Effects of process parameters on tablet critical quality attributes in continuous direct compression: a case study of integrating data-driven statistical models and mechanistic compaction models.

Continuous manufacturing of oral-dosage drug products is increasing the need for rigorous process understanding both from a process design and control perspective. The purpose of this study is to develop a methodology that analyzes the effects of upstream process parameters on continuous tablet compaction and then correlates associated upstream variables to the final tablet attributes (e.g. relative density and hardness). The impact of three process parameters (system throughput, blender speed, and compaction force) on tablet attributes is investigated using a full factorial experimental design. As expected, the compaction force was found to be the most significant process parameter. However, importantly, throughput was discovered to have a non-negligible impact which was previously unaccounted for. This impact is proposed to be related to differing levels of powder pre-compression. An empirical model for this relationship is regressed and incorporated into a flowsheet model. The flowsheet model is then used to develop an in silico design space which is compared favorably to that built from experiments. Moreover, in the future, the in silico design space based on the validated flowsheet model can provide better manufacturing flexibility and make control strategy development simpler.

A Thermodynamic Balance Model for Liquid Film Drying Kinetics of a Tablet Film Coating and Drying Process.

A tablet film coating and drying process was assessed by an experimentally validated thermodynamic balance model. Mass conservation equations were derived for the process air and the aqueous coating solution. Thermodynamic behavior of the solution was described by evaporation at the tablet surface and penetration into the tablet. Energy balance equations including heat loss to the atmosphere were coupled to the mass conservation equation. Experimental data using the ConsiGma™ coater (GEA, Belgium) were used for both parameter estimation and model validation. The results showed the proposed model can investigate primitive outlet variables and further internal variables representing evaporation and penetration. A sensitivity analysis revealed that evaporation depended more on the input parameters while penetration hinges on the tablet properties, particularly on the tablet volume affecting the tablet porosity.

Assessment of spatial heterogeneity in continuous twin screw wet granulation process using three-compartmental population balance model.

In this study, a novel three-compartmental population balance model (PBM) for a continuous twin screw wet granulation process is developed, combining the techniques of PBM and regression process modeling. The developed model links screw configuration, screw speed, and blend throughput with granule properties to predict the granule size distribution (GSD) and volume-average granule diameter. The granulator screw barrel was divided into three compartments along barrel length: wetting compartment, mixing compartment, and steady growth compartment. Different granulation mechanisms are assumed in each compartment. The proposed model therefore considers spatial heterogeneity, improving model prediction accuracy. An industrial data set containing 14 experiments is applied for model development. Three validation experiments show that the three-compartmental PBM can accurately predict granule diameter and size distribution at randomly selected operating conditions. Sixteen combinations of aggregation and breakage kernels are investigated in predicting the experimental GSD to best judge the granulation mechanism. The three-compartmental model is compared with a one-compartmental model in predicting granule diameter at different experimental conditions to demonstrate its advantage. The influence of the screw configuration, screw speed and blend throughput on the volume-average granule diameter is analyzed based on the developed model.

Modeling and simulation of continuous powder blending applied to a continuous direct compression process.

Continuous manufacturing techniques are increasingly being adopted in the pharmaceutical industry and powder blending is a key operation for solid-dosage tablets. A modeling methodology involving axial and radial tanks-in-series flowsheet models is developed to describe the residence time distribution (RTD) and blend uniformity of a commercial powder blending system. Process data for a six-component formulation processed in a continuous direct compression line (GEA Pharma Systems) is used to test the methodology. Impulse tests were used to generate experimental RTDs which are used along with parameter estimation to determine the number of axial tanks in the flowsheet. The weighted residual from the parameter estimation was less than the χ2 value at a 95% confidence indicating a good fit between the model and measured data. In-silico impulse tests showed the tanks-in-series modeling methodology could successfully describe the RTD behavior of the blenders along with blend uniformity through the use of radial tanks. The simulation output for both impulse weight percentage and blend uniformity were within the experimentally observed variance.

Protein a resin lifetime study: Evaluation of protein a resin performance with a model-based approach in continuous capture.

A modified shrinking core model (MSCM) has been used to describe the mechanism for the degradation of Protein A resin particles taking place under continuous chromatographic operation. The model is based on the hypothetical shrinkage of the boundary layer of the resin particles, which house the active Protein A ligands within their pores. The caustic during the sanitization phase of chromatography has been determined to cause the Protein A ligand degradation. Protein A resins provided by manufacturers possess unique caustic stability, which has been used in MSCM to appraise the ligand degradation. The kinetic model utilized semiempirical parameters including diffusion constant, rate constant, stoichiometric factor, and reaction order. The parameters were estimated from column breakthrough experiments to simulate continuous Protein A chromatography for three distinct resins. The reaction order has been identified as the key parameter for predicting the degradation kinetics. The recorded reaction orders vary for three different resins with the resin B showing the highest reaction order of 4 and lowest being 1.65 for the resin C. The model can predict the effects of caustic on resin performance and displayed that minimal degradation of the resins A and B occurred, when exposed to 0.1 N and 0.2N NaOH, retaining up to 96% binding capacity after 240 cycles. The adsorption study conducted for the resin B demonstrated the dynamic physical and chemical changes transpiring through the life cycle of the resin, further supported the degradation model. The performance data demonstrate that the resin B exhibits the desirable performance, with higher reaction order indicating slower resin degradation, higher binding capacities, and increased sustenance of this binding capacity for extended duration. The degradation model can be extended to build effective cleaning strategies for continuous downstream processing.

Serially Ordered Magnetization of Nanoclusters via Control of Various Transition Metal Dopants for the Multifractionation of Cells in Microfluidic Magnetophoresis Devices.

A novel method (i.e., continuous magnetic cell separation in a microfluidic channel) is demonstrated to be capable of inducing multifractionation of mixed cell suspensions into multiple outlet fractions. Here, multicomponent cell separation is performed with three different distinguishable magnetic nanoclusters (MnFe2O4, Fe3O4, and CoFe2O4), which are tagged on A431 cells. Because of their mass magnetizations, which can be ideally altered by doping with magnetic atom compositions (Mn, Fe, and Co), the trajectories of cells with each magnetic nanocluster in a flow are shown to be distinct when dragged under the same external magnetic field; the rest of the magnetic characteristics of the nanoclusters are identically fixed. This proof of concept study, which utilizes the magnetization-controlled nanoclusters (NCs), suggests that precise and effective multifractionation is achievable with high-throughput and systematic accuracy for dynamic cell separation.