In Silico Trials, Real Impacts!

Beyond the Scalpel: How Computer Models Are Rewriting Paediatric Heart Surgery

This episode explores groundbreaking research from Boston Children's Hospital and Harvard Medical School that demonstrates how multiphysiologic state computational fluid dynamics (CFD) modelling is transforming surgical planning for children with complex congenital heart conditions.
We delve into the innovative 3D virtual surgery workflow developed for patients with single ventricle physiology and interrupted inferior vena cava - a particularly challenging combination that historically carries high risks of life-threatening complications. The research team's approach utilises advanced CFD analysis across multiple physiological states to predict and optimise hepatic venous flow distribution, preventing the formation of pulmonary arteriovenous malformations that can prove fatal in these vulnerable young patients.
The episode examines how this in silico methodology successfully translates virtual surgical planning into real-world clinical outcomes, validated through post-operative MRI imaging. We discuss the broader implications for personalised paediatric medicine, the potential for reducing surgical revisions, and how computational modelling is enabling surgeons to achieve balanced blood flow patterns that were previously difficult to predict using traditional planning methods.
This case study exemplifies the transformative potential of digital health technologies in paediatric care, showcasing how sophisticated computational tools can directly improve surgical outcomes and quality of life for children with complex cardiac conditions.
Source: Hoganson DM, Govindarajan V, Schulz NE, Eickhoff ER, Breitbart RE, Marx GR, Del Nido PJ, Hammer PE. Multiphysiologic State Computational Fluid Dynamics Modeling for Planning Fontan With Interrupted Inferior Vena Cava. JACC Adv. 2024 Jun 13;3(7):101057.
 
 
 

Future-Proofing the UK Life Sciences Sector

Are you prepared for the seismic shift transforming UK life sciences careers? This latest "In Silico Trials, Real Impacts!" episode reveals how AI and in silico technologies are creating unprecedented employment opportunities across health tech sectors. 
Discover the essential skills driving this revolution, from computational biology to digital therapeutics, and why lifelong learning has become non-negotiable. We examine the geographical spread of emerging roles and explore how international talent maintains Britain's competitive advantage in global markets.
What does this transformation mean for traditional biologists, chemists, and clinicians as digital tools reshape their practice? How are government initiatives preparing the next generation for these evolving demands? 
Uncover the real-world implications for patient care and economic growth in this data-driven analysis of our industry's future.
Sources: Lightcast (2024), The UK Skills Revolution: Building a Data-Driven Skills System in an Era of Disruption https://lightcast.io/resources/research/uk-skills-revolution-25Lightcast, ABHI, ABPI, and BIA (2025) Life Sciences 2035: Developing the Skills for Future Growth https://www.abpi.org.uk/publications/life-sciences-2035-developing-the-skills-for-future-growth-main-report/
 
 
 

Exploring the Limitations and Potentials of RCTs: Beyond the Gold Standard

Are Randomised Controlled Trials (RCTs) always the definitive 'gold standard' in research? In the latest episode of In Silico Trials, Real Impacts!, we explore the nuanced landscape of RCTs, questioning their universal applicability and examining the complexities they often obscure. While RCTs are celebrated for their rigour, this discussion delves into their limitations, particularly when findings are applied across diverse contexts.
Drawing on seminal work by Deaton and Cartwright (2018), this episode highlights the critical role that RCTs play in the medical and social sciences, while underscoring the importance of complementing them with observational studies and theoretical frameworks. Ethical considerations and the need for a more integrated approach to research take centre stage, offering a fresh perspective on evidence generation.
Whether you're a researcher, healthcare professional, or simply curious about scientific methodologies, this episode provides thought-provoking insights into the evolving landscape of research.
Source: Deaton A, Cartwright N. Understanding and misunderstanding randomized controlled trials. Soc Sci Med. 2018 Aug;210:2-21.
 
 
 

Simpler or Complex: Rethinking Occam's Razor in Modelling Science

Is simplicity always the smartest choice in science? Or could complexity be the key to groundbreaking discoveries? This episode explores the evolving role of simplicity and complexity in scientific modelling, questioning the age-old principle of Occam's razor in light of modern advancements: Plurality should not be posited without necessity. 
Discover how digital approaches, from computational modelling to simulated clinical trials, are reshaping medical product development, making healthcare safer, more efficient, and unexpectedly precise. As we journey through recent research and breakthroughs, you'll gain insights into the tension between simple and complex scientific models, and how they impact the healthcare landscape.
Whether you're a researcher, regulator, patient representative, or just curious about the future of medicine, this episode unpacks the concept of parsimony and its implications, especially as technology progresses. Learn about the balance between simplicity and complexity and how they complement each other as tools in science.
 
