A simulation-first approach: In Silico Technologies for Medical Innovation in the Digital Era
By Professor Alejandro Frangi, Bicentennial Turing Chair in Computational Medicine at the Royal Academy of Engineering
Introduction
In Silico Methods drive scientific innovation by leveraging computer simulation instead of biological testing. This innovative technology facilitates discoveries though complex data analysis connecting a wide variety of tools from biology, computing, and mathematics (Translational Bioinformatics in Healthcare and Medicine, 2021).
This article explores how virtual trials can make medical innovations safer, more efficient, and more widely accessible.
The Challenge: Limitations of Current Testing Methods
As we stand on the brink of a new era in medical technology, the importance of robust scientific evidence to ensure the safety and efficacy of novel medical interventions cannot be overstated. Traditional methods, such as bench testing and animal studies followed by clinical trials, have served us well but often fall short in predicting rare side effects that only emerge after widespread use. Bench testing is limited in reproducing human physiology with accuracy; animal testing raises concerns on animal welfare and may not reliably predict human responses due to biological differences (source); and human clinical trials are regarded as the gold standard but are costly, time-consuming, and ethically complex.
The limitations of traditional methods are widely recorded in academic research, making the potential of In Silico Technologies a groundbreaking approach and a beneficial addition to the development of medical technology globally.
The Solution: A Simulation-First Approach
The human and financial implications of late-stage medical device failures can be devastating, and extensive human testing is often impractical, especially for paediatric patients, rare diseases, and hard-to-reach ethnic groups.
Computational Medicine, or In Silico Medicine, leverages the power of engineering, mathematics, and computational sciences to revolutionise our understanding and treatment of human diseases. In silico trials (IST) utilise computer-based trials with populations of digital twins (virtual patients) to simulate and predict clinical outcomes of medical devices. This innovative approach allows for an exhaustive exploration of potential risks and failure modes before any physical trials commence, significantly enhancing patient safety and reducing the time and cost associated with bringing new medical technologies to market.
The consolidation of in silico evidence is set to transform health and life sciences research, development, and regulatory processes. For first mover countries, this presents a unique opportunity to lead the way in health and life sciences, driving economic growth and providing citizens with early access to cutting-edge healthcare products. However, the journey is not without challenges. Regulatory harmonisation, in silico evidence integration in regulatory pathways, and effective cross-sector collaboration are critical hurdles that must be overcome to realise the full potential of in silico trials.
Regulatory bodies in the UK, US and EU are already recognising the value of in silico trials, establishing frameworks to support their integration into the medical device approval process. International harmonisation of regulatory standards is essential to facilitate the global adoption of in silico trials, ensuring that his new form of evidence is recognised and accepted across different jurisdictions while meeting the same or more stringent safety standards than today.
The future of medicine lies in the successful implementation of in silico trials, and this requires a concerted effort from all stakeholders. Cross-sector collaboration and international harmonisation of regulatory science are paramount. By fostering partnerships between academia, industry, regulators, and policymakers, we can ensure that the necessary technical, regulatory, and ethical standards are met. This collaborative approach will pave the way for a new era of medical innovation, ultimately accelerating the delivery of innovative solutions to patients while upholding the highest safety standards
When applied to medical devices testing, In Silico Technologies allow us to:
1. Use advanced computer models early in the development process
2. Simulate device behaviour under various conditions before physical testing
3. Identify and resolve potential issues early, saving time and money
4. Enhance device safety and performance through virtual optimisation
Therefore, In Silico Technologies can use detailed predictive models and virtual patient populations to test medical devices. This approach offers several advantages as it provides a controlled and reproducible testing environment, it more accurately replicates real-world conditions and patient variability, and it generates robust data for regulatory submissions and clinical decisions.
Real-World Example: In Silico Trial of Intracranial Flow Diverters
The FD-PASS study (source) illustrated the power of In Silico Trials. The flow diverter performance assessment (FD-PASS) in-silico trial modeled the treatment of intracranial aneurysms in 164 virtual patients with 82 distinct anatomies simulating both normotensive and hypertensive patient phenotypes using a flow-diverting stent. Computational fluid dynamics were employed to quantify post-treatment flow reduction. The predicted FD-PASS flow-diversion success rates mirrored those previously reported in three clinical trials or registries (PUFS, PREMIER and ASPIRE). This in-silico approach enabled a broader investigation of factors associated with insufficient flow reduction than what was feasible in a conventional trial. The findings demonstrated that in-silico trials of endovascular medical devices could replicate the results of traditional clinical trials to a 5% accuracy and perform virtual experiments and subgroup analyses that are challenging or impossible in conventional trials, thereby uncovering new insights into treatment failure, such as in the presence of side branches or hypertension.
Conclusion
Adopting a simulation-first approach enhances traditional methods by addressing potential issues early through virtual testing, reducing patient harm and trial failures, and improving cost-effectiveness and efficiency in device development. This approach also enhances safety and reliability from initial design to post-market monitoring.
As such, In Silico trials represent a significant leap forward in medical device development. By harnessing the power of computational modelling and simulation, we can create safer, more effective medical devices more quickly and at lower cost. This approach promises to revolutionise healthcare, leading to more equitable access to cutting-edge medical technologies and ultimately better outcomes for patients in the UK and worldwide.
As we embrace this digital transformation in medical innovation, we're not just changing how we develop devices – we're paving the way for a new era of personalised, efficient, and safer healthcare for all.
Resources
- Díaz-Struck, E. (2018). New Database Tracks Faulty Medical Devices Across The Globe. Retrieved from https://www.icij.org/investigations/implantfiles/new-database-tracks-faulty-medical-devices-across-the-globe
- The Cumberledge Report. www.immdsreview.org.uk
- KPMG (United Kingdom). (2024). In Silico Regulatory Evidence Utilisation within the Life Science Sector (Version v1). KPMG Life Science Regulatory Solutions and InSilicoUK Pro-Innovation Regulations Network. https://doi.org/10.5281/zenodo.12735158
- Sertkaya A, DeVries R, Jessup A, Beleche T. Estimated Cost of Developing a Therapeutic Complex Medical Device in the US. JAMA Netw Open. 2022 Sep 1;5(9):e2231609.
- Dubin JR, Enriquez JR, Cheng AL, Campbell H, Cil A. Risk of Recall Associated With Modifications to High-risk Medical Devices Approved Through US Food and Drug Administration Supplements. JAMA Netw Open. 2023 Apr 3;6(4):e237699.
- Sarrami-Foroushani A, Lassila T, MacRaild M, Asquith J, Roes KCB, Byrne JV, Frangi AF. In-silico trial of intracranial flow diverters replicates and expands insights from conventional clinical trials. Nat Commun. 2021 Jun 23;12(1):3861.
- Reagan-Udall Foundation for the FDA. In Silico Technologies: A Strategic Imperative for Accelerating Breakthroughs and Market Leadership for FDA-Regulated Products. 2024. https://reaganudall.org/regulatory-science-accelerator-computational-modeling-simulation-cms-fda-regulated-products
- Liu Q, Sarrami-Foroushani A, Wang Y, MacRaild M, Kelly C, Lin F, Xia Y, Song S, Ravikumar N, Patankar T, Taylor ZA, Lassila T, Frangi AF. Hemodynamics of thrombus formation in intracranial aneurysms: An in silico observational study. APL Bioeng. 2023 Jul 7;7(3):036102.
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