicted via a PLS model based on blend characteristics. Tablet weight variability was highly correlated with the variability on pre-compression displacement and main compression force. A good predictive model for tablet weight variability was obtained taking the porosity, wall friction angle, flowability, density, compressibility and permeability into account. Additionally, turret speed and paddle speed were included in the calibration of the model. The applied approach can save resources (material, time) during early drug product development.

A multivariate approach to predict the volumetric and gravimetric feeding behavior of a low feed rate feeder based on raw material properties

“…In a next step, the material properties can be linked via multivariate models with the process behavior at different unit operations of a continuous manufacturing line (e.g., feeders, blenders) (Clayton, 2015). Research has already been successfully conducted using this approach for granulation and tableting processes (Fonteyne et al, 2014;Garcia-Munoz, 2014;Haware et al, 2009aHaware et al, , 2009bThoorens et al, 2015;Van Snick et al, 2018b;Willecke et al, 2017). Once a predictive platform is developed for a unit operation, the characterization of a small amount of powder is sufficient to predict the behavior of that material at the specific unit operation.…”

The Wall Friction Properties of Pharmaceutical Powders, Blends, and Granulations

“…Faulhammer et al 18 re-visted wall friction effects in encapsulation processes in 2014 and they again reported a weak correlation between particle size and the WFA for microcrystalline cellulose samples. Finally, Van Snick et al 19 studied wall friction as part of a multivariate study of blend properties that could potentially impact die filling during tableting. They reported wall friction data for 30 active blends (with values between 4 and 18 ) and noted that the lubricated blends exhibited lower friction values than unlubricated blends.…”

Prediction of tablet weight variability in continuous manufacturing

“…A wide range of blend properties such as porosity, wall friction angle, flowability, density, compressibility, and permeability were taken into account. For more information, the reader is referred to Van Snick et al (2018).…”

“…Die filling of powder has been studied extensively using experimental and modeling techniques (Sinka et al, 2004;Wu and Cocks, 2006;Jackson et al, 2007;Schneider et al, 2007;Bierwisch et al, 2009;Guo et al, 2011;Wu and Guo, 2012;Ketterhagen, 2015;Van Snick et al, 2018). Wu et al (2003) developed a model shoe system that consisted of a rectangular feed shoe moving at a given velocity across a stationary die to study metallurgical powder flow in air and in vacuum.…”