271523 Developing Improved Understanding of Spray Drying Through Process Modelling

Thursday, November 1, 2012: 8:30 AM
Allegheny III (Westin )
Thoralf Hartwig1, Francois Ricard1, Ian C. Kemp1, Mark A. Pinto2 and Sean K. Bermingham2, (1)Particle Generation and Control Engineering, GlaxoSmithKline Ltd, Stevenage, United Kingdom, (2)Process Systems Enterprise, London, United Kingdom

Spray drying is often used in the pharmaceutical industry to rapidly produce particles with narrow size distributions and with low moisture contents.  In the spray drying process, a suspension or solution of a desirable product in a volatile solvent is converted to a largely dry solid product by contact with a drying medium. The process starts with an atomizer which creates droplets from the feed suspension or solution. These droplets are then mixed with a hot gas. Evaporation of the volatile solvent in the droplets takes place and a dry solid product is thus obtained.

Significant work has been done in the past to look at how individual droplets dry within a spray dryer. These models include detailed mass and energy balances and predict the droplet temperature and radius profile as drying occurs. In practice however, the atomisation process produces droplets of a range of sizes. As one of the factors influencing the rate of drying of a droplet is its initial droplet size, a model of a spray dryer should consider the distribution of droplet sizes generated in the atomiser in order to obtain a better prediction of product temperature and moisture content.

A model has been developed that considers this distribution of droplet sizes within the spray dryer. The model outputs include temperature and droplet size histories of droplets of various sizes as well as the evolution of the droplet size distribution within the spray dryer. The model has been used in a pharmaceutical application to look at how the mathematical modelling can aid in process development. The results obtained from this case study are promising and indicate that process modelling has the potential to significantly reduce process development times and costs.

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