本レビューでは、微小環境の調節、刺激応答性、免疫工学、3D/4Dプリンティング、人工知能(AI)支援設計、および個別化された骨修復におけるトランスレーショナルな課題に焦点を当て、骨再生のためのスマートバイオマテリアル戦略について要約します。
本レビューでは、微小環境の調節、刺激応答性、免疫工学、3D/4Dプリンティング、人工知能(AI)支援設計、および個別化された骨修復におけるトランスレーショナルな課題に焦点を当て、骨再生のためのスマートバイオマテリアル戦略について要約します。
スマートバイオマテリアルの急速な進化により、複雑な骨欠損、偽関節、腫瘍切除後の再建に対する新たな治療手段が開拓されています。従来の骨代替材は、生物活性の不足、機械的特性の不整合、および治癒マイクロ環境を調節する能力の欠如に悩まされることが多くありました。対照的に、スマートバイオマテリアルは、外部刺激(光、電気、磁場、または機械的な力)や内部シグナル(ROS、pH、または酵素活性)に応じて、その物理化学的特性を動的に調整でき、細胞挙動や局所的なマイクロ環境のダイナミクスを精密に制御することが可能です。免疫工学的に設計された材料、特にマクロファージを再生促進的なM2表現型へと分極させるように設計された材料の最近の進展は、炎症を抑制し、骨形成を加速させる可能性を示しています。同時に、3D/4Dプリンティング技術により、スキャフォールドの構造、分解プロファイル、および生物活性因子の空間的分布をプログラム可能に制御でき、これにより個別化された治療戦略がサポートされます。AI(人工知能)主導の材料探索と構造最適化は、次世代の高機能骨修復バイオマテリアルの設計空間をさらに拡大させています。本レビューでは、刺激応答性メカニズム、免疫調節戦略、高度な製造技術、およびAIによる設計に重点を置き、骨再生のためのスマートバイオマテリアルの最近の進展を包括的に統合し、臨床応用に向けた主要な障壁と今後の方向性を明らかにします。本レビューにおいて、「スマートバイオマテリアル(smart biomaterial)」は包括的な用語として使用されます。「刺激応答性バイオマテリアル(stimulus-responsive biomaterial)」は、外部トリガー(光、磁気、電気、機械的刺激、pH、ROS、または酵素)に反応するサブクラスを指し、「インテリジェントバイオマテリアル(intelligent biomaterial)」はスマートバイオマテリアルの同義語として扱われます。これらの用語は互換的に使用されるものではありません。
広範な骨欠損、骨折の偽関節、および腫瘍切除後の再建は、整形外科において依然として極めて困難な課題であり、世界的に深刻な罹患率と障害をもたらしています1,2。自家移植、同種移植、金属インプラント、従来のバイオセラミックスなどの伝統的な治療アプローチにより、ある程度の臨床的改善は見られたものの、採取部位の不足、免疫拒絶反応、感染リスク、不十分な生物活性、そして複雑な再生微小環境を調節する能力の限界といった制約が依然として存在します3,4,5。これらの限界は、広範囲な分節性欠損、炎症に伴う骨喪失、および患者固有の構造的再建を必要とする症例において特に顕著であり、従来の材料では精密な修復と機能的な再生という要求を満たすことができなくなっています6。
骨組織工学の急速な進展により、スマートバイオマテリアルが登場しています。静的な材料とは異なり、スマートバイオマテリアルは、光、電場や磁場、機械的な力などの外部刺激、あるいは活性酸素種(ROS)、酸性pH、異常な酵素活性などの内部の病理学的手がかりに応じて、その物理化学的特性を動的に調整することができます3,7,8,9,10。このような応答性により、細胞挙動、炎症カスケード、および再生プロセスの精密な調節が可能になります。同時に、免疫工学の台頭により、マクロファージの分極、T細胞機能、およびサイトカインネットワークを調整できる材料が導入され、これにより炎症、修復、およびリモデリングの相特異的な制御が可能となり、骨治癒が著しく促進されます4,11。さらに、3D/4Dプリンティングの進歩により、スキャフォールドの構造、機械的特性、生物活性因子の空間分布、さらには動的な形状変化までもカスタマイズして制御することが可能となり、高度に個別化された治療戦略がサポートされています11,12,13。加えて、材料スクリーニング、構造最適化、および個別設計への人工知能(AI)の統合により、次世代のスマート骨再生バイオマテリアルの開発サイクルが加速しています14(図1)。
前臨床および動物研究においてこれらの有望な進展が見られるものの、臨床への応用を妨げる大きな障壁が依然として存在している。これには、in vivoにおけるマルチ刺激応答の固有の複雑さ、材料の分解速度と骨再生の時間的経過との不一致、免疫調節機能の不安定さ、スケーラブルな製造における課題、および標準化された規制枠組みの欠如などが含まれる15。したがって、基礎的な原理を解明し、臨床応用の進展を導くためには、現在の設計戦略、刺激応答機構、免疫調節アプローチ、および高度な製造技術を体系的に統合することが不可欠である。
これらの考察に基づき、我々はスマートバイオマテリアルの設計が、治癒プロセス全体を通して単一の静的な機能を提供するのではなく、骨損傷治癒の3つの連続する段階(炎症、修復、リモデリング)に合わせるべきであると提案します。したがって、本考察では主に以下の点に焦点を当てます。(i) 骨治癒の各段階における生物学的ニーズと、スマートバイオマテリアルの関連する設計原理、(ii) オンデマンドで活性化可能な主要な化学反応および物理的シグナル、(iii) カスタマイズされたアプリケーションをサポートする製造および計算プラットフォーム(3D/4Dプリンティング、AI支援設計、オルガンオンチップ)、(iv) 実装前に克服すべき臨床応用の障壁。化学組成や用途で材料を分類する近年のレビューとは異なり、本レビューは治癒段階に沿った設計枠組みを特徴としており、in vitro研究から大型動物試験、さらには臨床研究に至るまで、各材料タイプのエビデンスレベルを明確に比較しています。
Biological basis of bone healing and microenvironmental regulation
Bone healing is a highly coordinated regenerative process that proceeds through overlapping phases of inflammation, tissue repair, and remodeling. These phases are not independent events but a continuous biological program controlled by immune cells, osteogenic cells, vascular cells, extracellular matrix components, and local biochemical and mechanical cues16,17. In the early inflammatory phase, tissue injury initiates hematoma formation and rapid recruitment of neutrophils and macrophages. These cells remove necrotic tissue and release inflammatory mediators, including tumor necrosis factor, interleukin-1, and interleukin-6, which help initiate vascular ingrowth and recruit osteoprogenitor cells to the defect site18,19,20. This early inflammatory response is necessary for repair initiation, but its duration and intensity must be tightly controlled. Excessive or persistent inflammation can impair osteogenic differentiation, delay angiogenesis, and contribute to non-union or defective regeneration (Figure 2).
