While conventionally manufactured metallic biomaterials can hardly meet all the requirements for bone implants including complex geometry, exact dimensions, adequate biodegradability, bone-matching mechanical properties, and biological function, two additional tools have recently appeared in the arsenal of biomaterials scientists which promise to deliver the desired combination of properties. First, the unique mechanical, electrical, and biological properties of graphene (Gr) and its derivatives (GDs), e.g., a Young's modulus up to 1 TPa, can be utilized to create metal matrix composites in which GDs of varied contents (typically not more than 2 wt%), sizes (lateral sizes from a few nanometers to several micrometers), surface areas (up to the theoretical value of 2630 m²/g), and layer numbers (typically up to 10) are embedded in the biodegradable metal matrix, thereby endowing the composite implants with extraordinary properties. Second, the distinct advantages of additive manufacturing (AM) make it possible for GD-containing composite materials to precisely mimic the complex shapes and structures of bones at multiple length scales. Here, a comprehensive review of the recent advances in the development of GD-containing biodegradable metal matrix composites (GBMMCs), ranging from composite fabrication, including composite powder preparation, and AM processes, to the evaluation of AM composites in terms of their mechanical and biological properties, is presented. Furthermore, the constraints in processing composite powders, the advantages and disadvantages of applicable AM techniques, and the mechanisms of mechanical reinforcement, biodegradation modulation, osteogenesis improvement, and cytotoxicity/antibacterial balance are critically analyzed. Thereafter, the foreseeable challenges faced in the development of the next-generation of bone implants based on GBMMCs are presented and some future directions of research are identified.

The authors regret that the affiliation of Joseph Ahn was incorrectly listed in the original article. The correct affiliation is:

Independent Researcher, Hwaseong-si, South Korea

This error has now been corrected in the online version of the article.

The authors would like to apologise for any inconvenience caused.

This Roadmap surveys the diversity of different approaches for characterising, modelling and designing metamaterials. It contains articles covering the wide range of physical settings in which metamaterials have been realised, from acoustics and electromagnetics to water waves and mechanical systems. In doing so, we highlight synergies between the many different physical domains and identify commonality between the main challenges. The articles also survey a variety of different strategies and philosophies, from analytic methods such as classical homogenisation to numerical optimisation and data-driven approaches. We highlight how the challenging and many-degree-of-freedom nature of metamaterial design problems call for techniques to be used in partnership, such that physical modelling and intuition can be combined with the computational might of modern optimisation and machine learning to facilitate future breakthroughs in the field.

Organoids are innovative three-dimensional and self-organizing cell cultures of various lineages that can be used to study diverse tissues and organs. Human organoids have dramatically increased our understanding of developmental and disease biology. They provide a patient-specific model to study known diseases, with advantages over animal models, and can also provide insights into emerging and future health threats related to climate change, zoonotic infections, environmental pollutants or even microgravity during space exploration. Furthermore, organoids show potential for regenerative cell therapies and organ transplantation. Still, several challenges for broad clinical application remain, including inefficiencies in initiation and expansion, increasing model complexity and difficulties with upscaling clinical-grade cultures and developing more organ-specific human tissue microenvironments. To achieve the full potential of organoid technology, interdisciplinary efforts are needed, integrating advances from biology, bioengineering, computational science, ethics and clinical research. In this Review, we showcase pivotal achievements in epithelial organoid research and technologies and provide an outlook for the future of organoids in advancing human health and medicine.

Incorporating shape-morphing capability into 3D microprinting enables the fabrication of 4D-printed microarchitectures as proof-of-concept actuators for potential use in soft robotics and microfluidic systems. The ability of these 3D microstructures to actuate rapidly and reversibly enables precise, non-invasive, and controllable deformation. In this study, we investigated the programmable shape-morphing behavior of 3D microarchitectures fabricated using two-photon polymerization (2PP) of a well-established temperature-responsive hydrogel, poly(N-isopropylacrylamide) (pNIPAM). We first systematically studied how 2PP 3D printing parameters (e.g., laser power, scanning speed) and the chemical composition of pNIPAM, including monomer and crosslinker, influence the shape morphing of bilayer microstructures within a temperature range of ~ 32 °C to 60 °C. The (thermo)mechanical properties of the hydrogels, including the Young’s modulus, thermal expansion coefficients, and angular deflection, were also measured at different laser doses and temperatures. Based on these experimental measurements, we calibrated a thermomechanical model capable of predicting the shape morphing of 4D-printed microarchitectures. These microarchitectures served as proof-of-concept actuators, demonstrating the potential of programmable microscale soft robotics and microfluidic systems. The findings provide design guidelines for engineering stimuli-responsive 3D microstructures, highlighting limitations and opportunities for future integration into functional soft robotic or microfluidic systems made of a single material.

