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Hydrogels are transformative three-dimensional polymeric networks that replicate the extracellular matrix owing to their high-water content, biocompatibility, and tunable physicochemical properties. Evolving beyond conventional applications in wound dressings, contact lenses, and basic drug depots, hydrogel systems have advanced into implantable designs capable of long-term physiological integration. Surgically placed or delivered via minimally invasive techniques, implantable hydrogels (IHGs) enable dynamic tissue interactions, biodegradability, self-healing behaviour, and sustained drug release. The emergence of multifunctional, stimuli-responsive variants of IHGs has further expanded their therapeutic, diagnostic, and regenerative potential while preserving their essential material attributes. By coupling stimuli responsiveness with patient-specific physiological cues, IHGs embody the "smart" nature of next-generation biomaterials, advancing personalized medicine through adaptive therapeutic delivery, real-time functional responsiveness, and dynamic biological integration. This review summarizes recent progress in the design and fabrication of IHGs, emphasizing 3D and 4D printing technologies and the development of hydrogel inks optimized for mechanical robustness, shape fidelity, and biological performance. Applications are discussed across four major areas: (i) hydrogel coatings for medical implants, (ii) injectable hydrogels for infection control, (iii) bone-regenerative scaffolds, and (iv) health-monitoring systems. Finally, the review addresses key translational challenges, including scalable manufacturing, long-term stability, and regulatory considerations, while outlining future directions toward smart, multifunctional implantable hydrogels capable of integrated biosensing and responsive therapeutic delivery. Distinct from previous reviews, this work combines implantability and multifunctionality/smartness within a single framework, highlighting how hydrogels can achieve durable physiological integration while dynamically adapting to patient-specific cues.
Nagay et al. (Tue,) studied this question.