(205f) Roller Compaction Modelling: Pharmaceutical Application

Sousa, R., R&D Drug Product Development
Doktorovova, S., Hovione FarmaCiência SA
Sainz, V., Hovione
Valente, P., Hovione FarmaCiência SA
Authelin, J. R., Sanofi
Bardet, L., Sanofi

Roller Compaction Modelling: Pharmaceutical



R. Sousa1, L. Bardet2, S.
Doktorovova1, V. Sainz1, P.C. Valente1, J.R.

1 R&D Drug
Product Development, Hovione Farmaciência S.A, Estrada do Paço do Lumiar, 1649-038
Lisboa, Portugal;

2Sanofi-aventis, Research and Development,
Physical Quality, 94403 Vitry-sur-Seine, France

present the comparison of different roller compaction models that predict the
ribbon density from the process parameters and material constitutive laws
benchmarked against experimental data. Two models from the literature
Johanson’s Model (Johanson,
and Thin Layer Model (Peter,
Lammens, & Steffens, 2010; Reimer & Kleinebudde, 2018) were
compared with a new model, which consists in an analytical solution to predict
the pressure at gap. The three models consider two regions between the rolls, a
slip region where the roll is faster than the powder and a nip region where the
material is compressed. Johanson’s Model finds the nip angle that separates the
two regions by intersecting the pressure gradient curves in both regions,
considering the log density as a linear function of the log stress in the nip
region (Johanson,
The Thin Layer Model was modified to solve the nip angle numerically to match
the specific roll force and relates the stress as a function of the natural
strain (Yu,
Regarding the new model, the nip angle is calculated as an analytical function
of the densification factor. Then, the nip angle expression is used in the
force integral to derive the maximum pressure, which can be used to estimate
the density at gap. All the calculations explained in the new model result in a
single expression that relates the at gap density with the material constitutive
laws (a constant and the compressibility factor), the specific roll force, gap
width and roll dimensions.

relative density has been shown to be a key predictor of granule properties
post milling. Densification should be as high as necessary to achieve the
desired granule flowability, but as low as possible to avoid the loss in
compactibility (Kleinebudde,
Therefore, in order to save time and material during formulation development,
it is advantageous to have a predictive model based on easily accessible
parameters and possible to calibrate with few experiments.

We present
different methodologies to calibrate these models based on roller compaction
experiments or die uniaxial simulations. The three models were calibrated for
three different formulations with one third of the samples used for external
validation. The new model was as reliable as the Johanson or Thin Layer models,
with a prediction error of approximately ±0.1 g/mL. In conclusion, these models
are important tools to obtain the desired granule properties with minimum loss
in development time and material. For instance, a roller compaction experiment
requires a minimum of 100 g of material, while a die compaction simulation
would only need a few milligrams to estimate the material properties.
Furthermore, they facilitate the scale up and should be easily transferred
between different roller compactors.

We dedicate
this work to prof. Noel Midoux who wrote all equations for the new model.


Johanson, J. R. (1965).
A Rolling Theory for Granular Solids. Journal of Applied Mechanics, 32(4),
842–848. https://doi.org/10.1115/1.3627325

P. (2004). Roll compaction/dry granulation: Pharmaceutical applications. European
Journal of Pharmaceutics and Biopharmaceutics
, 58(2), 317–326.

Peter, S.,
Lammens, R. F., & Steffens, K. J. (2010). Roller compaction/Dry
granulation: Use of the thin layer model for predicting densities and forces
during roller compaction. Powder Technology, 199(2), 165–175.

Reimer, H.
L., & Kleinebudde, P. (2018). Hybrid modeling of roll compaction processes
with the Styl’One Evolution. Powder Technology, #pagerange#.

Yu, S.
to The University of Birmingham for the degree of School of Chemical
Engineering The University of Birmingham October 2012, (October).