As inflammation resolves, bone repair enters a reparative phase characterized by the coordinated activity of chondrocytes, fibroblasts, osteoblasts, mesenchymal stem cells, and endothelial cells. During this phase, cartilaginous callus formation, extracellular matrix deposition, angiogenesis, and mineralization progressively bridge the defect and establish a structural template for new bone formation16,21. Growth factors such as bone morphogenetic proteins and vascular endothelial growth factor are central to this process because they support osteogenic commitment and neovascularization22,23. The final remodeling phase involves the replacement of immature repair tissue with mature bone through balanced osteoblast-mediated matrix formation and osteoclast-mediated resorption17,24. This stage may continue for months or years and is essential for restoring bone architecture and mechanical strength.
The immune microenvironment is increasingly recognized as a major determinant of bone-regeneration quality. Macrophages are particularly important because their phenotype changes dynamically during healing. M1-like macrophages support early defense, debris clearance, and inflammatory signaling, whereas M2-like macrophages promote inflammation resolution, angiogenesis, osteogenic differentiation, and tissue remodeling25,26,27. T lymphocytes also contribute to this process. Regulatory T cells can suppress excessive immune activation and establish a permissive regenerative environment, while CD4⁺ and CD8⁺ T cells influence macrophage activity, vascular formation, and bone metabolism28,29,30. Therefore, successful bone repair depends not only on osteogenic stimulation but also on coordinated immune regulation.
Smart biomaterials are uniquely positioned to interact with this complex microenvironment. Unlike passive scaffolds, which primarily provide structural support, smart biomaterials can be designed to regulate surface chemistry, topography, stiffness, porosity, degradation behavior, and bioactive factor delivery in response to the biological needs of the defect site. Surface functional groups, wettability, and nano-/micro-scale architecture can influence macrophage recognition, adhesion, spreading, and polarization, thereby promoting a transition from prolonged inflammation toward a pro-regenerative immune state31,32. Meanwhile, matrix stiffness, elastic modulus, pore architecture, and spatial biochemical gradients can modulate mesenchymal stem cell adhesion, migration, and osteogenic differentiation33,34. Interconnected pore networks further support vascular invasion, nutrient diffusion, and trabecular bone penetration35. Thus, the central principle of smart biomaterial design is to align material properties with the temporal and spatial requirements of bone healing.
The biological events described above impose explicit, time-resolved design constraints on smart biomaterials. First, the inflammatory phase demands that biomaterials minimize foreign-body response and actively resolve inflammation, which has motivated the incorporation of ROS scavengers (e.g., ceria nanoparticles, TEMPO-conjugated hydrogels), pH-responsive anti-inflammatory release (e.g., Schiff-base linkers cleaved at pH 5.5–6.5 in the acidic wound microenvironment), and immunomodulatory surface chemistries that bias macrophage recruitment toward a pro-resolving phenotype. Second, the reparative phase requires sustained and spatially patterned delivery of osteogenic and angiogenic cues, leading to the development of growth-factor-loaded microspheres, affinity-based release systems (e.g., heparin-binding peptides for BMP-2), and electrostatically patterned substrates that guide MSC alignment. Third, the remodeling phase requires mechanical compatibility with host bone and on-demand degradation, motivating the development of stiff-to-soft dynamic hydrogels, mineral-coated scaffolds, and stress-adaptive 4D-printed geometries. Importantly, these three design rules are not independent: a material that resolves inflammation early will not be effective in the reparative phase if it has already degraded. This temporal coupling is the central design challenge that motivates the smart biomaterial concept and that distinguishes this review from static biomaterial surveys.
A further design consideration is the patient-specific variability in healing trajectories, driven by age, sex, comorbidities (osteoporosis, diabetes, smoking), genetic polymorphisms in BMP and VEGF pathways, and defect geometry. This variability is the rationale for the personalized, closed-loop biomaterial systems discussed in the Emerging technologies and clinical translation section, in which real-time monitoring of healing biomarkers (e.g., pH, temperature, enzymatic activity) triggers on-demand release of growth factors or adapts mechanical properties.
Finally, the design rules derived from biology must be explicitly compared against the evidence base for each material class. The following sections, therefore, adopt a design rule → material example → evidence level (in vitro/small animal/large animal/clinical) structure throughout, addressing a key gap in current smart-biomaterial reviews.
Stimulus-responsive smart biomaterials for bone regeneration
Stimulus-responsive biomaterials represent a major class of smart biomaterials because they can convert external physical cues or endogenous pathological signals into programmable material responses. These responses may include changes in degradation rate, mechanical properties, surface characteristics, drug release, growth-factor presentation, or cellular interactions3,15,36,37 (Figure 3). In bone regeneration, this property is particularly valuable because the defect microenvironment changes substantially over time. Early inflammatory lesions may contain excessive reactive oxygen species, acidic pH, and proteolytic enzymes, whereas later repair stages require angiogenesis, osteogenic differentiation, mineral deposition, and mechanical remodeling. Stimulus-responsive materials can therefore provide phase-adapted regulation rather than static support.
Externally responsive biomaterials are activated by applied physical stimuli, including light, electrical stimulation, magnetic fields, ultrasound, mechanical loading, and piezoelectric signals. Light-responsive systems, especially near-infrared-responsive materials, have received considerable attention because near-infrared light can trigger photothermal conversion, photochemical reactions, and controlled release of therapeutic molecules38,39,40. In bone defects complicated by tumor resection or infection, photothermal materials may provide dual functions: local tumor ablation or antibacterial activity, followed by promotion of bone repair15,40. However, this strategy also faces translational challenges. Light penetration is limited in deep tissues, thermal dose must be carefully controlled to avoid collateral damage, and clinical implementation requires integration of optical devices into surgical or postoperative workflows41. Therefore, light-responsive systems may be most suitable for superficial, surgically exposed, or device-accessible defects.
Electrical and piezoelectric biomaterials are inspired by the natural electromechanical properties of bone. Bone is a mechanosensitive tissue, and mechanical loading can generate bioelectrical signals that influence bone remodeling and mass maintenance42. Conductive polymers, carbon-based nanomaterials, and electrically active scaffolds can modulate cell membrane potential, intracellular signaling, osteogenic differentiation, and mineralization43,44,45. Piezoelectric biomaterials further bridge mechanical and electrical regulation by converting deformation into localized electrical stimulation46,47. This is highly relevant for load-bearing defects, where physiological movement and mechanical stress are part of the healing environment. By integrating mechanical support with bioelectrical regulation, these materials may enhance osteogenesis without relying entirely on soluble growth factors. Nevertheless, stimulation intensity, duration, device compatibility, and long-term safety require careful optimization before clinical translation.
Magnetic-responsive biomaterials offer another route for remote, spatially controlled regulation. By incorporating magnetic nanoparticles, such as iron oxide-based components, scaffolds, or hydrogels can respond to external magnetic fields, enabling guided drug delivery, enhanced cell recruitment, improved angiogenesis, and osteogenic stimulation43,48. Compared with light-responsive systems, magnetic stimulation may offer deeper tissue penetration and noninvasive remote control. However, the dose, distribution, degradation, and long-term retention of magnetic particles must be evaluated thoroughly. Mechanically responsive materials are also highly relevant to bone repair. By tuning stiffness, elasticity, pore geometry, and surface architecture, these systems can mimic the mechanical microenvironment of native bone and activate mechanotransduction pathways involved in osteogenic differentiation45,49. Together, externally responsive materials provide high temporal controllability, but their success depends on safe stimulation parameters, device integration, reproducibility, and patient compliance.
Internally responsive biomaterials are activated by pathological or regenerative signals within the local microenvironment. Reactive oxygen species-responsive materials are particularly important because excessive oxidative stress is common in chronic inflammation, osteoporosis, tumor-associated bone defects, and impaired healing50,51. Persistent reactive oxygen species accumulation damages cells, disrupts osteogenic signaling, and disturbs the balance between bone formation and resorption. By incorporating oxidation-labile linkages, reactive oxygen species-degradable crosslinkers, or antioxidant-loaded nanostructures, these materials can selectively degrade or release therapeutic agents in oxidative environments52,53. Reactive oxygen species-responsive hydrogels and nanoparticles have shown potential for reducing inflammation, restoring osteogenic signaling, and enhancing osteoblast activity54.
pH-responsive biomaterials are designed to exploit acidic microenvironments in inflammatory, infectious, or tumor-associated bone lesions. Inorganic components, calcium phosphate systems, polymer networks, and hydrogels can be engineered to dissolve, swell, or release drugs preferentially under mildly acidic conditions55,56,57,58. This allows localized delivery of antibacterial agents, antitumor drugs, antioxidants, growth factors, or osteogenic molecules while limiting unnecessary release in healthy tissues. Enzyme-responsive biomaterials target elevated proteolytic activity, particularly matrix metalloproteinases, which are involved in extracellular matrix remodeling and tissue repair. By incorporating enzyme-cleavable crosslinkers or peptide sequences, hydrogels and scaffolds can release osteogenic or immunomodulatory factors on demand while maintaining structural support during early healing59,60,61. Compared with externally responsive systems, internally responsive materials resemble closed-loop platforms because they are activated by disease- or repair-associated cues. However, microenvironmental heterogeneity, patient-to-patient variability, insufficient stimulus intensity, and long-term stability remain major obstacles10,62. Major stimulus-responsive biomaterial strategies discussed above are summarized in Table 1.
Immunoengineering strategies for bone regeneration
Immunoengineering has become a central strategy in the design of smart biomaterials because the immune system actively regulates every stage of bone healing. The goal of immunoengineered biomaterials is not simply to suppress inflammation but to guide immune responses in a stage-specific manner. A well-designed immunomodulatory scaffold should permit early protective inflammation, prevent chronic inflammatory damage, promote the transition to tissue repair, and support osteogenesis and angiogenesis4,63. This concept is particularly important for large defects, infection-associated defects, aging-related impaired healing, and inflammatory bone loss, where immune dysregulation often compromises regeneration.
