Webinar: Self-driving tableting DataFactory

05/12/2023 3pm (Paris Time) - Online,
Presented by Daniel Markl

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Tuesday, December 5th - 3:00 pm CET (Paris time)

Traditional methods of developing drug products for a new active pharmaceutical ingredient are time-consuming, costly and often inflexible. The selection of the right excipients in tablets and process conditions are crucially important as they can impact manufacturability, performance and stability of the drug product. Formulation optimisation studies are conducted to identify a robust formulation that can meet manufacturability criteria (e.g. flowability, tensile strength) while fulfilling the desired performance targets, e.g. release of > 80% of the drug in less than 30 min. This is a multidimensional problem with a high degree of interdependence between raw material attributes, process parameters, and drug product properties. These complex relationships cannot be fully captured by first principle models and it is not feasible, in a reasonable time, to experimentally investigate these multidimensional formulation (type of excipient, concentration, drug loading) and process parameter (e.g. compression force, dwell time) spaces following traditional experimental planning and methods.

This webinar will present a self-driving, high-throughput, data-intensive micro-scale tablet development system – a tableting DataFactory - that can automatically prepare and measure powder, produce and test single tablets. By employing robots, the system combines an automated dosing unit, a dedicated powder transportation unit, near-infrared spectroscopy for evaluating powder blend homogeneity, a STYL’One compaction simulator, and an automated testing system for measuring tablet properties. The data is automatically structured and fed into a database for the development of a hybrid system of models, including mechanistic and data-driven (AI) approaches, to predict critical powder blend (e.g. flowability) and tablet attributes (tensile strength, porosity) from raw material properties.

This webinar will further discuss the combination of hybrid modelling approaches with model-based optimisation and the micro-scale tablet development system. This approach significantly reduces hands-on-lab time (> 80%), material, and waste, offering significant potential for accelerated and sustainable drug product development.

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tablet development data-driven methods digital technologies

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KEY LEARNINGS

How STYL'One compaction simulators can be used to significantly reduce hands-on time, material, and waste
How digital technologies integrating a compaction simulator, robotics and data-driven methods work together in a fully self-driving tablet development system
How artificial intelligence combined with mechanistic and empirical models can revolutionize tablet development methodology

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About the speaker

Daniel Markl

Daniel Markl is a Reader in Pharmaceutical Product Engineering at the University of Strathclyde and Associate Director at the Centre for Continuous Manufacturing and Advanced Crystallisation (CMAC). He obtained a PhD in chemical engineering from Graz University of Technology, worked as a Senior Scientist at the Research Center Pharmaceutical Engineering (RCPE) and as a Research Associate at the University of Cambridge before joining the University of Strathclyde in 2018 to start his research group in the area of coupling advanced measurement techniques with digital process and product design tools to resolve the relationship between material attributes, manufacturing conditions and the performance and stability of solid oral dosage forms.

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