Existing deep learning (DL) networks are primarily trained on adult datasets and may not always generalize to pediatric populations, where growth plays a major role. Here, we investigated improving semantic segmentation outcomes of pediatric hand phalanges from radiographs without relying on fully pediatric training datasets, which are scarce. First, alternative DL networks (FCN-8, FCN-32, U-Net, Inception U-Net, and DeepLabv3+) were trained with manually segmented radiographs of near-skeletally-mature (NSM) subjects and their performances were evaluated using mean intersection-over-union (Mean IoU) and multiclass Dice scores. DeepLabv3+ and Inception U-Net performed the best for NSM segmentation, with Mean IoU scores of 0.899 ± 0.035 and 0.887 ± 0.062, respectively. These networks were then used to investigate zero pediatric data (scaling-based data augmentation) and minimal pediatric data (incremental pediatric data substitution) approaches to improve age-domain generalizability. The minimal pediatric data approach proved effective, with a 20 % pediatric data inclusion leading to an up to 21.1 % increase in Mean IoU for pediatric subjects compared to networks trained exclusively on NSM subjects. Furthermore, no adverse effects of this approach were found when tested on NSM subjects, and there were even improvements in performance for Inception U-Net. To conclude, we highlight that networks utilizing multi-scale filters perform best for the semantic segmentation of hand phalanges. We further demonstrate that a minimal inclusion of pediatric training data can markedly improve age-domain generalizability for semantic segmentation tasks. This removes the difficult task of gathering large training datasets of pediatric subjects, which is often impractical, if not impossible.

Additively manufactured (AM) biodegradable zinc alloys hold huge potential as promising candidates for bone defect and fracture repair, thanks to their suitable biodegradation rates and acceptable biocompatibility. However, the mechanical properties of AM zinc alloys developed so far, ductility in particular, fall short of the requirements for bone substitution. Here, we present Zn-1Mn and Zn-1Mn-0.4Mg alloy implants with unique microstructures, fabricated using laser powder bed fusion (LPBF). Notably, the LPBF Zn-Mn-Mg alloy exhibited an extraordinary balance of strength and ductility, with an ultimate tensile strength of 289 MPa, yield strength of 213.5 MPa, and elongation over 20 %, outperforming all previously reported AM zinc alloys. The simultaneously enhanced strength and ductility of the ternary alloy were attributed to the strong grain-refining effect of the Mg₂Zn₁₁ second phase and the synthetic strengthening caused by the dispersion of the MnZn₁₃ and Mg₂Zn₁₁ second phases inside the grains and at the grain boundaries. In addition, both alloys had similar rates of in vitro biodegradation (∼0.15 mm/year), properly aligned with the bone remodeling process, while also demonstrating favorable biocompatibility and upregulating multiple osteogenic markers. The Zn-Mn-Mg alloy showed even better osteogenic potential than the Zn-Mn alloy, owing to the addition of Mg. The combined attributes of the LPBF Zn-Mn-Mg ternary alloy indicated huge potential for its use as a bone repair material, especially for load-bearing bone fixation. Statement of significance: The mechanical properties of previously developed additively manufactured biodegradable zinc alloys, especially ductility, have not met the requirements for bone repair. Using laser powder bed fusion (LPBF), we fabricated Zn-1Mn and Zn-1Mn-0.4Mg alloy implants with unique microstructures. The LPBF Zn-Mn-Mg alloy demonstrated an exceptional balance of strength and ductility, achieving a tensile strength of 289 MPa, yield strength of 213.5 MPa, and elongation over 20 %, surpassing all reported AM zinc alloys. This study is the first to produce a directly printed biodegradable alloy meeting the mechanical requirements for bone fixation devices without post-processing. Additionally, the alloy exhibited moderate a biodegradation rate and excellent biocompatibility, underscoring its potential for load-bearing bone repair applications.