Macrophages are the most widely studied immune targets in bone-regenerative biomaterials. During the early phase of repair, M1-like macrophages secrete pro-inflammatory cytokines, including tumor necrosis factor-α, interleukin-1, and interleukin-6. These cytokines contribute to pathogen clearance, necrotic tissue removal, and recruitment of reparative cells64,65,66. However, persistent M1-like activation may amplify inflammation, inhibit osteogenic differentiation, and impair vascularization. As healing progresses, macrophages normally shift toward an M2-like reparative phenotype, characterized by secretion of interleukin-10, transforming growth factor-β, vascular endothelial growth factor, and bone morphogenetic proteins63,67,68. These mediators support inflammation resolution, matrix reconstruction, angiogenesis, and new bone formation. Timely and appropriately scaled M2-like polarization is therefore a key determinant of successful repair, whereas prolonged M1 dominance is associated with delayed healing and non-union69,70,71. Smart biomaterials can influence macrophage behavior through multiple material-level cues. Surface charge, functional group density, wettability, stiffness, roughness, and nano-/micro-topography can affect macrophage adhesion, morphology, spreading, and activation state68,72,73. For example, specific surface architectures may reduce excessive inflammatory activation while promoting a pro-repair phenotype. In addition, biomaterials can be engineered to deliver immunomodulatory molecules such as interleukin-4, interleukin-13, microRNAs, or other bioactive agents that reinforce M2-like polarization74. These strategies allow biomaterials to act as immune-instructive platforms rather than inert implants.
Cytokine and chemokine regulation further expands the potential of immunoengineered biomaterials. Bone healing requires dynamic cytokine changes: early pro-inflammatory signaling initiates repair, whereas later anti-inflammatory and pro-regenerative signaling support tissue formation69,70,71. Controlled release of interleukin-4 or interleukin-13 can reduce persistent inflammation and promote macrophage transition toward a reparative phenotype74. Sequential release of transforming growth factor-β, vascular endothelial growth factor, and bone morphogenetic proteins can coordinate matrix reconstruction, angiogenesis, and osteogenesis75,76. This temporally programmed approach may be superior to continuous single-factor release because it better reflects the physiological sequence of bone healing.
Chemokines are also valuable for recruiting immune and progenitor cells to the defect site. Monocyte chemoattractant protein-1 can attract macrophages and mesenchymal progenitor cells through CCR2-mediated signaling, thereby supporting early immune modulation and repair initiation77,78. C-X-C motif chemokine ligand 12 can promote stem cell homing and provide a sustained cell source for osteogenesis79,80. By creating spatial chemokine gradients, biomaterials can actively organize cellular recruitment instead of relying on passive cell infiltration. Nevertheless, immune modulation must be carefully balanced. Excessive suppression of early inflammation may impair clearance of damaged tissue, whereas uncontrolled chemokine release may prolong immune infiltration. Similarly, excessive or poorly timed M2-like polarization may compromise immune surveillance. Therefore, next-generation immunoengineered biomaterials should pursue dynamic, reversible, and multitarget immune regulation, integrating macrophage modulation, stem-cell recruitment, angiogenesis, and osteogenic stimulation in a coordinated framework81,82.
Recent osteoimmunology research has substantially revised the classical M1/M2 paradigm. Macrophage phenotypes are now understood to exist on a continuum rather than as discrete M1/M2 states, and single-cell transcriptomic studies of fracture callus have identified at least 5–7 transcriptionally distinct macrophage subpopulations that emerge and resolve at different times during healing. Among these, osteomacs—tissue-resident macrophages lining bone surfaces—play non-redundant roles in osteoblast maintenance and have been proposed as a distinct target for biomaterial-based immunomodulation.
Beyond macrophages, the immune response during bone healing involves coordinated activity of neutrophils, dendritic cells, T cells, and osteoclasts. Neutrophil extracellular traps (NETs) in early inflammation, when dysregulated, delay the M1→M2 transition. Dendritic cells bridge innate and adaptive immunity and modulate mesenchymal stem cell (MSC) recruitment. T cells, particularly Tregs, promote bone formation via IL-10 and CTLA-4 signaling, whereas Th17 cells can be pro-osteoclastogenic. The temporal heterogeneity of these populations argues for stage-specific, not generic, immunomodulatory design.
Although the M1→M2 transition is widely viewed as beneficial, recent evidence indicates that excessive or prolonged M2-like polarization can impair bone regeneration. M2 macrophages secrete TGF-β, IL-10, and PDGF, which, at sustained high levels, have been associated with heterotopic ossification, marrow adipogenesis, and fibrous encapsulation rather than functional bone integration. This underscores the need for time-limited immunomodulation, in which the biomaterial actively resolves inflammation during the first 7–10 days and then ceases to drive M2 polarization, allowing the natural transition to remodeling. We suggest that future smart biomaterials should incorporate built-in off-switches (e.g., enzymatically degradable immunomodulatory motifs) that prevent sustained M2 polarization beyond the reparative phase. The immunoengineering strategies discussed in this section are summarized in Table 2.
3D/4D printing and personalized bone repair
Personalized bone regeneration requires biomaterials that match not only biological needs but also the anatomical and mechanical characteristics of individual defects. Three-dimensional printing has become a powerful tool for this purpose because it allows patient-specific scaffold design based on clinical imaging, digital reconstruction, and precise additive manufacturing83,84,85,86. Computed tomography and magnetic resonance imaging can be used to reconstruct the geometry, curvature, volume, and load-bearing requirements of a bone defect. These data can then guide the fabrication of scaffolds that fit irregular anatomical structures and provide appropriate mechanical support85,86,87. This is particularly important for mandibular reconstruction, segmental long-bone defects, craniofacial repair, and post-tumor resection defects, where anatomical precision strongly influences functional outcomes.
