08 Mar 2021Ended

Demonstrate how machine learning tools can aid development of formulation, analysis and manufacturing of pharmaceutical drug products


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upto 100
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Mar 2021


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Novo Nordisk has initiated several optimisation projects using machine learning tools and robotics as alternatives to traditional design of .. Read more experiments (DoE) methodologies and hands-on experiments. In this webinar Rolf Hejle Taaning and Erik Skibsted from Novo Nordisk will demonstrate optimisation of pharmaceutical liquid formulations and chemical reactions using a mix of different tools like Bayesian Optimisation, Principal Component Analysis and Robotics. Erik Skibsted received a master degree in chemical engineering from the Technical University of Denmark in 1998 and worked with development of novel fluorescence sensors for bioreactor monitoring, before starting at Novo Nordisk in 2000. In 2005 he finished his PhD studies at Novo Nordisk and the University of Amsterdam in the group of Process Analysis and Chemometrics under the guidance of Professor Age Smilde. In his PhD work he developed novel algorithms for spectroscopic data analysis and published several papers on the topics of process analytical technology applied to pharmaceutical drug product manufacturing. He is deeply interested in the integration of machine learning, AI, chemometrics, sensor technology and computer technology into drug product manufacturing and formulation research. His current work, beyond his daily obligations to process development, focuses on establishing an automated and autonomous platform for chemical optimization and facilitating the access to optimization algorithms to non-programmers through tool development and graphical user interfaces.

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