In this study, by mimicking bone tissue adaptation, we introduce a hierarchical design approach to optimize the mechanical performance of auxetic metamaterials. Using a multi-material voxel-based 3D printer, we rationally position soft and hard phases at the voxel level based on a bone-inspired remodeling algorithm that maintains the homeostasis of strain energy density. This process introduces an additional length scale within the structure, leading to (1) a significant expansion of the envelope of achievable elastic properties, (2) more homogeneous strain energy distributions, and (3) up to 78 % stronger metamaterials compared to initial designs. Our results demonstrate that this bone-mimicking design approach enables the emergence of an intermediate length scale between the unit cell and voxel scales, which is responsible for the observed improvements in mechanical performance. Taken together, these findings highlight the potential of biomimetic remodeling for the rational design of stress-worthy, multiscale mechanical metamaterials that combine unusual elastic properties with high mechanical performance.

High-performance soft–hard interfaces are inherently difficult to fabricate due to the dissimilar mechanical properties of both materials, especially when connecting extremely soft biomaterials, such as hydrogels, to much harder biomaterials, such as rigid polymers. Nevertheless, there is significant clinical demand for synthetic soft–hard interfaces. Here, soft–hard interface geometries are proposed, designed with the aid of computational analyses and fabricated as 3D-printed hydrogel-to-polylactide (PLA) structures. Two primary interlocking geometries (i.e., anti-trapezoidal (AT) and double-hook (DH)) are used to study the envelope of 2.5D geometric interlocking designs, fabricated through hybrid 3D printing, combining pneumatic extrusion with fused deposition modeling. Finite-element analysis, uniaxial tensile tests, and digital image correlation (DIC) are used to characterize the geometries and identify parameters that significantly influence their mechanical performance. These findings reveal significant differences between geometric designs, where DH geometries performed significantly better than AT geometries, exhibiting a 190% increase in the maximum force, F_max, and a 340% increase in the fracture toughness, W. Compared to the control groups (i.e., flat, inset, and 90° interfaces), F_max and W values increased by 500%–990% and 350%–1200%, respectively. The findings of this study can serve as a guideline for the design and fabrication of efficient soft–hard interfaces with performances close to predicted values.

The development of high-fidelity three-dimensional (3D) tissue models can minimize the need for animal models in clinical medicine and drug development. However, physical limitations regarding the distances within which diffusion processes are effective impose limitations on the size of such constructs. That is because larger-size constructs experience necrosis, especially in their centers, due to the cells residing deep inside such constructs not receiving enough oxygen and nutrients. This hampers the sustained in vitro growth of the tissues which is required for achieving functional microtissues. To address this challenge, we used three types of 3D printing technologies to create perfusable networks at different length scales and integrate them into such constructs. Toward this aim, networks incorporating porous conduits with increasingly complex configurations were designed and fabricated using fused deposition modeling, stereolithography, and two-photon polymerization while optimizing the printing conditions for each of these technologies. Furthermore, following network embedding in hydrogels, contrast agent-enhanced micro-computed tomography and confocal fluorescence microscopy were employed to characterize one of the essential network functionalities, namely the diffusion function. The investigations revealed the effects of various design parameters on the diffusion behavior of the porous conduits over 24 h. We found that the number of pores exerts the most significant influence on the diffusion behavior of the contrast agent, followed by variations in the pore size and hydrogel concentration. The analytical approach and the findings of this study establish a solid base for a new technological platform to fabricate perfusable multiscale 3D porous networks with complex designs while enabling the customization of diffusion characteristics to meet specific requirements for sustained in vitro tissue growth. Statement of significance: This study addresses an essential limitation of current 3D tissue engineering, namely, sustaining tissue viability in larger constructs through optimized nutrient and oxygen delivery. By utilizing advanced 3D printing techniques this research proposes the fabrication of perfusable, multiscale and customizable networks that enhance diffusion and enable cell access to essential nutrients throughout the construct. The findings highlighted the role of network characteristics on the diffusion of a model compound within a hydrogel matrix. This work represents a promising technological platform for creating advanced in vitro 3D tissue models that can reduce the use of animal models in research involving tissue regeneration, disease models and drug development.

