A Hybrid System of Computational Models to Predict Pharmaceutical Powder and Tablet Properties
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CMAC has established a system of hybrid models which span empirical, mechanistic, data-driven and AI-based approaches that predict key pharmaceutical process outputs, such as powder flow and tablet tensile strength, based on material properties, equipment settings and formulation composition for active pharmaceutical ingredients (APIs) and excipients. The models have been primarily developed for a solid oral dosage form manufactured through a continuous direct compression (CDC) route across Loss-In-Weight (LIW) feeders, blending incorporating mixture rules and tabletting. Collectively, these models have the potential to be used for digital support decision-making, process optimisation and, Quality-by-Digital-Design (QbDD) initiatives.
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An Overview of CERSI Training Courses and Course-Specific
Learning Objectives
Introduction
Question of Interest
Context of Use
Model Assumptions and Limitations
Model Risk Assessment
A Hybrid System of Models
Feeder Models
Feeder Models Lesson Recap
Feeder Models Lesson Quiz
Mixture Models
Mixture Models Lesson Recap
Mixture Models Lesson Quiz
Tableting Models
Tableting Models Lesson Recap
Tableting Models Lesson Quiz
Module Recap
End of Module Quiz
References
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Understand the Question of Interest, Context of Use and Risk Level associated with this hybrid system of models
Gain an understanding of the models that are included in this hybrid system of models including model goal, type, inputs and outputs
Gain an understanding of how the inputs and outputs of this hybrid system of models are interconnected
Easily access relevant publications to delve into these models in further detail
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Pharmaceutical professionals, regulatory affairs professionals, regulators and researchers who want to understand the concepts and methods underlying this system of computational models.
This course is delivered by CMAC’s Digital CMC CERSI team.
Available now
Format: E-learning
Free for CMAC and CERSI members and partners
Approx 1-1.5 hours
Register your interest:
