Many-objective process optimisation with constraints for continuous tableting lines : a case study in lovastatin

Tools

Wu, Kai Eivind and Brown, Cameron J. and Robertson, Murray N. and Johnston, Blair F. and Panoutsos, George (2022) Many-objective process optimisation with constraints for continuous tableting lines : a case study in lovastatin. In: CMAC Annual Open Day 2022, 2022-05-16 - 2022-05-18.

[thumbnail of Wu-etal-CMAC-2022-Many-objective-process-optimisation-with-constraints]
Preview
 Text. Filename: Wu_etal_CMAC_2022_Many_objective_process_optimisation_with_constraints.pdf
Final Published Version
License: Strathprints license 1.0
Download (1MB)| Preview

Abstract

Background: Digital design, assisted by data science, experienced significant progress over recent years within the continuous manufacturing in the pharmaceutical sector. Research Objective: The project focuses the fundamental research on robust numerical and visual performance indicators for assessing performance for many-objective optimisation algorithms under multiple constraints Methods: A surrogate model-based machine learning algorithm is used, to train data-driven models that capture the manufacturing process behaviour. Then use optimisation algorithms to get optimal solutions. Results: >75% dissolution release could be achieved in 45 minutes.

ORCID iDs

Wu, Kai Eivind, Brown, Cameron J. ORCID logoORCID: https://orcid.org/0000-0001-7091-1721, Robertson, Murray N. ORCID logoORCID: https://orcid.org/0000-0001-9543-7667, Johnston, Blair F. ORCID logoORCID: https://orcid.org/0000-0001-9785-6822 and Panoutsos, George;

Persistent Identifier

https://doi.org/10.17868/strath.00081659
CORE (COnnecting REpositories)