Model-based approach to the design of pharmaceutical roller-compaction processes

Influence of Roll Speed during Roll Compaction and Its Effect on the Prediction of Ribbon Solid Fraction

Influence of the roll speed (RS) during roll compaction on ribbon, granule, tablet properties and its effect on the prediction of the ribbon solid fraction at-gap is often neglected or controversially discussed. The aim of this study was to investigate the effect of the RS systematically. Microcrystalline cellulose (MCC) and lactose were compressed at several maximum roll pressures (Pmax) and RS combinations using a gap-controlled roll compactor. The ribbon solid fraction after elastic recovery (SFribbon), granule size distribution and tabletability of the granules as well as the ribbon solid fraction at-gap (SFgap) were measured. The Midoux number (Mi), derived from the Johanson model, was used to predict the ribbon solid fraction at-gap (SFMi). The measured SFgap and the predicted SFMi lead to a prediction accuracy (PA) of the Midoux number. The results are highly dependent on the material used and the applied Pmax. Higher plasticity of the material leads to a reduction in SFribbon and granule size with increasing RS. However, this effect can be overcome or reduced by adjusting Pmax above the yield pressure of the used material. These results allow for higher roll speeds as a potential upscaling method in roll compaction. On the other side, the PA of the Midoux number was also reduced with increased RS for MCC and had no effect for lactose. Thus, RS seems to be an important factor in the prediction of roll compaction processes and prediction models should include RS as a parameter to improve their accuracy.

Modelling the Compaction Step of a Platform Direct Compression Process

The ability to predict formulation behaviour at production scale during formulation design can reduce the time to market and decrease product development costs. However, it is challenging to extrapolate compaction settings for direct compression formulations between tablet press models during scale-up and transfer from R&D to commercial production. The aim of this study was to develop statistical process models to predict tablet tensile strength, porosity and disintegration time from compaction parameters (pre-compression and main compression force, and press speed), for three formulations, with differing deformation characteristics (plastic, brittle and elastic), on three tablet press models (one pilot-scale tablet press (KG RoTab) and two production-scale presses (Fette 1200i and GEA Modul P)). The deformation characteristics of yield pressure and elastic recovery were determined for the model placebo formulations investigated. To facilitate comparison of dwell time settings between tablet press models, the design of experiments (DoE) approach was 9 individual 16-run response surface DoEs (3 formulation × 3 press models), whose results were combined to create a polynomial regression model for each tablet property. These models predicted tablet tensile strength, porosity and disintegration time and enabled the construction of design spaces to produce tablets with specified target properties, for each formulation on each press. The models were successfully validated. This modelling approach provides an understanding of the compaction behaviour of formulations with varying deformation behaviour on development and commercial tablet press models. This understanding can be applied to inform achievable production rates at a commercial scale, during the formulation development.

Using a Model-based Material Sparing Approach for Formulation and Process Development of a Roller Compacted Drug Product

The present work details a material sparing approach that combines material profiling with Instron uniaxial die-punch tester and use of a roller compaction mathematical model to guide both formulation and process development of a roller-compacted drug product. True density, compression profiling, and frictional properties of the pre-blend powders are used as inputs for the predictive roller compaction model, while flow properties, particle size distribution, and assay uniformity of roller compaction granules are used to select formulation composition and ribbon solid fraction. Using less than 10 g of a model drug compound for material profiling, roller compacted blend in capsule formulations with appropriate excipient ratios were developed at both 1.4% and 14.4% drug loadings. Subsequently, scale-up batches were successfully manufactured based on the roller compaction process parameters obtained from predictive modeling. The measured solid fractions of roller compaction ribbon samples from the scale-up batches were in good agreement with the target solid fraction of the modeling. This approach demonstrated considerable advantages through savings in both materials and number of batches in the development of a roller-compacted drug product, which is of particular value at early development stages when drug substance is often limited and timelines are aggressive.

Model-Based Scale-Up Methodologies for Pharmaceutical Granulation

In the pharmaceutical industry, it is a major challenge to maintain consistent quality of drug products when the batch scale of a process is changed from a laboratory scale to a pilot or commercial scale. Generally, a pharmaceutical manufacturing process involves various unit operations, such as blending, granulation, milling, tableting and coating and the process parameters of a unit operation have significant effects on the quality of the drug product. Depending on the change in batch scale, various process parameters should be strategically controlled to ensure consistent quality attributes of a drug product. In particular, the granulation may be significantly influenced by scale variation as a result of changes in various process parameters and equipment geometry. In this study, model-based scale-up methodologies for pharmaceutical granulation are presented, along with data from various related reports. The first is an engineering-based modeling method that uses dimensionless numbers based on process similarity. The second is a process analytical technology-based modeling method that maintains the desired quality attributes through flexible adjustment of process parameters by monitoring the quality attributes of process products in real time. The third is a physics-based modeling method that involves a process simulation that understands and predicts drug quality through calculation of the behavior of the process using physics related to the process. The applications of these three scale-up methods are summarized according to granulation mechanisms, such as wet granulation and dry granulation. This review shows that these model-based scale-up methodologies provide a systematic process strategy that can ensure the quality of drug products in the pharmaceutical industry.