In Silico Trials, Real Impacts

Breaking New Ground: The Virtual Trial Transforming Knee Surgery

Can 3D-printed, personalized knee surgery implants revolutionize arthritis treatment? Virtual clinical trials show promising results for a custom device that could make corrective knee surgery safer and more accessible. Discover how computer simulations are paving the way for the future of personalized orthopaedics.MacLeod AR, Peckham N, Serrancolí G, Rombach I, Hourigan P, Mandalia VI, Toms AD, Fregly BJ, Gill HS. Personalised high tibial osteotomy has mechanical safety equivalent to generic device in a case-control in silico clinical trial. Commun Med (Lond). 2021 Jun 30;1:6. doi: 10.1038/s43856-021-00001-7.
 
 
 
 
 
 

Standards as Innovation Catalysts: The PAGIT Framework

How can we unlock innovation while ensuring responsible governance? Dive into the evolution of the PAGIT framework, where standards meet strategic oversight. From disruptive technologies to incremental advances, discover how this groundbreaking approach is reshaping the UK's innovation landscape. Join us to explore how smart regulation and standards are building tomorrow's technological future.
Tait J (2024) The PAGIT framework: Its role in the governance of UK technologies to drive greater innovation, BSI, https://www.bsigroup.com/en-GB/insights-and-media/insights/whitepapers/update-to-pagit-framework-for-innovation.

In Silico vs. Real Life: Can Computer Models Outperform Spine Surgery Tests?

Can computers predict if medical devices are safe? Discover how virtual testing revolutionises surgical implant design, potentially saving millions in development costs and speeding up innovation. Learn how digital twins are helping bring safer bone screws to the operating room, faster than ever before.
 
Nagaraja S, Loughran G, Baumann AP, Kartikeya K, Horner M. Establishing finite element model credibility of a pedicle screw system under compression-bending: An end-to-end example of the ASME V&V 40 standard. Methods. 2024 May;225:74-88. doi: 10.1016/j.ymeth.2024.03.003.

Heartware: Programming the Perfect Heartbeat

This week we ask: Can computers help us revolutionise heart failure treatment? Join us as we explore how computational modelling is transforming cardiac pacing therapy. Discover how virtual trials are accelerating research, optimising treatment strategies, and improving patient outcomes—all before a single device is implanted. Learn how this cutting-edge approach is helping clinicians identify the right treatment for the right patient, potentially changing the future of cardiac care. A fascinating intersection of computer science and cardiology you won't want to miss.
 
Strocchi M, Wijesuriya N, Mehta V, de Vere F, Rinaldi CA, Niederer SA. Computational Modelling Enabling In Silico Trials for Cardiac Physiologic Pacing. J Cardiovasc Transl Res. 2024 Jun;17(3):685-694. doi: 10.1007/s12265-023-10453-y.
 

Digital Twins Revolutionizing Shoulder Implant Design

Ever wondered how we can make shoulder replacements safer without endless clinical trials? In today's episode, we dive into groundbreaking research that's revolutionising orthopaedic device testing through virtual simulations. We'll explore how researchers have developed a sophisticated computational model that predicts when shoulder implants might loosen – a critical concern in shoulder replacement surgery.
What makes this study fascinating is its dual-validation approach, which combines laboratory tests with real-world clinical data. We'll unpack how the team validated their virtual model using foam block experiments and actual patient outcomes, creating a bridge between controlled testing and clinical reality.
But here's the real kicker – this research could transform how we test medical devices, potentially reducing the need for extensive human trials. We'll discuss how this model handles different implant designs and surgical variations and what it means for the future of orthopaedic device development.
Join us as we explore the intersection of virtual testing and real-world medicine!
 