At the microscale, 3D printing enables control over pore size, porosity, pore interconnectivity, and internal architecture. These parameters are critical for cell migration, vascular invasion, nutrient diffusion, waste removal, and new bone deposition88. Gradient structures can mimic the heterogeneous architecture of native bone, balancing dense regions for mechanical support with porous regions for biological integration89,90. Biodegradable printed scaffolds may further reduce long-term complications associated with permanent metallic implants, including stress shielding, chronic inflammation, and the need for secondary removal91,92. Thus, 3D printing provides a platform for integrating structural precision with biological function.
Another important advantage of 3D printing is spatial control over biomolecules, cells, and material composition. Growth factors such as bone morphogenetic proteins and vascular endothelial growth factor can be incorporated into predefined regions of a scaffold to create functional zones that promote osteogenesis and angiogenesis in a coordinated manner91,93. This strategy is especially valuable because bone regeneration requires simultaneous vascularization and mineralization. Spatially organized delivery can direct different cell behaviors in different regions of the scaffold, resembling the cortical-trabecular organization of native bone. In addition, 3D printing allows integration of multiple materials with different degradation rates, stiffness values, or bioactive functions, creating scaffolds that are both mechanically supportive and biologically instructive94.
Four-dimensional printing builds on 3D printing by introducing time-dependent changes in structure or function. Using shape-memory polymers or stimuli-responsive materials, 4D-printed constructs can change their configuration, stiffness, porosity, degradation behavior, or release kinetics in response to environmental cues such as temperature, pH, ions, hydration, or body fluids83,86,95. This dynamic responsiveness may be especially useful for irregular defects, minimally invasive implantation, and staged bone healing. For example, a compact scaffold could be implanted through a smaller surgical window and then expand or conform to the defect geometry in situ. Similarly, a 4D-printed scaffold could adjust its release behavior as the microenvironment transitions from an inflammatory to a reparative phase83,96. However, 4D printing remains less clinically mature than 3D printing. Long-term shape stability, predictable response behavior, scalable manufacturing, sterilization, mechanical reliability, and biosafety must be rigorously evaluated before broad clinical translation83,84,97.
Emerging technologies and clinical translation
The future development of smart biomaterials is increasingly linked to artificial intelligence, organoid systems, bone-on-a-chip models, and real-time monitoring technologies. Artificial intelligence, especially machine learning and deep learning, can accelerate biomaterial discovery by analyzing large datasets that connect material composition, structure, mechanical properties, degradation behavior, and biological outcomes98,99. Instead of relying solely on trial-and-error experimentation, machine-learning models can predict candidate materials with favorable biocompatibility, osteogenic potential, immune-regulatory capacity, and mechanical performance. Artificial intelligence can also support scaffold optimization by integrating clinical variables such as defect type, patient age, comorbidities, imaging features, and expected mechanical loading100,101,102. This may allow the field to move from generalized scaffold design toward individualized material selection (Figure 4).
Organoid and bone-on-a-chip technologies provide more physiologically relevant platforms for evaluating smart biomaterials. Traditional two-dimensional cultures cannot fully reproduce cell-cell interactions, three-dimensional architecture, vascular-like networks, immune regulation, or dynamic mechanical and biochemical gradients. Bone organoids and microfluidic bone-on-a-chip systems can better model osteogenesis, angiogenesis, immune-cell interactions, and material-tissue responses under controlled conditions103,104. These systems may be particularly useful for screening biomaterial formulations, testing drug or growth-factor combinations, and reducing reliance on early animal experiments. Their high-throughput potential could accelerate optimization of complex smart biomaterial systems102.
Despite encouraging preclinical results, only a small fraction of smart biomaterials have reached late-stage clinical trials or commercialization. Table 3 summarizes the current translational landscape, listing representative technologies, their highest preclinical evidence level, clinical trial status (if any), and major remaining challenges. Two patterns emerge: (i) mechanical and electrical stimulation are the only strategies with regulatory approval (e.g., FDA-cleared low-intensity pulsed ultrasound (LIPUS) devices, FDA-cleared PEMF devices), whereas responsive chemistries (pH-, ROS-, enzyme-triggered) remain largely at the small-animal stage; (ii) multifunctional combination products (e.g., BMP-releasing 3D-printed scaffolds) face the highest regulatory and manufacturing barriers due to the complexity of combination-product approval pathways.
Across all seven stimulus-responsive strategies discussed in 'Stimulus-responsive smart biomaterials for bone regeneration', we estimate that >70% of publications report only in vitro (EL-1) or small-animal (EL-2, rodent critical-size defect <5 mm) data, fewer than 15% include large-animal validation (EL-3, rabbit/dog/sheep/pig defect ≥5 mm), and only a handful have advanced to registered clinical trials (EL-4) or regulatory approval (EL-5). This disproportion between in vitro promise and clinical translation is a central challenge for the field and motivates the standardized assessment frameworks proposed in 'Conclusions'.
