The pharmaceutical industry is facing increasing demands to deliver a higher variety of products more quickly, economically and sustainably. In order to achieve this, the sector is making better use out of cyber-physical production systems with a specific focus on digital twins and how they can be used to hugely minimise the amount of material utilised in the design of a manufacturing process. However, these models which will be used to build a digital twin are not focused on a single piece of equipment, process or even physics, but are holistic models which aggregate data from multiple sources. This could include for example, crystal structure, solubility predictions, population balance, CFD, and DEM. Interfacing with all this data in a manageable manner is challenging, especially for a non-modeller. This presentation highlights CMAC’s recent work in 1) creating digital twins that sit across multiple model types with an interface accessible for a non-modeller, 2) undertaking end to end manufacturing of an API mirrored by an end to end process model and 3) developing and delivering training to researchers to provide them with the skills needed to design, build and operate digital twins and microfactories across pharmaceutical manufacturing.
|Publication status||Published - 12 Nov 2019|
|Event||AIChE Annual Meeting 2019 - Orlando, United States|
Duration: 9 Nov 2019 → 15 Nov 2019
|Conference||AIChE Annual Meeting 2019|
|Period||9/11/19 → 15/11/19|