4D (bio-)printing endows 3D printed (bio-)materials with multiple functionalities and dynamic properties. 4D printed materials have been recently used in biomedical engineering for the design and fabrication of biomedical devices, such as stents, occluders, microneedles, smart 3D-cell engineered microenvironments, drug delivery systems, wound closures, and implantable medical devices. However, the success of 4D printing relies on the rational design of 4D printed objects, the selection of smart materials, and the availability of appropriate types of external (multi-)stimuli. Here, this work first highlights the different types of smart materials, external stimuli, and design strategies used in 4D (bio-)printing. Then, it presents a critical review of the biomedical applications of 4D printing and discusses the future directions of biomedical research in this exciting area, including in vivo tissue regeneration studies, the implementation of multiple materials with reversible shape memory behaviors, the creation of fast shape-transformation responses, the ability to operate at the microscale, untethered activation and control, and the application of (machine learning-based) modeling approaches to predict the structure–property and design–shape transformation relationships of 4D (bio)printed constructs.

Effective treatment of large acetabular defects remains among the most challenging aspects of revision total hip arthroplasty (THA), due to the deficiency of healthy bone stock and degradation of the support columns. Generic uncemented components, which are favored in primary THA, are often unsuitable in revision cases, where the bone-implant contact may be insufficient for fixation, without significant reaming of the limited residual bone. This study presents a computational design strategy for automatically generating patient-specific implants that simultaneously maximize the bone-implant contact area, and minimize bone reaming while ensuring insertability. These components can be manufactured using the same additive manufacturing methods as porous components and may reduce cost and operating-time, compared to existing patient-specific systems. This study compares the performance of implants generated via the proposed method to optimally fitted hemispherical implants, in terms of the achievable bone-implant contact surface, and the volume of reamed bone. Computer-simulated results based on the reconstruction of a set of 15 severe pelvic defects (Paprosky 2A-3B) suggest that the patient-specific components increase bone-implant contact by 63% (median: 63%; SD: 44%; 95% CI: 52.3%–74.0%; RMSD: 42%), and reduce the volume of reamed bone stock by 97% (median: 98%; SD: 4%; 95% CI: 95.9%–97.4%; RMSD: 3.7%).

The existing 3D printing methods exhibit certain fabrication-dependent limitations for printing curved constructs that are relevant for many tissues. Four-dimensional (4D) printing is an emerging technology that is expected to revolutionize the field of tissue engineering and regenerative medicine (TERM). 4D printing is based on 3D printing, featuring the introduction of time as the fourth dimension, in which there is a transition from a 3D printed scaffold to a new, distinct, and stable state, upon the application of one or more stimuli. Here, we present an overview of the current developments of the 4D printing technology for TERM, with a focus on approaches to achieve temporal changes of the shape of the printed constructs that would enable biofabrication of highly complex structures. To this aim, the printing methods, types of stimuli, shape-shifting mechanisms, and cell-incorporation strategies are critically reviewed. Furthermore, the challenges of this very recent biofabrication technology as well as the future research directions are discussed. Our findings show that the most common printing methods so far are stereolithography (SLA) and extrusion bioprinting, followed by fused deposition modelling, while the shape-shifting mechanisms used for TERM applications are shape-memory and differential swelling for 4D printing and 4D bioprinting, respectively. For shape-memory mechanism, there is a high prevalence of synthetic materials, such as polylactic acid (PLA), poly(glycerol dodecanoate) acrylate (PGDA), or polyurethanes. On the other hand, different acrylate combinations of alginate, hyaluronan, or gelatin have been used for differential swelling-based 4D transformations. TERM applications include bone, vascular, and cardiac tissues as the main target of the 4D (bio)printing technology. The field has great potential for further development by considering the combination of multiple stimuli, the use of a wider range of 4D techniques, and the implementation of computational-assisted strategies.

Emerging 4D printing techniques have enabled the realization of smart materials whose shape or properties can change with time. Two important phenomena play important roles in the 4D printing of shape memory polymeric materials. First, the anisotropic deformation of the printed filaments due to residual stresses can be harnessed to create out-of-plane shape transformations. Second, the unavoidable formation of micro-defects during the printing processes often affects the programmability of the printed object. Here, we propose a design approach that harnesses these two effects occurring during fused deposition modeling to create tailor-made curved geometries from initially 2D flat disks. We first determined the size and distribution of the imperfections formed within printed structures by varying two printing parameters namely the printing speed and the number of printed materials. Spatially varying the printing speed and combining polylactic acid filaments with a softer material without shape memory properties allowed us to cover a variety of shapes from negative to positive values of the mean and Gaussian curvature. We propose an analytical model to calculate the magnitude of the maximum out-of-plane deformation from the anisotropic expansion factor of the constituting microstructures. Furthermore, we develop computational models to predict the complex shape-changing of thermally actuated 4D printed structures given the distribution of rationally introduced imperfections and we demonstrate the potential applications of such defect-based metamaterials in drug delivery systems.