The application of AI to smart biomaterial design has expanded rapidly beyond simple compositional screening. Six specific AI capabilities are particularly relevant to bone regeneration. (i) Generative AI for biomaterial discovery: variational autoencoders and diffusion models can propose novel polymer chemistries, peptide sequences, or composite formulations with desired mechanical, degradation, and bioactivity properties, complementing traditional design-of-experiments. (ii) Digital twins of bone defect healing: patient-specific finite-element and agent-based models, calibrated by imaging and biomarker data, can simulate healing trajectories and predict optimal scaffold geometry and release kinetics. (iii) Machine learning-guided scaffold optimization: surrogate models trained on high-throughput printing data accelerate the design of pore architecture, lattice topology, and multimaterial interfaces. (iv) Predictive modeling of degradation behavior: physics-informed neural networks predict in vivo degradation rates under patient-specific loading, inflammation, and pH conditions, addressing a key translational bottleneck. (v) Explainable AI (XAI): SHAP, LIME, and attention mechanisms are beginning to make AI-driven design recommendations interpretable, which is essential for regulatory acceptance. (vi) Data scarcity and federated learning: the field faces a chronic shortage of large, labeled biomaterial-performance datasets; federated and self-supervised approaches, together with synthetic data generation, are emerging as solutions.
Real-time monitoring technologies may further transform bone repair from static follow-up into dynamic therapeutic management. Implantable sensors and smart implants can monitor local stress, strain, temperature, pH, oxygen concentration, or healing-related signals after implantation105,106,107. Wireless data transmission and Internet-of-Things-based systems could allow clinicians to detect delayed healing, abnormal loading, infection risk, or implant failure earlier than conventional imaging-based follow-up. When combined with responsive biomaterials, these monitoring systems may eventually create closed-loop therapeutic platforms that sense local conditions and adjust treatment accordingly.
Current limitations and unresolved challenges
Despite substantial progress, the field faces several unresolved challenges. (i) Disproportion between in vitro and clinical evidence: as noted in the section 'Emerging technologies and clinical translation,' >70% of smart biomaterial studies remain at EL-1/EL-2, and the leap to clinical translation is hindered by the scarcity of GLP-compliant large-animal safety data. (ii) Oversimplified immune models: the M1/M2 dichotomy, although pedagogically useful, no longer captures the spectrum of macrophage phenotypes revealed by single-cell transcriptomics. (iii) Limited integration of patient-specific variables: most designs assume a generic healing trajectory and do not account for age, sex, comorbidity, or genetic background. (iv) Lack of standardized assessment: cross-study comparison is impeded by the absence of harmonized protocols for biosafety, immunogenicity, degradation kinetics, and mechanical reliability. (v) Regulatory ambiguity for combination products: smart biomaterials that combine a device, a drug, and a biologic fall into complex regulatory categories whose approval pathways remain ill-defined in many jurisdictions. Addressing these limitations will require coordinated action from materials scientists, immunologists, clinicians, regulators, and industry partners.
Methodological limitations and reporting standards in smart biomaterial research
While smart biomaterials hold considerable promise, the gap between laboratory demonstration and clinical benefit remains the most important unsolved problem. A bias toward publishing positive in vitro results, combined with limited replication and few registered preclinical studies, inflates the field's perceived maturity. The community would benefit from a shift toward registered study designs and standardized reporting.
Smart biomaterials are reshaping bone regeneration by moving beyond passive structural support to actively regulate the local repair microenvironment. Stimulus-responsive platforms respond to external cues (light, electrical signals, magnetic fields, mechanical loading) and internal pathological signals (ROS, acidic pH, enzymatic activity), enabling precise spatiotemporal control of therapeutic release and cellular behavior. In parallel, immunoengineered biomaterials guide macrophage polarization and immune-cell recruitment to foster a regenerative microenvironment. The integration of 3D/4D printing, AI-driven design, organoid models, and bone-on-a-chip systems further expands the potential for personalized bone repair.
However, the current evidence base remains predominantly preclinical. Most studies rely on in vitro systems or small-animal models, and robust clinical data are scarce; these gaps must be acknowledged when interpreting the promising outcomes reported in the literature. Clinical translation is further limited by biosafety concerns, degradation-product toxicity, manufacturing reproducibility, and regulatory complexity.
Recent complementary studies further enrich this framework: Vignolo et al.108 discussed strategies for craniofacial tissue engineering and scalable bone regeneration; Cai et al.109 summarized advances in biomimetic bone scaffold development; Patel et al.110 reviewed bone morphogenetic protein-related therapies for medication-related osteonecrosis of the jaw; and Viraji et al.111 reported a wireless bioelectric stimulation strategy for bone regeneration.
Future advancements should focus on six strategic priorities: (1) developing temporally programmable, multifunctional systems that recapitulate the inflammation–repair–remodeling cascade; (2) engineering closed-loop platforms that integrate real-time biosensors with responsive actuators; (3) utilizing clinically relevant large-animal models and patient-derived disease constructs; (4) establishing standardized assessment protocols aligned with ARRIVE-like reporting guidelines; (5) advancing patient-specific designs by synergizing artificial intelligence with individual imaging and genomic data; and (6) bridging the translational gap through Good Laboratory Practice (GLP)-compliant safety evaluations, Good Manufacturing Practice (GMP) manufacturing, and proactive regulatory engagement. Ultimately, next-generation smart biomaterials capable of microenvironmental responsiveness, immune modulation, and personalized customization hold significant promise for delivering precise therapeutic interventions for complex bone defects, non-union fractures, and post-oncologic reconstruction.

Figure 1: Clinical demands, limitations of conventional strategies, and smart biomaterial-based solutions in bone regeneration. Population aging, rising incidence of bone defects, immune dysregulation, and personalized therapeutic needs underscore the need for improved bone repair. Traditional treatments—such as autografts/allografts, metal implants, and standard bioceramics—are limited by donor scarcity, immune rejection, stress shielding, low bioactivity, and uncontrolled degradation. Smart biomaterials overcome these shortcomings by responding to endogenous (pH, ROS, enzymes) and external stimuli (light, electrical, and mechanical cues), and by integrating advanced 3D/4D printing technologies to enable precise and personalized bone regeneration. Figure created by BioRender. https://BioRender.com Please click here to view a larger version of this figure.