Source:
Dubova M, Chandramouli S, Gigerenzer G, Grünwald P, Holmes W, Lombrozo T, Marelli M, Musslick S, Nicenboim B, Ross LN, Shiffrin R, White M, Wagenmakers EJ, Bürkner PC, Sloman SJ. Is Ockham's razor losing its edge? New perspectives on the principle of model parsimony. Proc Natl Acad Sci U S A. 2025 Feb 4;122(5):e2401230121.
 
 
 
 
 
 

Evaluating Continuous Glucose Monitoring Sensors with in Silico Trials: A Real-World Exemplar

Could computer simulations redefine diabetes care? In this episode, we focus on a real medical product and the role of in silico trials in the transition from the Medtronic Guardian Sensor 3 to the Guardian 4 sensor, central to the Medtronic 780G pump system, which aims to simplify diabetes management by eliminating the need for fingerstick calibrations. Discover how computer simulations, clinical studies, and real-world data converge to evaluate this significant shift, revealing slight shifts in glucose metrics but proving the reliability of in silico methods in predicting real outcomes.
Join us to uncover the potential of digital modeling to transform healthcare, making it more precise while retaining safety, and contemplate how these advances might accelerate personalized medicine delivery, bypassing some traditional trial limitations.
Source:
Grosman B, Parikh N, Roy A, Lintereur L, Vigersky R, Cohen O, Rhinehart A. In Silico Evaluation of the Medtronic 780G System While Using the GS3 and Its Calibration-Free Successor, the G4S Sensor. Ann Biomed Eng. 2023 Jan;51(1):211-224.
 
 
 

Unveiling Evidence-Based Medicine Plus and Mechanistic Reasoning

What is Evidence-Based Medicine Plus? This podcast episode explores the transformative power of computational modelling and simulated clinical trials in medical innovation. Discover the significance of evidence-based medicine (EBM) and evidential pluralism, emphasising the role of mechanistic evidence alongside traditional studies. Join us as we delve into compelling examples like mobile phone radiation and ACE inhibitors, highlighting how these insights enhance the external validity of treatments. Perfect for researchers and regulators alike, or anyone interested in the evolving landscape of medicine.
Sources:
Russo F, Williamson J. Epistemic causality and evidence-based medicine. Hist Philos Life Sci. 2011;33(4):563-81.Parkkinen, V.-P., Wallmann, C., Wilde, M., Clarke, B., Illari, P., Kelly, M. P., Norell, C., Russo, F., Shaw, B., & Williamson, J. (Eds.). (2023). Evaluating Evidence of Mechanisms in Medicine: Principles and Procedures. Oxford University Press.
 
 
 

What Underpins Model Credibility? Three Philosophical Perspectives

How do philosophers of science think about model evaluation? Dive deep into the crucial process of model evaluation, a fundamental step in digital science that determines the effectiveness and precision of computational models.
This episode explores three primary perspectives on model quality: the mirror view, relevant similarity, and fitness for purpose. Learn about the complexities and challenges involved in evaluating models, from data limitations to the intricate balance between accuracy and usability.
Whether you're a researcher, regulator, or a curious listener, discover how these cutting-edge methodologies are reshaping healthcare, improving safety, efficiency, and equitability, one simulated trial at a time. Join us as we delve into the philosophy behind model evaluation and unveil the real-world impact of digital innovation.
Parker WS. Model Evaluation: An Adequacy-for-Purpose View. Philos Sci. 2020;87(3):457-477.
Bokulich A, Parker W. Data models, representation and adequacy-for-purpose. Eur J Philos Sci. 2021;11(31). 
 
 
 
 

Exploring Digital Twins: The Philosophy Behind Healthcare's Digital Revolution

Have you ever wondered what makes a digital twin truly "twin-like" and not just another computer model? This fascinating question lies at the heart of modern healthcare innovation, where virtual copies of real-world systems are revolutionising how we approach medical research and patient care. Our latest episode delves into groundbreaking research that examines the philosophical underpinnings of digital twins, exploring what sets them apart from conventional computational models.
We unpack how digital twins are transforming healthcare through their unique ability to capture complex, emergent behaviours in ways traditional models cannot. From enabling safer drug development through in silico trials to advancing personalised medicine, these sophisticated virtual representations are bridging the gap between computational simulation and real-world applications. Our discussion reveals why digital twins represent more than just technological advancement - they embody a fundamental shift in how we understand and interact with healthcare systems, promising more precise, efficient, and safer medical innovations for the future.
Reference: Wagg DJ, Burr C, Shepherd J, Xuereb Conti Z, Enzer M, Niederer S. The philosophical foundations of digital twinning. Data-Centric Engineering. 2025;6:e12. doi:10.1017/dce.2025.4