Quality by digital design to accelerate sustainable medicines development
Mustoe, Chantal L. and Turner, Alice J. and Urwin, Stephanie J. and Houson, Ian and Feilden, Helen and Markl, Daniel and Al Qaraghuli, Mohammed M. and Chong, Magdalene W.S. and Robertson, Murray and Nordon, Alison and Johnston, Blair F. and Brown, Cameron J. and Robertson, John and Adjiman, Claire and Batchelor, Hannah and Benyahia, Brahim and Bresciani, Massimo and Burcham, Christopher L. and Cardona, Javier and Cottini, Ciro and Dunn, Andrew S. and Fradet, David and Halbert, Gavin W. and Henson, Mark and Hidber, Pirmin and Langston, Marianne and Lee, Ye Seol and Li, Wei and Mantanus, Jérôme and McGinty, John and Mehta, Bhavik and Naz, Tabbasum and Ottoboni, Sara and Prasad, Elke and Quist, Per-Ola and Reynolds, Gavin K. and Rielly, Chris and Rowland, Martin and Schlindwein, Walkiria and Schroeder, Sven L.M. and Sefcik, Jan and Settanni, Ettore and Siddique, Humera and Smith, Kenneth and Smith, Rachel and Srai, Jagjit Singh and Thorat, Alpana A. and Vassileiou, Antony and Florence, Alastair J. (2025) Quality by digital design to accelerate sustainable medicines development. International Journal of Pharmaceutics. 125625. ISSN 1873-3476 (https://doi.org/10.1016/j.ijpharm.2025.125625)
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Abstract
We present a shared industry-academic perspective on the principles and opportunities for Quality by Digital Design (QbDD) as a framework to accelerate medicines development and enable regulatory innovation for new medicines approvals. This approach exploits emerging capabilities in industrial digital technologies to achieve robust control strategies assuring product quality and patient safety whilst reducing development time/costs, improving research and development efficiency, embedding sustainability into new products and processes, and promoting supply chain resilience. Key QbDD drivers include the opportunity for new scientific understanding and advanced simulation and model-driven, automated experimental approaches. QbDD accelerates the identification and exploration of more robust design spaces. Opportunities to optimise multiple objectives emerge in route selection, manufacturability and sustainability whilst assuring product quality. Challenges to QbDD adoption include siloed data and information sources across development stages, gaps in predictive capabilities, and the current extensive reliance on empirical knowledge and judgement. These challenges can be addressed via QbDD workflows; model-driven experimental design to collect and structure findable, accessible, interoperable and reusable (FAIR) data; and chemistry, manufacturing and control ontologies for shareable and reusable knowledge. Additionally, improved product, process, and performance predictive tools must be developed and exploited to provide a holistic end-to-end development approach.
ORCID iDs
Mustoe, Chantal L.






















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Item type: Article ID code: 92725 Dates: DateEvent24 April 2025Published24 April 2025Published Online18 April 2025AcceptedSubjects: Medicine > Pharmacy and materia medica Department: Faculty of Science > Strathclyde Institute of Pharmacy and Biomedical Sciences
Faculty of Engineering > Chemical and Process Engineering
Faculty of Science > Pure and Applied Chemistry
Technology and Innovation Centre > Continuous Manufacturing and Crystallisation (CMAC)
Strategic Research Themes > Advanced Manufacturing and Materials
Strategic Research Themes > Measurement Science and Enabling Technologies
Technology and Innovation Centre > BionanotechnologyDepositing user: Pure Administrator Date deposited: 30 Apr 2025 10:45 Last modified: 30 Apr 2025 10:45 URI: https://strathprints.strath.ac.uk/id/eprint/92725