ReviewFrontiers in drug delivery2026
Advancing transdermal drug delivery through 4D bioprinting and dynamic skin modelling.
Review in Frontiers in drug delivery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
1 author.
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Abstract
Transdermal drug delivery (TDD) provides a non-invasive approach for sustained drug release. However, traditional models present limitations in capturing the dynamic interactions between drugs, skin and the environmental factors over time. The incorporation of time as a critical dimension alongside three-dimensional (3D) structures in four-dimensional (4D) modelling offers a promising solution by simulating the temporal evolution of drug diffusion and skin responses. In this review, 4D modelling refers to the computational and material-based systems that incorporate time-dependent changes whereas 4D bioprinting specifically involves fabrication of dynamic, stimuli-responsive skin constructs. Together, these approaches create temporally adaptive models which are ideal for simulating drug permeation and skin behaviour. This review will explore the potential application of 4D modelling in TDD, primarily focusing on and emphasising its capacity to predict drug permeation, release kinetics and skin interactions in response to variables such as hydration, temperature and mechanical impact. 4D bioprinting provides a more accurate depiction of real-world scenarios, enabling researchers to optimise drug formulations whilst minimising reliance on empirical testing. Despite challenges associated with cost and complexity, 4D modelling presents considerable opportunities, particularly in the advancement of personalised medicine. The integration of artificial intelligence could further enhance these models, resulting in more accurate predictions. By addressing both spatial and temporal dimensions, 4D constructs will continue to evolve and have the potential to transform TDD; particularly in the context of individualised treatment where dynamic patient-specific variables can be integrated to develop more effective and tailored treatments.
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