Integrated Filtration and Washing Modeling: Optimization of Impurity Rejection for Filtration and Washing of Active Pharmaceutical Ingredients.

A digital design tool that can transfer material property information between unit operations to predict the product attributes in integrated purification processes has been developed to facilitate end-to-end integrated pharmaceutical manufacturing. This work aims to combine filtration and washing operations frequently using active pharmaceutical ingredient (API) isolation. This is achieved by coupling predicted and experimental data produced during the upstream crystallization process. To reduce impurities in the isolated cake, a mechanistic model-based workflow was used to optimize an integrated filtration and washing process model. The Carman-Kozeny filtration model has been combined with a custom washing model that incorporates diffusion and axial dispersion mechanisms. The developed model and approach were applied to two systems, namely, mefenamic acid and paracetamol, which are representative compounds, and various crystallization and wash solvents and related impurities were used. The custom washing model provides a detailed evolution of species concentration during washing, simulating the washing curve with the three stages of the wash curve: constant rate, intermediate stage, and diffusion stage. A model validation approach was used to estimate cake properties (e.g., specific cake resistance, cake volume, cake composition after washing, and washing curve). A global systems analysis was conducted by using the calibrated model to explore the design space and aid in the setup of the optimization decision variables. Qualitative optimization was performed in order to reduce the concentration of impurities in the final cake after washing. The findings of this work were translated into a final model to simulate the optimal isolation conditions.

Digital Design of Filtration and Washing of Active Pharmaceutical Ingredients via Mechanistic Modeling.

To facilitate integrated end-to-end pharmaceutical manufacturing using digital design, a model capable of transferring material property information between operations to predict product attributes in integrated purification processes has been developed. The focus of the work reported here combines filtration and washing operations used in active pharmaceutical ingredient (API) purification and isolation to predict isolation performance without the need of extensive experimental work. A fixed Carman-Kozeny filtration model is integrated with several washing mechanisms (displacement, dilution, and axial dispersion). Two limiting cases are considered: case 1 where there is no change in the solid phase during isolation (no particle dissolution and/or growth), and case 2 where the liquid and solid phases are equilibrated over the course of isolation. In reality, all actual manufacturing conditions would be bracketed by these two limiting cases, so consideration of these two scenarios provides rigorous theoretical bounds for assessing isolation performance. This modeling approach aims to facilitate the selection of most appropriate models suitable for different isolation scenarios, without the requirement to use overly complex models for straightforward isolation processes. Mefenamic acid and paracetamol were selected as representative model compounds to assess a range of isolation scenarios. In each case, the objective of the models was to identify the purity of the product reached with a fixed wash ratio and minimize the changes to the crystalline particle attributes that occur during the isolation process. This was undertaken with the aim of identifying suitable criteria for the selection of appropriate filtration and washing models corresponding to relevant processing conditions, and ultimately developing guidelines for the digital design of filtration and washing processes.

Model driven design for integrated twin screw granulator and fluid bed dryer via flowsheet modelling.

This paper presents a flowsheet modelling of an integrated twin screw granulation (TSG) and fluid bed dryer (FBD) process using a Model Driven Design (MDD) approach. The MDD approach is featured by appropriate process models and efficient model calibration workflow to ensure the product quality. The design space exploration is driven by the physics of the process instead of extensive experimental trials. By means of MDD, the mechanistic-based process kernels are first defined for the TSG and FBD processes. With the awareness of the underlying physics, the complementary experiments are carried out with relevance to the kinetic parameters in the defined models. As a result, the experiments are specifically purposeful for model calibration and validation. The L/S ratio (liquid to solid ratio) and inlet air temperature are selected as the Critical Process Parameters (CPPs) in TSG and FBD for model validation, respectively. Global System Analysis (GSA) is further performed to assess the uncertainty of CPPs imposed on the Critical Quality Attributes (CQAs), which provides significant insights to the exploration of the design space considering both TSG and FBD process parameters.

Tableting model assessment of porosity and tensile strength using a continuous wet granulation route.

This paper presents a comprehensive assessment of the most widely used tablet compaction models in a continuous wet granulation tableting process. The porosity models, tensile strength models and lubricant models are reviewed from the literature and classified based on their formulations i.e. empirical or theoretical and applications, i.e. batch or continuous. The majority of these models are empirical and were initially developed for batch tabletting process. To ascertain their effectiveness and serviceability in the continuous tableting process, a continuous powder processing line of Diamond Pilot Plant (DiPP) installed at The University of Sheffield was used to provide the quantitative data for tablet model assessment. Magnesium stearate (MgSt) is used as a lubricant to investigate its influence on the tensile strength. Whilst satisfactory predictions from the tablet models can be produced, a compromise between the model fidelity and model simplicity needs to be made for a suitable model selection. The Sonnergaard model outperforms amongst the porosity models whilst the Reynolds model produces the best goodness of fitting for two parameters fitting porosity models. An improved tensile strength model is proposed to consider the influence of powder size and porosity in the continuous tableting process.