Figure 2: Temporal progression of bone healing and the stage-specific roles of immune regulation. Bone healing proceeds through the inflammatory, repair, and remodeling phases, accompanied by dynamic changes in cellular activities and cytokine levels (e.g., IL-1, IL-6, TNF-α). Early inflammation is dominated by M1 macrophages, which establish a pro-inflammatory microenvironment. As healing advances, macrophages transition toward the M2 phenotype, promoting osteogenesis and tissue repair. T cells—particularly regulatory T cells (Tregs)—further modulate M2 polarization, maintain immune homeostasis, and facilitate coordinated bone regeneration. Figure created by BioRender. https://BioRender.com Please click here to view a larger version of this figure.

Figure 3: Schematic illustration of external and internal stimulus-responsive smart biomaterials for bone regeneration. The left panel depicts materials responsive to external physical stimuli—including light, electrical signals, magnetic fields, ultrasound, and mechanical/piezoelectric cues—while the right panel shows biomaterials responsive to internal microenvironmental signals such as ROS, pH, enzymatic activity, ion concentrations, endogenous electric fields, and immune microenvironmental changes. Together, these distinct classes of stimuli-responsive materials promote bone regeneration through multiple coordinated mechanisms. Figure created by BioRender. https://BioRender.com. Please click here to view a larger version of this figure.

Figure 4: Key barriers and future directions for the clinical translation of smart biomaterials in bone regeneration. The left panel summarizes major bottlenecks hindering clinical translation, including biosafety and immunogenicity concerns, uncertainties in degradation kinetics, insufficient long-term mechanical and functional stability, and the regulatory complexity associated with multifunctional composite systems. The right panel highlights emerging future directions, such as multi-target synergistic material designs, patient-specific personalized therapies, AI-driven material optimization, and 4D-printed constructs capable of dynamically adapting to the in vivo environment. Figure created by BioRender. https://BioRender.com. Please click here to view a larger version of this figure.
| Stimulus Type | Representative Materials | Key Biological Effects | Advantages / Limitations | References |
| Light (NIR) | BP nanosheets, AuNRs, PDA coatings, ICG-loaded hydrogels | Tumor ablation (PTT); antibacterial activity; controlled drug/GF release; MSC osteogenesis | Pros: High spatiotemporal precision; on-demand activation; dual antibacterial + osteogenic | 38,39,40,41 |
| (External) | Cons: Limited deep-tissue penetration; thermal dose control; suitable mainly for superficial defects | |||
| Electrical & Piezoelectric | Conductive polymers (PPy, PEDOT), CNTs, piezoceramics (BaTiO₃, PVDF) | Enhanced MSC osteogenic differentiation; increased ALP activity; mineral deposition; angiogenesis | Pros: Mimics native bone electromechanics; no exogenous GF required; suitable for load-bearing defects | 43,44,45,46,47 |
| (External) | Cons: Stimulation parameter optimization unclear; long-term biosafety; patient compliance | |||
| Magnetic | IONPs (Fe₃O₄, γ-Fe₂O₃), magnetic hydrogels, magnetoelectric composites | Guided drug delivery; enhanced cell recruitment; angiogenesis; osteogenic stimulation | Pros: Deep tissue penetration; noninvasive remote control; spatial targeting; no ionizing radiation | 43,44,45,46,47,48 |
| (External) | Cons: Particle dose and long-term retention concerns; potential iron overload; standardization lacking | |||
| Mechanical | Tunable-stiffness hydrogels, elastomeric scaffolds, stress-adaptive polymers | MSC lineage commitment; matrix deposition; mechanically-driven osteogenesis | Pros: Directly mimics bone mechanical niche; passive (no external power); integrates with physiological loading | 45,46,47,48,49 |
| (External) | Cons: Static vs. dynamic loading complexity; patient-specific mechanical requirements; fatigue over time | |||
| Ultrasound | LIPUS devices, ultrasound-responsive microbubbles | Accelerated fracture healing; enhanced angiogenesis; increased callus formation | Pros: Clinically approved (Exogen®); noninvasive; established safety; good patient compliance | 15 |
| (External) | Cons: Mechanism incompletely understood; efficacy varies by defect type; optimal parameters not standardized | |||
| ROS-Responsive | PPS-based polymers, TK-linked hydrogels, ceria NPs, PDA-coated scaffolds | Localized antioxidant release; inflammation reduction; restored osteogenic signaling; M1→M2 transition | Pros: Closed-loop (activated by pathology); targets chronic inflammation and ROS-rich defects; selective degradation | 50,51,52,53,54 |
| (Internal) | Cons: ROS heterogeneity between patients; insufficient stimulus intensity in some defects; burst vs. sustained release | |||
| pH-Responsive | CaP nanoparticles, chitosan-based hydrogels, Schiff-base-crosslinked networks | Site-specific drug/GF release at acidic defect sites; antibacterial delivery; antitumor drug release | Pros: Exploits endogenous acidosis (inflammation, infection, tumor); localized delivery; reduced systemic toxicity | 55,56,57,58 |
| (Internal) | Cons: pH gradient variability; burst release risk; limited specificity (inflammatory vs. tumor pH overlap) | |||
| Enzyme-Responsive (MMP) | MMP-sensitive PEG hydrogels, peptide-functionalized scaffolds | On-demand GF/cytokine release during tissue remodeling; cell-mediated scaffold remodeling; MSC recruitment | Pros: Cell-driven release kinetics; matches tissue remodeling timeline; maintains structural support early | 59,60,61 |
| (Internal) | Cons: Enzyme level variability; patient-to-patient differences; long-term stability of peptide linkers; manufacturing complexity |
Table 1: Stimulus-responsive comparison table. This table compares externally and internally responsive smart biomaterials across stimulus categories, triggering mechanisms, representative material platforms, key biological effects, advantages, and translational limitations. Externally responsive strategies (light/near-infrared, electrical/piezoelectric, magnetic, mechanical, and ultrasound) provide high spatiotemporal control through applied physical stimuli but require device integration and patient compliance. Internally responsive strategies (reactive oxygen species, pH, and enzyme/matrix metalloproteinase) function as closed-loop platforms activated by pathological or regenerative signals within the local microenvironment, offering pathology-specific regulation but facing challenges posed by microenvironmental heterogeneity and patient-to-patient variability. Please click here to download this Table.
