Mechanistic models, or science-based digital twins, use process understanding to describe and predict the quantitative behavior of pharmaceutical processes for risk assessment, control strategy design and evaluation, scale up/tech transfer, and design space exploration. While science-based models are well established and widely accepted for traditional liquid chemical processes, drug product manufacturing relies heavily on solid processing, for which mechanistic modeling is a rapidly evolving field. Although population balance models are often considered the standard framework for solids processing, in fact a variety of methodologies are available to describe drug product manufacturing processes, ranging from simple dimensionless number models to high-fidelity models like the discrete element method. In pharmaceutical applications, it is often the simpler models that prove the most useful in achieving practical objectives.
In this webinar, we will compare and contrast science-based modeling frameworks for drug product manufacturing processes, including:
- Mass and energy balance & thermodynamic models
- Regime map and dimensionless number models
- Compaction models
- Residence time distribution models
- Population balance models
- High-fidelity models (computational fluid dynamics & discrete element method)
Industrial applications of these approaches will be discussed, highlighting key differences in assumptions, data requirements, capabilities, and limitations. These cases studies will cover a variety of unit operations, including roller compaction, continuous feeding and blending, tablet coating, and fluid bed granulation. Finally, considerations will be presented to determine how to select the most appropriate model to solve a particular problem.
What this webinar covers
- Model-based approaches to drug product manufacture in pharmaceutical R&D and engineering
- A variety of available methodologies to describe solids processes in a digital twin
- Industrial application cases of these methodologies
- Considerations for selecting the appropriate model for a particular objective
Who should attend?
Those with an interest in drug product manufacturing, from non-modellers to expert modellers.
Dana Barrasso is a Principal Consultant in the Formulated Products business unit at Process Systems Enterprise. As PSE’s Strategy Director for Pharmaceuticals, she is the technical lead for collaborative and strategic activities with industry, academia, and regulatory bodies in the synthetic pharmaceuticals sector. Her responsibilities include acting as the technical director for the Systems-based Pharmaceutics Alliance, a collaborative project between Eli Lilly, GSK, Pfizer, Roche, Sanofi, Bayer and PSE aimed at developing the tools and workflows that enable systems-based approaches to drug product and process design. With a PhD from Rutgers University, Dana’s background is in solids process modeling, with a focus on wet granulation processes. With this experience, she leads the development and application of PSE’s offerings in drug product manufacture, including continuous direct compression, wet and dry granulation, and tableting.
6 January 2021, 10:00 EST/ 15:00 GMT
45 minutes plus Q&AWATCH NOW