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Chronic diabetic wounds are notoriously difficult to treat due to impaired healing, prolonged inflammation, and an elevated risk of infection. In response to this challenge, researchers have created an artificial intelligence (AI)-assisted, 4D-printed microneedle patch capable of actively closing wounds, combating bacterial infections, and enhancing tissue regeneration. Drawing inspiration from the carnivorous plant Drosera capensis, the innovative platform integrates shape-memory materials, adhesive DNA-based nanoparticles, and antibacterial zinc coatings, demonstrating how AI can help translate natural biological mechanisms into advanced, programmable medical technologies.

Chronic wounds represent a significant burden in healthcare, particularly among individuals with diabetes, where healing is often delayed and complications are common. Conventional wound-closure methods—including sutures, staples, and adhesive dressings—can physically approximate wound edges but lack the ability to dynamically interact with the body's healing environment. As a result, researchers have increasingly focused on developing adaptive biomaterials that can both respond to physiological conditions and actively support tissue repair while minimizing infection.

A research team led by Associate Professor Hyun-Do Jung at Hanyang University has developed an AI-guided microneedle system that changes shape at normal body temperature (37°C), enabling it to mechanically assist wound closure while simultaneously delivering regenerative and antibacterial therapies. The study brings together several cutting-edge disciplines, including artificial intelligence, 4D printing, biomimetic design, DNA nanotechnology, and advanced surface engineering, within a single therapeutic platform.

The research, published online on March 30, 2026, appeared in the journal Advanced Materials.

The concept was inspired by the carnivorous plant Drosera capensis, which captures prey through a sophisticated combination of movement, adhesion, and protective mechanisms. Mimicking these biological features, the researchers engineered shape-memory microneedles that actively bend after being inserted into tissue. These structures were fabricated using 4D printing technology, which enables printed materials to undergo programmed shape transformations in response to environmental triggers.

To optimize the performance of the microneedles, the team employed machine-learning algorithms to predict how the printed materials would recover their shape under physiological conditions, significantly reducing the need for extensive experimental testing. By evaluating the effects of material composition and manufacturing parameters, the researchers identified an ideal processing window that provided both mechanical durability and rapid shape recovery. Among the AI models tested, Gaussian Process Regression delivered the highest predictive accuracy and the most reliable estimates of uncertainty.

According to Dr. Jung, the study extends beyond traditional biomimicry by leveraging artificial intelligence to convert nature-inspired concepts into practical biomedical technologies. He emphasized that the significance of the work lies not only in its biological inspiration, but also in AI's ability to transform those inspirations into predictable, programmable, and clinically applicable therapeutic systems.

Laboratory testing demonstrated that the microneedles quickly reverted to their programmed curved configuration at body temperature, facilitating wound closure and maintaining stable contact with surrounding tissues. The system also incorporated adhesive DNA nanoparticles to stimulate tissue regeneration and a zinc-based surface treatment to provide antimicrobial protection. Experimental results showed sustained DNA delivery, positive cellular responses from endothelial cells and fibroblasts involved in wound repair, and strong antibacterial activity against both Escherichia coli and Staphylococcus aureus.

In preclinical wound-healing studies, the integrated microneedle platform significantly accelerated wound closure and promoted more effective tissue regeneration compared with conventional treatment methods.

Dr. Jung also noted that the AI-assisted 4D-printing approach could have broader applications beyond wound care, including the development of soft biomedical robots and tissue-interfacing devices that require programmable movement, controlled shape changes, and reliable interaction with biological tissues.

Although additional studies are necessary before the technology can enter clinical practice, the platform may eventually be adapted for smart wound dressings, implantable devices, tissue scaffolds, and stents that respond dynamically to their biological environment. Over the long term, this approach could contribute to the emergence of intelligent biomaterials designed to improve healing outcomes and reduce medical complications.

Reference
Original Article: AI–Guided 4D Printing of Carnivorous Plants–Inspired Microneedles for Accelerated Wound Healing
Journal: Advanced Materials
DOI: 10.1002/adma.202523665