| Immunomodulatory Dimension | Key Immune Cells / Factors | Smart Biomaterial-Based Modulation Strategies | Primary Biological Effects on Bone Healing | Key Design Principles | Potential Risks and Translational Challenges | References |
| Inflammatory Phase Immune Activation | M1 macrophages; TNF-α, IL-1, IL-6 | Surface chemical functionalization; micro-/nano-topographical modulation | Clearance of necrotic tissue; initiation of angiogenesis and tissue repair | Allow transient, controlled pro-inflammatory signaling | Prolonged inflammation may impair bone healing | 64,65,66, 68,69,70,71,72,73 |
| Immune transition during the reparative phase | M2 macrophages, IL-10, TGF-β | Surface functionalization; IL-4/miRNA delivery | Suppress inflammation; promote osteogenesis and angiogenesis | Promote M2 polarization after inflammatory clearance | Excessive M2 polarization may impair immune surveillance | 63, 67, 68, 74 |
| Osteogenic–angiogenic coupling | VEGF,BMPs | Biodegradable scaffolds; multilayer coatings; sequential release | Osteogenesis; angiogenesis; matrix remodeling | Coordinated osteogenic–angiogenic signaling is required | Osteogenic–angiogenic signaling requires coordination | 22, 23, 75, 76 |
| Temporal immune programming | IL-4/IL-13 → TGF-β/VEGF → BMPs | Programmable degradable materials; staged release | Coordinate inflammation–repair–remodeling | Avoid single release; enable staged control | High complexity; manufacturing and stability | 69,70,71,72,73,74,75,76 |
| Immune cell recruitment | MCP-1/CCR2, CXCL12 | Chemokine gradients; factor binding | Recruit macrophages and MSCs | Coordinate recruitment and polarization | Cell source heterogeneity; individual variability | 77,78,80 |
| Multitarget immune remodeling | Macrophages + stem cells + osteoblasts | Factor combinations; spatial release control | Improve the local immune–regenerative microenvironment | Integrate temporal and spatial heterogeneity | Balancing standardization and personalization | 63, 77,78,79,80,81,82 |
Table 2: Immunoengineering strategies for bone regeneration. This table summarizes major immunoengineering strategies used in smart biomaterial-assisted bone regeneration, including regulation of inflammatory activation, macrophage phenotype transition, osteogenic–angiogenic coupling, temporal immune programming, immune-cell recruitment, and multitarget immune remodeling. Key immune cells, regulatory factors, biomaterial-based modulation approaches, biological effects, design principles, and potential translational challenges are listed. Please click here to download this Table.
| Decision criteria | 3D-printed bone scaffolds | 4D-printed bone scaffolds | References |
| Core design principles | Image-based, statically matched implants | Introduce temporal dynamics for adaptive regulation | 83,84,85,86,95 |
| Primary technological basis | CT/MRI-driven reconstruction; layer-by-layer fabrication | Stimuli-responsive materials and programmable structures | 83,84,85,86,87, 95 |
| Degree of personalization | Personalized anatomy and mechanics; fixed after implantation | Dynamic in vivo adjustment of form and function | 85,86,87, 92, 95,96,97 |
| Ability to mimic bone microarchitecture | Controlled porosity to mimic cortical–trabecular bone | Dynamic adaptation during bone repair | 88,89,90, 95, 96 |
| Spatial control of bioactive factors | Spatial gradients of BMPs and VEGF | Environment-responsive temporal release | 91, 93, 94, 96 |
| Mechanical–biological functional synergy | Balance mechanical support and cell infiltration | Dynamic mechanical adaptation during healing | 88,90,91, 93,94,95 |
| Adaptability to complex defects | For defined, load-bearing bone defects | For irregular or dynamic defects | 85,86,87, 92, 95,96,97 |
| Surgical and implantation advantages | Mature preoperative design; clear implantation | In situ adaptation reduces surgical complexity | 83, 85,86,87, 92, 96, 97 |
| Primary clinical application stage | Most mature, near-clinical technology | Exploratory, early-stage translation | 83, 84, 95,96,97 |
| Potential limitations | Limited dynamic responsiveness | Stability, controllability, and long-term safety need evaluation | 83, 84, 95, 97 |
| Decision recommendations | Large, load-bearing defects needing precise mechanics | Irregular defects needing adaptive control | 85,86,87, 89, 90, 92, 95,96,97 |
Table 3: Comparison of 3D and 4D printing strategies for personalized bone regeneration. This table compares 3D- and 4D-printed bone scaffolds with respect to design principles, technological basis, personalization capacity, bone microarchitecture mimicry, spatial or temporal control of bioactive factors, mechanical–biological synergy, adaptability to complex defects, surgical advantages, clinical maturity, limitations, and recommended application scenarios. Please click here to download this Table.
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