The Use of Computational Approaches to Design Nanodelivery Systems Article Swipe
Abedalrahman Abughalia
,
Mairead Flynn
,
Paul F. A. Clarke
,
Darren Fayne
,
Oliviero L. Gobbo
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/nano15171354
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/nano15171354
Nano-based drug delivery systems present a promising approach to improve the efficacy and safety of therapeutics by enabling targeted drug transport and controlled release. In parallel, computational approaches—particularly Molecular Dynamics (MD) simulations and Artificial Intelligence (AI)—have emerged as transformative tools to accelerate nanocarrier design and optimise their properties. MD simulations provide atomic-to-mesoscale insights into nanoparticle interactions with biological membranes, elucidating how factors such as surface charge density, ligand functionalisation and nanoparticle size affect cellular uptake and stability. Complementing MD simulations, AI-driven models accelerate the discovery of lipid-based nanoparticle formulations by analysing vast chemical datasets and predicting optimal structures for gene delivery and vaccine development. By harnessing these computational approaches, researchers can rapidly refine nanoparticle composition to improve biocompatibility, reduce toxicity and achieve more precise drug targeting. This review synthesises key advances in MD simulations and AI for two leading nanoparticle platforms (gold and lipid nanoparticles) and highlights their role in enhancing therapeutic performance. We evaluate how in silico models guide experimental validation, inform rational design strategies and ultimately streamline the transition from bench to bedside. Finally, we address key challenges such as data scarcity and complex in vivo dynamics and propose future directions for integrating computational insights into next generation nanodelivery systems.
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All OpenAlex metadata
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The Use of Computational Approaches to Design Nanodelivery SystemsWork title
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reviewOpenAlex work type
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enPrimary language
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2025Year of publication
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2025-09-03Full publication date if available
- Authors
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Abedalrahman Abughalia, Mairead Flynn, Paul F. A. Clarke, Darren Fayne, Oliviero L. GobboList of authors in order
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https://doi.org/10.3390/nano15171354Publisher landing page
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| corresponding_author_ids | https://openalex.org/A5066223674, https://openalex.org/A5083612858 |
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| corresponding_institution_ids | https://openalex.org/I205274468, https://openalex.org/I4210154619, https://openalex.org/I42934936 |
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| citation_normalized_percentile.is_in_top_10_percent | False |