ArticleBMJ innovations2025
Use of in silico research in the development of abdominal and thoracic surgical devices: a systematic review.
Article in BMJ innovations, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
8 authors.
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Abstract
Objective: Surgical innovation has exponentially improved over the past three decades. However, efficacy assessment of surgical devices through randomised controlled trials requires significant resources. In silico modelling may provide a solution, utilising computational simulations to develop and improve devices. This study aims to evaluate the current use of in silico modelling for devices used in abdominal and thoracic surgery. Design: A systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Data Resources: PubMed, MEDLINE and Embase databases from January 2019 to August 2024 were searched. Eligibility criteria for selecting studies: Inclusion criteria were defined as studies using mathematical/computational models to investigate invasive devices implanted or incorporated in abdominal and thoracic surgery. Results: The search strategy yielded 2968 studies, with 42 included in the final analysis. Core themes identified included proof of concept (n=19), device improvement (n=22) and in silico clinical trials with simulated human patients (n=1). Specialities included: general surgery (n=4); hepato-pancreato-biliary (n=2); vascular (n=5); paediatric (n=9) and cardiothoracic (n=22). Most studies were at IDEAL stage 0 (preclinical) and 19 studies validated in silico results with in vitro/in vivo data. Conclusion: In silico modelling can complement preclinical in vitro and in vivo testing for surgical devices. Its applications include simulating rare diseases, modelling diverse patient demographics, and generating early efficacy data for novel or repurposed devices. Standardising methodologies through a core outcome set and credibility framework is essential to reduce inter-study heterogeneity. Global collaboration and clear regulatory guidance are key for its integration into mainstream surgical device research.
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