Year: 2023
Type: conference-paper
Abstract: Data are the fuel for modern Industrial Digital Technologies (IDTs) such as AI. If data are not FAIRified then it could take many years for the pharma sector to reach a position in which the full value of IDTs are realised. Beyond the slow pace of data curation, the high level of laborious human intervention, and associated costs, will continue to be a challenge. Through the Smarter Innovation Centre - Digital Medicines Manufacturing Research Centre (DM2) project funded by EPSRC, we provide a foundation on which we can begin to build trusted and structured data sets that will significantly improve reusability and future value. Within Platform 1 of DM2, we have developed Extract-Transform-Load (ETL) tools to simplify data acquisition efforts and allow future data to be integrated easily. The DM2 ETL tool, with multiple components, has been developed for automatic extraction, transformation and loading of heterogeneous medicine manufacturing data from multiple instruments. Schema for experimental data in the medicine manufacturing domain has been designed that provides a structure for data and establishes linkage to meta-data. Once data from multiple instruments is structured through DM2 , data can be visualised by a powerful data visualisation and business intelligence software Tableau. This helps the domain experts in medicine manufacturing to see and understand their data. It provides an intuitive and interactive way to explore, analyze, and visualise data from various sources. It allows users to create visualisations without the need for extensive programming skills. Medicine manufacturing data can also be accessed by domain experts in Artificial Intelligence for modelling.
Institution: University of Strathclyde
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7204063930