(201e) Simulation of an Tablet-Coating Process on Industrial Scale

Introduction

Tablet coating is a widely used unit
operation in the pharmaceutical industry and is used to coat the tablet core
with with one or more polymer layers that have a certain function, such as enteric
coating to protect the tablet core from the acidic content of the stomach.
Sometimes, the layer can contain an active pharmaceutical ingredient (API). Inter
tablet coating mass variation (CoV) has to be low when coating an API onto a
tablet to achieve a consistent high product quality. Therefore, a good understanding
of the process is needed. Experiments focus mostly on the laboratory scale, due
to costs. Thus, for large-scale optimization simulation is a promising tool.

So far, numerical simulations focused on
laboratory scale equipment due to computational limitations [1], [2]. However, it is now
possible to simulate millions of particles using massive parallelization capabilities
of graphical processing units (GPU). This presentation demonstrates the
capabilities of DEM simulations executed on GPUs using the example of an
industrial tablet coating process with more than one million tablets.

Objective

This work is based on an active
coating process for the production of tablets that contain two APIs: one in the
core and one in the coating. Gastrointestinal therapeutic systems (GITS) were
used as starting material (Bayer Pharma AG, Leverkusen, Germany). GITS are
round-shaped biconvex tablets with a diameter of 9 mm and a height of 5 mm. In
the modeled process, an aqueous coating solution containing an API is added.
The central aim of this study was to reduce the inter tablet coating
variability (CoV) by comparing different process settings, e.g., drum load,
rotation velocity, number of nozzles.

Material and methods

Drum Coater

Coating runs were performed in a
high-performance Bohle Film Coater (BFC 400, L.B Bohle Maschinen + Verfahren
GmbH, Ennigerloh, Germany), which  is a commercially available production scale
coater . During the coating process the tablets are flowing in the rotating
drum of the coater and are mixed axially and radially by baffles integrated
into the coater design, allowing efficient mixing.

Simulation software

 ?eXtended Particle
System? (XPS)
is an in-house developed Discrete Element Method algorithm written in CUDA [3]. CUDA is a C extension developed
by nVidia, specifically designed for GPU computing. Modern GPU architecture
allows parallel computing on over 2000 so-called CUDA cores. Parallelizing the
DEM algorithm allows the simulation in the range of several 10 million spheres
on a single GPU.

To calculate the interaction of
non-spherical particles such as tablets, a glued sphere approach is used. The
simulated particle consists of eight single spheres glued together. These spheres
are allowed to overlap to approximate the real shape of a particle. In Figure 1, the filled drum is shown
as seen during the simulation.

The material properties were
determined experimentally as described in [4]. The results,
e.g. the CoV, were calculated via post processing routines. CoV results
received from 90 seconds simulated time were extrapolated and compared to experimental
measurements.

Figure 1: Filled drum coater with the position
of the spray nozzles from the side. The drum is filled with 290 kg (1,028,369
tablets) and is rotated with 8 rpm

Summary and Conclusion

The goal of this work was to simulate
the tablet coating process in an industrial scale drum coater, filled with up
to 290 kg (1,028,369  tablets), using the Discrete Element Method. Simulations
were done to investigate the influence different process parameters on the
process outcome. The parameters studied were the drum load, ranging from 230 kg
to 290 kg and the rotation velocity, ranging from 8 to 10 rpm. The spray rate
and number of nozzles was varied as well and showed a significant impact on the
CoV.

The CoV (Figure 2) results from the
simulation match results from experiments closely. This work shows that
simulation can be used to get more insight into the tablet coating process on
the industrial scale based on state-of-the-art simulation tools.

Figure 2: CoV for experiments and simulations
in a bar chart [Load, Rotation velocity, Spray Rate, Process Time] (A: [260kg,
9rpm, 160 g/min, 172 min] B: [240kg, 9rpm, 360 g/min, 248 min] C: [250 kg,
9rpm, 360 g/min, 368 min]  D: [250 kg, 9 rpm, 160 g/min, 345 min] E:[250 kg, 9
rpm, 240g/min, 522 min])

References

[1]      W. R. Ketterhagen,
M. T. am Ende, and B. C. Hancock, ?Process modeling in the pharmaceutical
industry using the discrete element method,? J. Pharm. Sci., vol. 98,
pp. 442?470, 2009.

[2]      G. Toschkoff, S. Just, K.
Knop, P. Kleinebudde, A. Funke, A. Altmeyer, D. Djuric, and G. Scharrer,
?Design-of-Experiment based DEM simulation of an active tablet coating process
.?

[3]      C.. Radeke, B. J. Glasser,
and J. G. Khinast, ?Large-scale powder mixer simulations using massively
parallel GPUarchitectures,? Chem. Eng. Sci., vol. 65, no. 24, pp.
6435?6442, Dec. 2010.

[4]      S. Just, G. Toschkoff, A.
Funke, D. Djuric, G. Scharrer, J. G. Khinast, K. Knop, and P. Kleinebudde,
?Experimental Analysis of Tablet Properties for Discrete Element Modeling of an
Active Coating Process,? AAPS PharmSciTech, vol. 14, no. 1, pp. 402?411,
2013.