Celia Martín Cubillo

Background: Digital surgery integrates advanced imaging, computational modeling, additive manufacturing, and intraoperative navigation technologies. Although widely explored, most platforms remain fragmented and lack regulatory cohesion. The B-onic Platform was conceived as a unified workflow that enables surgical planning, device personalization, and intraoperative navigation within a regulatory-compliant framework. Objective: This study aimed to present a comprehensive single-center clinical evaluation of the implementation of the B-onic Platform in a large single-center cohort, focusing on efficiency, patient safety, and surgeon-reported outcomes. Methods: A retrospective review of 308 consecutive surgical plans was performed at La Paz University Hospital (Madrid, Spain) between 2020 and 2024 and compared with institutional historical controls from 2018 to 2019. Procedures included maxillofacial surgery, traumatology, reconstructive surgery, and other specialties. The platform incorporated imaging-based CAD modeling, 3D-printed biomodels and guides, and immersive validation through the NavigatorPro XR module. Outcomes analyzed were preoperative planning time, operative duration, 30-day complication and rehospitalization rates, intraoperative blood loss, and surgeon-reported perception of anatomical understanding and intraoperative confidence. Results: Mean preoperative planning time was reduced by 34% (−42 h; 95% CI: −48 to −36 h; p < 0.01) compared with historical controls. Mean operative duration decreased from 226 ± 74 min to 181 ± 61 min (−45 min; 95% CI: −52 to −38 min; p < 0.001). The 30-day postoperative complication rate decreased from 12.9% to 10.7% (absolute reduction 2.2%; 95% CI: 0.2–4.1%; p = 0.037), while rehospitalization rates declined from 9.1% to 4.3% (p = 0.012). Mean length of hospital stay decreased from 6.8 ± 3.1 to 5.2 ± 2.3 days (p = 0.022), and intraoperative blood loss was reduced by 12–30% across specialties (p = 0.008). NavigatorPro XR halved validation time for guides and implants (71.8 ± 22.4 h vs. 35.6 ± 18.9 h; p < 0.001). Ninety-two percent of surveyed surgeons reported improved 3D anatomical understanding and enhanced intraoperative safety. Conclusions: The B-onic Platform has transitioned from a prototype to a consolidated system, integrated into routine practice with significant gains in efficiency, safety, and training value. These findings support the potential of the platform as a precision surgery model; however, further multicenter prospective studies are required to confirm scalability.

Background and Objectives: The integration of digital planning and point-of-care (POC) manufacturing has expanded rapidly in oral and maxillofacial surgery (OMFS); however, evidence focusing on regulated, platform-based workflows and their clinical impact remains limited. This study aimed to evaluate the clinical and organizational impact of implementing a unified digital ecosystem centered on the B-Onic platform in routine OMFS practice. Materials and Methods: A retrospective observational study was conducted comparing OMFS procedures planned and executed using the B-Onic platform with a historical control cohort managed with conventional workflows. Surgical cases were categorized into four pathology-based subgroups: facial trauma, oncologic resection and reconstruction, orthognathic surgery, and craniofacial or skull base surgery. Outcomes included preoperative planning time, validation time for guides and implants, surgical duration, intraoperative plan modifications, postoperative complications, 30-day rehospitalization rates, length of hospital stay, and estimated intraoperative blood loss. Results: A total of 110 cases managed using the B-Onic platform were compared with 72 historical control cases. Implementation of the platform was associated with significant reductions in preoperative planning time, validation time, and surgical duration. Clinically relevant improvements were observed in postoperative outcomes, including lower complication rates, reduced 30-day rehospitalization, shorter hospital stays, fewer intraoperative plan modifications, and decreased estimated blood loss. The magnitude of benefit was greatest in high-complexity procedures—particularly oncologic resection and reconstruction and craniofacial or skull base surgery—while more modest effects were observed in orthognathic surgery, reflecting optimized baseline outcomes. Conclusions: The adoption of a regulated, platform-based POC digital ecosystem in oral and maxillofacial surgery is associated with meaningful improvements in workflow efficiency, surgical reproducibility, and postoperative outcomes, especially in complex procedures. These findings support the integration of unified digital platforms as a core component of contemporary OMFS practice and provide OMFS-specific evidence of their clinical and organizational value.

B-onic Suite is an integrated platform that combines surgical planning, personalized medical device development, and intraoperative navigation within a regulatory-compliant workflow. Leveraging patient-specific imaging, the system enables the creation of customized anatomical models, surgical guides, and implants through ISO 13485-certified 3D printing processes. Unlike existing commercial solutions, B-onic Suite ensures end-to-end traceability and compliance with MDR and FDA regulations, bridging engineering precision with clinical safety. Its NavigatorPro XR module offers immersive, extended reality environments for surgical planning and real-time collaboration, facilitating multidisciplinary decision-making and remote expert support. Deployed in routine clinical workflows at La Paz University Hospital, the platform has demonstrated reduced preoperative planning times and improved surgical accuracy. By integrating extended reality into both planning and execution phases, B-onic Suite enhances spatial understanding, reduces intraoperative error rates, and supports surgical training. This unified ecosystem addresses critical limitations of current siloed systems, offering a scalable model for precision medicine. Future developments will incorporate AI-driven planning optimization and adaptive device customization to further increase clinical efficiency and automation.

The SHIELD project aims to enhance the prevention and management of CVD and diabetes through an innovative approach combining multimodal data collection, AI, and collaboration among healthcare stakeholders. By developing personalized risk stratification tools and care plans, SHIELD seeks to empower patients and improve outcomes. Clinical trials across Spain, Italy, and Switzerland will validate the tool’s effectiveness, while insights from this research will inform evidence-based health policies for broader population-wide impact in non- communicable disease prevention.