Multiphysics modelling enhanced by imaging and artificial intelligence for personalised cancer nanomedicine: Foundations for clinical digital twins.
Authors
Affiliations (5)
Affiliations (5)
- Department of Physics, Toronto Metropolitan University, Toronto, ON, Canada; Institute for Biomedical Engineering, Science & Technology (iBEST), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada.
- Biofluids Research Lab, Department of Mechanical Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad, India.
- School of Chemical Engineering, Chonnam National University, Gwangju, Republic of Korea.
- Department of Applied Mathematics, University of Waterloo, Waterloo, ON, Canada.
- School of Engineering, University of Aberdeen, Old Aberdeen Campus, Aberdeen, UK. Electronic address: [email protected].
Abstract
Nano-sized drug delivery systems have emerged as a more effective, versatile means for improving cancer treatment. However, the complexity of drug delivery to cancer involves intricate interactions between physiological and physicochemical processes across various temporal and spatial scales. Relying solely on experimental methods for developing and clinically translating nano-sized drug delivery systems is economically unfeasible. Multiphysics models, acting as open systems, offer a viable approach by allowing control over the individual and combined effects of various influencing factors on drug delivery outcomes. This provides an effective pathway for developing, optimising, and applying nano-sized drug delivery systems. These models are specifically designed to uncover the underlying mechanisms of drug delivery and to optimise effective delivery strategies. This review outlines the diverse applications of multiphysics simulations in advancing nanos-sized drug delivery systems for cancer treatment. The methods to develop these models and the integration of emerging technologies (i.e., medical imaging and artificial intelligence) are also addressed towards digital twins for personalised clinical translation of cancer nanomedicine. Multiphysics modelling tools are expected to become a powerful technology, expanding the scope of nano-sized drug delivery systems, thereby greatly enhancing cancer treatment outcomes and offering promising prospects for more effective patient care.