Temporomandibular joint (TMJ) replacement prostheses often face limitations in accommodating translational movements, leading to unnatural kinematics and loading conditions, which affect functionality and longevity. Here, we investigate the potential of functionally graded materials (FGMs) in TMJ prostheses to enhance mandibular kinematics and reduce joint reaction forces. We develop a functionally graded artificial cartilage for the TMJ implant and evaluate five FGM designs: hard, hard-soft, and three FGM gradients with gradual transitions from 90% hard material to 0%, 10%, and 20%. These designs are 3D printed, mechanically tested under quasi-static compression, and simulated under physiological conditions. Results from computational modeling and experiments are compared to an intact mandible during incisal clenching and left group biting. The FGM design with a transition from 90% to 0% hard material improves kinematics by 19% and decreases perfomance by 3%, reduces joint reaction forces by 8% and 10%, and increases mandibular movement by 20% and 88% during incisal clenching and left group biting, respectively. These findings provide valuable insights for next-generation TMJ implants.

Additively manufactured (AM) biodegradable porous iron-manganese (FeMn) alloys have recently been developed as promising bone-substituting biomaterials. However, their corrosion fatigue behavior has not yet been studied. Here, we present the first study on the corrosion fatigue behavior of an extrusion-based AM porous Fe35Mn alloy under cyclic loading in air and in the revised simulated body fluid (r-SBF), including the fatigue crack morphology and distribution in the porous structure. We hypothesized that the fatigue behavior of the architected AM Fe35Mn alloy would be strongly affected by the simultaneous biodegradation process. We defined the endurance limit as the maximum stress at which the scaffolds could undergo 3 million loading cycles without failure. The endurance limit of the scaffolds was determined to be 90 % of their yield strength in air, but only 60 % in r-SBF. No notable crack formation in the specimens tested in air was observed even after loading up to 90 % of their yield strength. As for the specimens tested in r-SBF, however, cracks formed in the specimens subjected to loads exceeding 60 % of their yield strength appeared to initiate on the periphery and propagate toward the internal struts. Altogether, the results show that the extrusion-based AM porous Fe35Mn alloy is capable of tolerating up to 60 % of its yield strength for up to 3 million cycles, which corresponds to 1.5 years of use of load-bearing implants subjected to repetitive gait cycles. The fatigue performance of the alloy thus further enhances its potential for trabecular bone substitution subjected to cyclic compressive loading. Statement of significance: Fatigue behavior of extrusion-based AM porous Fe35Mn alloy scaffolds in air and revised simulated body fluid was studied. The Fe35Mn alloy scaffolds endured 90 % of their yield strength for up to 3 × 10⁶ loading cycles in air. Moreover, the scaffolds tolerated 3 × 10⁶ loading cycles at 60 % of their yield strength in revised simulated body fluid. The Fe35Mn alloy scaffolds exhibited a capacity of withstanding 1.5-year physiological loading when used as bone implants.

The currently available treatments for inner ear disorders often involve systemic drug administration, leading to suboptimal drug concentrations and side effects. Cochlear implants offer a potential solution by providing localized and sustained drug delivery to the cochlea. While the mechanical characterization of both the implants and their constituent material is crucial to ensure functional performance and structural integrity during implantation, this aspect has been mostly overlooked. This study proposes a novel methodology for the mechanical characterization of our recently developed cochlear implant design, namely, rectangular and cylindrical, fabricated using two-photon polymerization (2 PP) with a novel photosensitive resin (IP-Q™). We used in silico computational models and ex silico experiments to study the mechanics of our newly designed implants when subjected to torsion mimicking the foreseeable implantation procedure. Torsion testing on the actual-sized implants was not feasible due to their small size (0.6 × 0.6 × 2.4 mm³). Therefore, scaled-up rectangular cochlear implants (5 × 5 × 20 mm³, 10 × 10 × 40 mm³, and 20 × 20 × 80 mm³) were fabricated using stereolithography and subjected to torsion testing. Finite element analysis (FEA) accurately represented the linear behavior observed in the torsion experiments. We then used the validated Finite element analysis models to study the mechanical behavior of real-sized implants fabricated from the IP-Q resin. Mechanical characterization of both implant designs, with different inner porous structures (pore size: 20 μm and 60 μm) and a hollow version, revealed that the cylindrical implants exhibited approximately three times higher stiffness and mechanical strength as compared to the rectangular ones. The influence of the pore sizes on the mechanical behavior of these implant designs was found to be small. Based on these findings, the cylindrical design, regardless of the pore size, is recommended for further research and development efforts.

