Digital twin of a continuous direct compression line for drug product and process design using a hybrid flowsheet modelling approach.

The pharmaceutical industry is continuously overcoming ways to reduce its development times to market and bring new medicines to patients with the highest quality standards faster. This can be achieved with continuous manufacturing and digital design by minimising the amount of active pharmaceutical ingredient (API) needed in drug product design, early project de-risking, and reducing the use of clinical manufacturing equipment, rework, and quality investigations. This paper presents the digital twin of a continuous direct compression line combining first-principles models, residence time distribution (RTD) models obtained from discrete element method (DEM) simulations, science of scale tools and data-driven models from process data in a hybrid flowsheet approach. The flowsheet predicts critical process parameters in the feeders, blender, and tablet press, and critical quality attributes, like tablet composition, weight, thickness, and hardness. It allows the study of the steady state operation in the design space, the impact of operating conditions, material and process parameters, and the dynamic response to disturbances. This is used to de-risk and optimise drug product and process development while reducing the number of experiments. The digital twin also has the potential to guide manufacturing runs and respond to new drug product market approval queries using flowsheet modelling.

Development of a predictive model for gravimetric powder feeding from an API-rich materials properties library.

A model was developed for predicting the feed factor profile of a powder, processed through a gravimetric feeder, as a function of material properties and process parameters. Predictive models proposed in existing literature have often used excipients and active pharmaceutical ingredients (APIs) with good powder flow characteristics in their development. In this work, a material properties library containing a large proportion of APIs, as well as excipients and co-processed blends, was used to build the model and enhance the prediction of feed factor profile for cohesive powders. Gravimetric feeder trials were performed at varying mass flow rates and screw geometries to determine the feed factor profiles. A semi-empirical exponential model, with parameters fmax, fmin, and ß, was then used to fit the experimental feed factor profiles. Bayesian optimisation and Support Vector Regression (SVR) modelling techniques were utilised to optimise and predict the exponential model parameters as a function of material properties. The parameters found to strongly influence the model were particle size, bulk density, FFC and FT4 rheometer parameters. Results showed low prediction errors between the estimated and experimental data. The final model produces good estimations of the feed factor profile and requires minimal powder consumption.

Continuous Mixing Technology: Characterization of a Vertical Mixer Using Residence Time Distribution.

Continuous powder mixing technology (CMT) application during continuous direct compression has emerged as a leading technology used in the development and manufacture of solid oral dosage forms. The critical quality attributes of the final product are heavily dependent on the performance of the mixing step as the quality of mixing directly influences the drug product quality attributes. This study investigates the impact of blend material properties (bulk density, API particle size distribution) and process parameters (process throughput, hold up mass and impeller speed) on the mixing performance. Mixing of the blend was characterized using the Residence Time Distribution (RTD) of the process by trending the outlet stream of the mixer using a near-infrared (NIR) probe after the injection of a small mass of tracer at the inlet stream. The outcomes of this study show that the RTDs of the mixer with throughput ranging between 15 and 30 kg/h; impeller speed ranging between 400 and 600 rpm and hold up mass (HUM) ranging between 500 and 850 g can be described by a series of two ideal Continuous Stirred Tank Reactors (CSTRs) with different volumes, and correspondingly, different mean residence times. It is also observed that the mixing is mainly occurring in the lower chamber of the CMT and the normalized RTDs of the mixer are similar across the range of process conditions and material attributes studied. The results also showed that the formulation blend with different API particle sizes and bulk properties, like bulk density and flowability, provide insignificant impact on the mixing performance. The CMT allows independent selection of target set points for HUM, impeller rotational speed and line throughput and it shows great robustness and flexibility for continuous blending in solid oral dose manufacturing.

Towards integrated drug substance and drug product design for an active pharmaceutical ingredient using particle engineering.

A novel experimental approach describing the integration of drug substance and drug production design using particle engineering techniques such as sonocrystallization, high shear wet milling (HSWM) and dry impact (hammer) milling were used to manufacture samples of an active pharmaceutical ingredient (API) with diverse particle size and size distributions. The API instability was addressed using particle engineering and through judicious selection of excipients to reduce degradation reactions. API produced using a conventional batch cooling crystallization process resulted in content uniformity issues. Hammer milling increased fine particle formation resulting in reduced content uniformity and increased degradation compared to sonocrystallized and HSWM API in the formulation. To ensure at least a 2-year shelf life based on predictions using an Accelerated Stability Assessment Program, this API should have a D [v, 0.1] of 55 µm and a D [v, 0.5] of 140 µm. The particle size of the chief excipient in the drug product formulation needed to be close to that of the API to avoid content uniformity and stability issues but large enough to reduce lactam formation. The novel methodology described here has potential for application to other APIs.