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Nikhil Pattani, Jaspinder Sanghera, Emily Mills, William Bolton, Deena Harji, Joshua Burke, 60 In-Silico Modelling in the Development of Novel Devices in Thoracic and Abdominal Surgery: A Systematic Review, British Journal of Surgery, Volume 112, Issue Supplement_6, March 2025, znaf042.030, https://doi.org/10.1093/bjs/znaf042.030
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Abstract
Surgical innovation has made significant leaps in recent years, but the adoption of novel devices has lagged due to prolonged efficacy and safety assessment through randomised controlled trials. In-silico modelling may provide a solution, utilising computational simulations to develop and improve surgical devices. This systematic review aimed to evaluate the current use of in-silico modelling for devices utilised in thoracic and abdominal surgery.
Studies in the last five years were searched in PubMed databases (Jan 2019 - Aug 2024). Specified inclusion criteria included original studies using mathematical/computational modelling to investigate thoracic/abdominal surgical devices which are invasive in nature.
Of 2968 studies derived from the search strategy, 42 were included in the final analysis and categorised by surgical specialty: general surgery (n=4); hepato-pancreato-biliary (n=2); vascular (n=5); paediatric (n=9); and cardiothoracic (n=22). Three core themes were identified: proof of concept (n=19), device improvement (n=22), and in-silico clinical trials (ISCTs) with simulated human patients (n=1). Most studies were at IDEAL stage 0 (pre-clinical) and 19 studies validated in-silico results with in-vitro/ in-vivo data.
In future, in-silico modelling could replace components of pre-clinical in-vitro and in-vivo testing of surgical devices. Applications include generating efficacy data for novel devices in the pre-clinical stage, modelling minority patient demographics or rare diseases, and developing/repurposing existing devices to reduce complications. Standardised core outcomes and credibility frameworks will minimise inter-study heterogeneity in methodologies and reporting of results. Global collaboration will help bring in-silico modelling to the forefront of surgical device research.