gPROMS FormulatedProducts’s solids processing libraries contain the capabilities to provide dynamic, high-fidelity models and advanced model validation, process optimization and custom modelling capabilities in addition to the basic, steady-state models available in general solids process modelling tools.
This facilitates a wide range of steps in the workflow for optimizing design and operation of solids processes: identifying dominant mechanisms, estimating model parameters that allow extrapolation of knowledge, investigation of batch vs continuous operation, process scale-up and optimization of process operation at the manufacturing scale.
The solids processing libraries are used to accelerate the development of new processes and the optimization of existing processes whilst reducing technology risk.
The formation of granules consisting active ingredient and excipient primary particles, created through either dry or wet processes, can be modelled in gPROMS FormulatedProducts® giving predictive capability of both transient granule development and their final key attributes such as size, moisture content.
Milling and screening
Milling and screening units are key in classifying, separating and recycling particles and granules that do not meet specification. Performance of these units can drastically affect downstream unit performance and so are modelled in detail.
Combining advanced process modelling of spray drying with targeted experiments for material characterization allows for process design, exploration, improvement and control. Predictions of not just thermodynamic properties but also particle attributes can be achieved allowing for an in-depth analysis of process-particle interactions.
Blending and tableting
Achieving uniformity in a blend of active ingredient and excipients is key for delivering an on-spec product. Modelling of the continuous blending stage allows for prediction of potency of the final blend and assess the impact of disturbances of the feed rate on the same. Tableting, both compaction and coating, is required for functional performance; with these models, a user may predict the final product properties such as hardness, tensile strength, porosity and coating thickness.