In silico clinical trials in the orthopedic device industry: from fantasy to reality?
Open accessAbstract
The orthopedic device industry relies heavily on clinical evaluation to confirm the safety, performance, and clinical benefits of its implants. Limited sample size often prevents these studies from capturing the full spectrum of patient variability and real-life implant use. The device industry is accustomed to simulating benchtop tests with numerical methods and recent developments now enable virtual "in silico clinical trials" (ISCT). In this article, we describe how the advancement of computer modeling has naturally led to ISCT; outline the potential benefits of ISCT to patients, healthcare systems, manufacturers, and regulators; and identify how hurdles associated with ISCT may be overcome. In particular, we highlight a process for defining the relevant patient risks to address with ISCT, the utility of a versatile software pipeline, the necessity to ensure model credibility, and the goal of limiting regulatory uncertainty. By complementing-not replacing-traditional clinical trials with computational evidence, ISCT provides a viable technical and regulatory strategy for characterizing the full spectrum of patients, clinical conditions, and configurations that are embodied in contemporary orthopedic implant systems.
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This paper complements and builds upon related work, including a theoretical framing for credibility of in silico studies, a discussion of limitations of ASME V&V40 2018 for ISCTs, a framework for executing an ISCT using VVUQ concepts, and a proposed alteration to ASME V&V40 2018 for ISCTs.
“This paper complements and builds upon related work, including a theoretical framing for credibility of in silico studies [10], a discussion of limitations of ASME V&V40 2018 for ISCTs [11], a framework for executing an ISCT using VVUQ concepts [12], and a proposed alteration to ASME V&V40 2018 for ISCTs, including modification of the risk assessment stage which is outside the scope of the present”
From Credibility assessment of in silico clinical trials for medical devices (2024) · cites this paper as [11]
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- Authors
- Favre, P., Maquer, G., Henderson, A., Hertig, D., Ciric, D., & Bischoff, J. E.
- Affiliations
- Zimmer Biomet (Switzerland) (CH)
- Zimmer Biomet (United States) (US)
- Corresponding author
- Favre, Philippe
- Venue
- Annals of Biomedical Engineering
- Published
- 2021-05-10
- Volume
- 49
- Issue
- 12
- Pages
- 3213-3226
- ISSN
- 0090-6964 (ISSN-L)
- 1573-9686
- PMC
- PMC8110242
- OpenAlex
- W3162989881
- Cited by
- 32
- References
- 41
- Citations by year
- 2026: 9 · 2025: 3 · 2024: 7 · 2023: 5 · 2022: 7 · 2021: 1
- FWCI
- 4.69
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Annals of Biomedical Engineering (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Zimmer Biomet
- Topics
- Health Sciences › Medicine › Surgery › Orthopaedic implants and arthroplasty
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- in silico clinical trials, orthopedic implants, computer modeling, patient heterogeneity, model credibility, regulatory uncertainty, computational evidence, implant safety, software pipeline
- MeSH terms
- Computer Simulation, Europe, Humans, Industry, Orthopedic Equipment, Software, Equipment Failure Analysis
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