A novel mixing rule model to predict the flowability of directly compressed pharmaceutical blends.

In the pharmaceutical industry, powder flowability is an essential manufacturability attribute to consider when selecting the suitable manufacturing route and formulation. The selection of the formulation is usually based on the physical and chemical properties of the Active Pharmaceutical Ingredient (API) under consideration. Current industrial practice heavily relies on experimental work, which often results in significant labor and API consumption that results in higher costs. In this study we describe the development of a mixing rule to predict powder blend flowability from the flow properties of the individual components for industrial formulations manufactured via Direct Compression (DC). The mixing rule assumes that the granular solids' interactions are dominated by cohesive forces but are pragmatic to calibrate from the perspective of the typical data collated in an industrial environment. The proposed model was validated using a range of different APIs and the results show that the model can effectively predict the flowability properties of any formulation across the space of DC-relevant formulation compositions. Finally, a connection between the model and APIs properties (shape and size) was investigated via a linear correlation between the API particle properties and interparticle forces.

Enhanced in-situ liquid transport investigation setup for pharmaceutical tablet disintegration analysis using terahertz radiation.

The disintegration process of pharmaceutical solid dosage forms commences on contact with the dissolution medium and continues with subsequent spontaneous imbibition of the medium in the tablet matrix. Identifying the location of the liquid front in situ during imbibition, therefore, plays a significant role in understanding and modelling the disintegration process. Terahertz pulsed imaging (TPI) technology can be used to investigate this process by its ability to penetrate and identify the liquid front in pharmaceutical tablets. However, previous studies were limited to samples suitable for a flow cell environment, i.e. flat cylindrical disk shapes; thus, most commercial tablets could only be measured with prior destructive sample preparation. This study presents a new experimental setup named open immersion to measure a wide range of pharmaceutical tablets in their intact form. Besides, a series of data processing techniques to extract subtle features of the advancing liquid front are designed and utilised, effectively increasing the maximum thickness of tablets that can be analysed. We used the new method and successfully measured the liquid ingress profiles for a set of oval convex tablets prepared from a complex eroding immediate-release formulation.

Practical use of primary drying models in an industrial environment with limited availability of equipment sensors.

In the pharmaceutical industry, lyophilization is typically adopted to extend long-time stability of valuable thermolabile medicines and vaccines. Primary drying is the most time-consuming and energy-intensive step of the entire process; thus, accelerating and optimizing the primary drying recipe is a key process development goal. To that purpose, mathematical models have been proposed and successfully validated. However, models typically require invasive experiments and/or sensors (e.g. product temperatures) for parameter estimation, which are rarely available in good manufacturing practice (GMP) environment. This represents a severe limitation when leveraging the model to transfer operation recipes across different facilities and for scale-up. In this study, we assess the possibility to exploit limited industrial data for model parameter estimation, namely pressure measurements and gravimetric tests, by defining a calibration protocol that is tested on two different pieces of equipment. Results are verified on a recently proposed model, and show that statistically meaningful estimates can be obtained without the need of product temperature measurements. Model predictions and optimal inputs trajectories are comparable to those obtained from the model calibrated using the full set of temperature and pressure data.

Streamlining tablet lubrication design via model-based design of experiments.

In oral solid dosage production through direct compression powder lubrication must be carefully selected to facilitate the manufacturing of tablets without degrading product manufacturability and quality (e.g. dissolution). To do so, several semi-empirical models relating compression performance to process operating conditions have been developed. Among them, we consider an extension of the Kushner and Moore model (Kushner and Moore, 2010, International Journal Pharmaceutics, 399:19) that is useful for the purpose, but requires an extensive experimental campaign for parameters identification. This implies the preparation and compression of multiple powder blends, each one with a different lubrication extent. In turn, this translates into a considerable consumption of Active Pharmaceutical Ingredient (API), and into time-consuming experiments. We tackled this issue by proposing a novel model-based design of experiments (MBDoE) approach, which minimizes the number of optimal blends for model calibration, while obtaining statistically sound parameters estimates and model predictions. Both sequential and parallel MBDoE configurations were compared. Experimental results involving two placebo blends with different lubrication sensitivity showed that this methodology is able to reduce the experimental effort by 60-70% with respect to the standard industrial practice independently of the formulation considered and configuration (i.e. parallel vs. sequential) adopted.