Linked experimental and modelling approaches for tablet property predictions.

Recent years have seen the advent of Quality-by-Design (QbD) as a philosophy to ensure the quality, safety, and efficiency of pharmaceutical production. The key pharmaceutical processing methodology of Direct Compression to produce tablets is also the focus of some research. The traditional Design-of-Experiments and purely experimental approach to achieve such quality and process development goals can have significant time and resource requirements. The present work evaluates potential for using combined modelling and experimental approach, which may reduce this burden by predicting the properties of multicomponent tablets from pure component compression and compaction model parameters. Additionally, it evaluates the use of extrapolation from binary tablet data to determine theoretical pure component model parameters for materials that cannot be compacted in the pure form. It was found that extrapolation using binary tablet data - where one known component can be compacted in pure form and the other is a challenging material which cannot be - is possible. Various mixing rules have been evaluated to assess which are suitable for multicomponent tablet property prediction, and in the present work linear averaging using pre-compression volume fractions has been found to be the most suitable for compression model parameters, while for compaction it has been found that averaging using a power law equation form produced the best agreement with experimental data. Different approaches for estimating component volume fractions have also been evaluated, and using estimations based on theoretical relative rates of compression of the pure components has been found to perform slightly better than using constant volume fractions (that assume a fully compressed mixture). The approach presented in this work (extrapolation of, where necessary, binary tablet data combined with mixing rules using volume fractions) provides a framework and path for predictions for multicomponent tablets without the need for any additional fitting based on the multicomponent formulation composition. It allows the knowledge space of the tablet to be rapidly evaluated, and key regions of interest to be identified for follow-up, targeted experiments that that could lead to an establishment of a design and control space and forgo a laborious initial Design-of-Experiments.

High-throughput blend segregation evaluation using automated powder dispensing technology.

Due to the complexity in the interactions of variables and mechanisms leading to blend segregation, quantifying the segregation propensity of an Active Pharmaceutical Ingredient (API) has been challenging. A high-throughput segregation risk prediction workflow for early drug product development has been developed based on the dispensing mechanism of automated powder dispensing technology. The workflow utilized liquid handling robots and high-performance liquid chromatography (HPLC) with a well-plate autosampler for sample preparation and analysis. Blends containing three different APIs of varying concentrations and particle sizes of different constituents were evaluated through this automated workflow. The workflow enabled segregation evaluation of different API blends in very small quantities (~7g) compared to other common segregation testers that consume hundreds of grams. Segregation patterns obtained were well explained with vibration induced percolation-based segregation phenomena. Segregation risk was translated quantitatively using relative standard deviation (RSD) calculations, and the results matched well with large-scale segregation studies. The applied approach increased the throughput, introduced a simple and clean walk-up method with minimized equipment space and API exposures to conduct segregation studies. Results obtained can provide insights about optimizing particle size distributions, as well as selecting appropriate formulation constituents and secondary processing steps in early drug product development when the amount of available API is very limited.

Lubrication empirical model to predict tensile strength of directly compressed powder blends.

A new approach is proposed to support prediction of tablet tensile strength as a function of both solid fraction (and/or compression pressure) and extent of lubrication by using empirical data to parameterise the model. This is a pre-requisite for simulation of the compaction unit operation where a linkage from tablet press operating parameters and formulation material properties to output tensile strength is required. The approach extends the previously published Kushner and Moore model to allow calculation across a range of solid fractions. The applicability of the approach is supported by testing using formulations with different commonly used pharmaceutical excipients.

Development and Scale-Up of Diversion Strategy for Twin Screw Granulation in Continuous Manufacturing.

Successful implementation of Continuous Manufacturing technology requires real time product quality monitoring that can result into rejection strategies for material manufactured outside process control limits. In a twin screw granulation process, parameters like water content, powder feed rate, and granulator screw speed can influence granule quality. Deviations in any of these parameters from the set-point may affect granule quality. Having a sound diversion strategy in place can help divert these implicated granules to waste. Residence time distribution experiments were conducted on a 16-mm Thermo Fisher twin screw granulator (TSG) for a range of process parameters, and the data was modelled to predict the needed diversion time as a function of process parameters. Scale-up from the 16-mm to 24-mm granulator was evaluated and data was found to scale based on mass per unit volume of granulator (channel fill), thus enabling 16-mm data to scale to 24-mm. The diversion strategy proposed is based on utilizing a wash out curve derived from residence time distribution to quantify the maximum concentration of implicated material that could be present in the next downstream unit operation(s) (e.g. a fluid bed dryer) and ensuring it is less than a suitable threshold to prevent product quality impact.

The impact of channel fill level on internal forces during continuous twin screw wet granulation.

The forces experienced by the particles inside a twin screw granulator (TSG) are one of the most difficult parameters to measure quantitatively. However, it is possible to perform accurately this measurement through the use of dye containing calibrated microencapsulated sensors (CAMES) whose rupture is directly dependant on their experienced shear stress. The current study measures the extent of local stresses in the transformation from powder to granules at different channel fills during TSG processing. Channel fill has shown good potential as a design tool, however, its validity for predicting particle size distributions has yet to be demonstrated in an 11-mm TSG. The results of this study showed that the particles within the twin screw granulator experienced stresses in the range of 350-1000 kPa and this value was not linear with the specific mechanical energy applied by the granulator. It was observed that the majority of these stresses were produced by material transport processes rather than the granulation in itself. In addition it was determined that the torque required by the TSG increases exponentially after a certain channel fill a feature that requires to be considered in order to design safer, predictable and reliable granulation workspaces.

Decoupling the role of image size and calorie intake on gastric retention of swelling-based gastric retentive formulations: pre-screening in the dog model.

Gastric retention is postulated as an approach to improve bioavailability of compounds with narrow absorption windows. To elucidate the role of image size on gastric retention and pharmacokinetics, formulations with different image sizes and swelling kinetics but similar dissolution rates were designed and imaged in dogs. Diet had a clear effect, with increasing calorific intake prolonging retention in the dog model. In contrast to clinical observations, no obvious effect of image size on gastric retention was observed in the dog, with the larger gastric retentive (GR) and smaller controlled release (CR) formulations both demonstrating similar gastric emptying. Comparable pharmacokinetic profiles were observed for the two formulations, corroborating the imaging data and providing evidence of similar in vivo dissolution rates and dosage form integrity in the dog. Food, specifically meal composition, resulted in comparable enhancements in exposure in the dog and clinic due to prolonged gastric retention. However, differentiating retention based on image size in the dog was not feasible due to the smaller pyloric aperture compared to humans. This work illustrates that the dog is capable of determining the pharmacokinetic advantage of gastric retention relative to immediate release (IR) or CR formulations, however, has limited value in differentiating between CR and GR formulations.