Introduction

Pan coating is a commonly used unit operation
to apply a functional layer around tablet cores. The tablet cores are placed in
a rotating drum, and a coating liquid is sprayed onto the moving tablets. The
coating fulfils different functions; a special application is active coating,
where the coating layer itself contains an active pharmaceutical ingredient
(API). In this case, the variation of coating mass between tablets has to be
consistently small.

To guarantee a consistently high uniformity,
a large amount of process understanding is needed. To this end, a number of
experimental investigations were done. In recent years, a strong trend emerged
to complement this with numerical simulations^1,2.

Due to lengthy simulation times, these
investigations often are restricted to small-scale cases. This limits the
statements that can be done for the industry (full) scale process, and generally
means that no or few large-scale data points are available for scale-up
considerations.

In this work, the application of an active
coating was investigated from lab scale to industry scale using Discrete
Element Method (DEM) simulations (both commercial software and in-house code).
The influence of process parameters on the quality attributes is studied for
each scale. Further, it is studied how far scale-up rules known in literature³
are applicable, and new guidelines are considered.

Material & Method

Tablet
coating process

The investigated tablet is a Gastrointestinal
therapeutic systems (Adalat® GITS, Bayer Pharma AG, Germany) coated with an
aqueous suspension containing candesartan cilexetil as API. Different
sizes of pan coaters (BFC, L.B. Bohle, Germany) were used. The process
parameters were set according to experimental runs and available formulation
data. As the variation of this API between tablets has to be
small, a high inter-tablet coating mass uniformity is vital. The central aim
therefore was to improve the inter-tablet coating uniformity.

Discrete
Element Method (DEM) simulations

For the simulations, a commercial software
(EDEM 2.5.1, DEM Solutions, UK) and an in-house developed code (XPS, Research
Center Pharmaceutical Engineering GmbH, Austria) were combined to cover the
scale range. The XPS software exploits the massively parallel structures of
modern graphic cards to simulate number of particles that is sufficiently large
to cover even the industrial scale with reasonable computation times. The material properties came from measurements⁴.
Different methods for the modeling of a spray in DEM simulations were
implemented⁵.

Figure 1: Snapshot of the
Discrete Element Method simulation of the lab-scale coating drum.

Conclusion

In this work, two implementations of Discrete Element Method
simulations were combined to describe a tablet coating process from lab scale
to pilot scale. The parameters needed from simulation were taken from
measurements where possible. For the pilot scale, comparison
of the simulation result to available measurement data was done. On one hand,
valuable insights into the process mechanics were gathered on each separate
scale. On the other hand, covering the whole scale range allowed for a critical
treatment of existing scale-up rules and the investigation towards new
guidelines.

References

1.            Ketterhagen, W. R., am Ende, M. T. &
Hancock, B. C. Process modeling in the pharmaceutical industry using the
discrete element method. J. Pharm. Sci. 98, 442?70 (2009).

2.            Toschkoff, G. & Khinast, J. G. Mathematical
modeling of the coating process. Int J Pharm (2013).

3.            Mueller, R. & Kleinebudde, P. Prediction of
tablet velocity in pan coaters for scale-up. Powder Technol. 173, 51?58 (2007).

4.            Just, S. et al. Experimental analysis of tablet
properties for discrete element modeling of an active coating process. AAPS
PharmSciTech 14, 402?11 (2013).

5.            Toschkoff, G. et al. Spray models for discrete
element simulations of particle coating processes. Chem Eng Sci 101, 603?614
(2013).