Speaker
Description
Microneedle (MN) technologies are emerging as a transformative alternative to conventional hypodermic needles, addressing long-standing challenges associated with pain, needle phobia, needle-stick injuries, and poor patient compliance. By minimally breaching the stratum corneum, microneedles enable safe, painless, self-administered delivery of drugs, vaccines, and cosmetics, while also enhancing hygiene and accessibility. Advances in fabrication—ranging from polymeric and ceramic microneedles to hollow, dissolving, and hydrogel-forming platforms—have significantly expanded their potential applications across healthcare and industry. Despite rapid technological progress, MN design has largely relied on empirical trial-and-error, resulting in high development costs, lengthy design cycles, and uncertain performance due to variability in skin properties, materials, and formulations.
This presentation introduces the concept of Needleless Futures and advocates a shift from empirical development to predictive, model-driven MN innovation. It will present state-of-the-art mathematical and computational modelling frameworks that capture the coupled physics governing microneedle performance, including insertion mechanics, fluid flow, drug transport, polymer dissolution, and swelling behaviour. Modelling strategies for hollow, dissolving, super-swelling, hydrogel-forming, and phase-transition microneedles will be discussed, demonstrating how dose–delivery relationships, insertion forces, and structural integrity can be accurately predicted. Solid-mechanics and fluid–structure interaction models will be highlighted as tools for establishing robust design rules and optimising polymer-based microneedle platforms.
The talk will further showcase case studies—such as wrinkle-removal applications and industrially relevant drug-delivery systems to illustrate how predictive modelling informs material selection, geometry optimisation, and performance enhancement beyond healthcare. Finally, a roadmap will be presented for integrating experimentally validated models with optimisation and data-driven tools, positioning predictive modelling as a catalyst for accelerating innovation, supporting regulatory approval, and enabling equitable global access to advanced, needle-free therapies.
| Country | United Kingdom |
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