The Poisson's ratio and elastic modulus are two parameters determining the elastic behavior of biomaterials. While the effects of elastic modulus on the cell response is widely studied, very little is known regarding the effects of the Poisson's ratio. The micro-architecture of meta-biomaterials determines not only the Poisson's ratio but also several other parameters that also influence cell response, such as porosity, pore size, and effective elastic modulus. It is, therefore, very challenging to isolate the effects of the Poisson's ratio from those of other micro-architectural parameters. Here, we computationally design meta-biomaterials with controlled Poisson's ratios, ranging between -0.74 and +0.74, while maintaining consistent porosity, pore size, and effective elastic modulus. The 3D meta-biomaterials were additively manufactured at the micro-scale using two-photon polymerization (2PP), and were mechanically evaluated at the meso‑scale. The response of murine preosteoblasts to these meta-biomaterials was then studied using in vitro cell culture models. Meta-biomaterials with positive Poisson's ratios resulted in higher metabolic activity than those with negative values. The cells could attach and infiltrate all meta-biomaterials from the bottom to the top, fully covering the scaffolds after 17 days of culture. Interestingly, the meta-biomaterials exhibited different cell-induced deformations (e.g., shrinkage or local bending) as observed via scanning electron microscopy. The outcomes of osteogenic differentiation (i.e., Runx2 immunofluorescent staining) and matrix mineralization (i.e., Alizarin red staining) assays indicated the significant potential impact of these meta-biomaterials in the field of bone tissue engineering, paving the way for the development of advanced bone meta-implants. Statement of significance: We studied the influence of Poisson's ratio on bone cell response in meta-biomaterials. While elastic modulus effects are well-studied, the impact of Poisson's ratio, especially negative values found in architected biomaterials, remains largely unexplored. The complexity arises from intertwined micro-architectural parameters, such as porosity and elastic modulus, making it challenging to isolate the Poisson's ratio. To overcome this limitation, this study employed rational computational design to create meta-biomaterials with controlled Poisson's ratios, alongside consistent effective elastic modulus, porosity, and pore size. The study reveals that two-photon polymerized 3D meta-biomaterials with positive Poisson's ratios displayed higher metabolic activity, while all the developed meta-biomaterials supported osteogenic differentiation of preosteoblasts as well as matrix mineralization. The outcomes pave the way for the development of advanced 3D bone tissue models and meta-implants.

Meta-biomaterials, engineered materials with distinctive combinations of mechanical, physical, and biological properties stemming from their micro-architecture, have emerged as a promising domain within biomedical engineering. Correspondingly, meta-implants, which serve as the device counterparts of meta-biomaterials, offer exceptional functionalities, holding great potential for addressing complex skeletal diseases. This paper presents a comprehensive overview of the various types of meta-implants, including hybrid, shape-morphing, metallic clay, and deployable meta-implants, highlighting their unprecedented properties and recent achievement in the field. This paper also delves into the potential future developments of meta-implants, addressing the exploration of multi-functionalities in meta-biomaterials and their applications in diverse biomedical fields.

This study proposes a new concept for an on-demand drug releasing device intended for integration into additively manufactured (i.e., 3D printed) orthopedic implants. The system comprises a surface with conduits connected to a subsurface reservoir used for storage and on-demand release of antimicrobial agents, covered with a cap that prevents the antibacterial agents from being released until alternating magnetic field (AMF) raises the temperature of the cap, thus, releasing the stored drug. To demonstrate this concept, Ti6Al4V specimens are directly 3D printed using selective laser melting and their surface, reservoirs, and drug releasing properties are characterized. A new synthetic antimicrobial peptide, SAAP-148, is thereafter tested for its cytotoxic, osteogenic, and immunomodulatory effects at concentrations relevant for its minimal bactericidal concentration (MBC) and is compared with its natural analogue, LL-37. The results showed that AMF successfully activated the release from the 3D printed loaded samples. Both peptides demonstrated to be non-cytotoxic within the MBC levels for macrophages and preosteoblasts and did not influence their osteoimmunomodulatory behavior. The findings of this study indicate that the proposed concept is technically feasible and has the potential to be used for the development of bone implants with on-demand delivery systems to fight IAI without systemic or continuous local release of antibiotics.