Maquer G, Mueri C, Henderson A, Bischoff J, Favre P. Developing and Validating a Model of Humeral Stem Primary Stability, Intended for In Silico Clinical Trials. Ann Biomed Eng. 2024 May;52(5):1280-1296. doi: 10.1007/s10439-024-03452-w
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Enhancing UK Medicine Regulation

Can the UK reclaim its crown as a clinical trials powerhouse? As Baroness Merron champions modernised regulations through Parliament, ABPI's candid assessment of MHRA reveals both progress and untapped potential. Join us in this bonus episode to explore how strategic reforms could transform the UK into a global life sciences leader.Association of British Pharmaceutical Society (2024). Enhancing the role of UK medicine regulation. https://www.abpi.org.uk/publications/enhancing-the-role-of-uk-medicine-regulation
Baroness Merron (2024) Clinical Trials Regulations. Statement on UK Parliament 12-12-24. https://questions-statements.parliament.uk/written-statements/detail/2024-12-12/hlws306 
 
 
 
 
 
 

How Regulatory-Ready is Model-Informed Drug Development?

Can we truly trust mathematical models to shape the future of medicine? In this episode, we explore the fascinating world of Model-Informed Drug Development (MIDD)—a game-changing approach that blends cutting-edge simulations with real-world data to revolutionise how drugs are developed and approved.
With the new ICH M15 Guideline, the global pharmaceutical landscape is moving towards a harmonised framework that ensures credibility, consistency, and trust in MIDD evidence. But how do these models hold up under scrutiny? And what does this mean for patient safety, regulatory decision-making, and the future of innovation in healthcare?
Join us for an engaging discussion on the science, risks, and rewards of MIDD, and discover how this transformative approach is reshaping the way medicines are brought to life.
 
Marshall S, Ahamadi M, Chien J, Iwata D, Farkas P, Filipe A, Frey N, Greene E, Kawai N, Li J, Lippert J, Musuamba Tshinanu F, Manolis E, Peterson MC, Sarem S, Shebley M, Tegenge M, Tsai CH, Tu CL, Otsubo Y, Wei J, Zhang L, Zhu H, Karlsson KE. Model-Informed Drug Development: Steps Toward Harmonized Guidance. Clin Pharmacol Ther. 2023 Nov;114(5):954-959. doi: 10.1002/cpt.3006.
 
 
 
 
 
 

Shaping In Silico Medicine: The Power of Patient and Public Involvement

Public and patient involvement (PPI) have a central role in advancing the adoption of in silico technologies. We explore insights from two pivotal documents: a position paper from the Avicenna Alliance advocating for a coordinated international approach to PPI in digital health and feedback from a UK public advisory panel that influenced a groundbreaking UK Centre of Excellence on In Silico Regulatory Science and Innovation initiative led by InSilicoUK. Join us as we uncover the challenges, successes, and actionable strategies driving cultural change and fostering collaboration between researchers, patients, and the public in this rapidly evolving field.
 
www.insilicouk.org
www.avicenna-alliance.com
 
 
 
 
 
 

Model-Informed Medicine Revolutionising Pregnancy Prescriptions

In an era where precision matters most, computational modelling is reshaping how we approach medication during pregnancy. Join us as we explore groundbreaking research revealing how healthcare providers and expectant mothers are embracing mathematical simulations to tackle one of medicine's most complex challenges: safe and effective dosing during pregnancy. Discover why these sophisticated in silico approaches are gaining support in antenatal care, and what this means for the future of maternal-fetal medicine. We'll unpack the science, explore the stakeholder perspectives, and examine how these computational tools could transform pregnancy care from guesswork to precision medicine.
 
Koldeweij C, Dibbets C, Franklin BD, Scheepers HCJ, de Wildt SN. A User-Driven Framework for Dose Selection in Pregnancy: Proof of Concept forSertraline. Clin Pharmacol Ther. 2024 Sep 9. doi: 10.1002/cpt.3429. 
Koldeweij CJM, Dibbets AC, Ceulemans M, de Vries LC, Franklin BD, ScheepersHCJ, de Wildt SN. Willingness-to-use and preferences for model-informedantenatal doses: a cross-sectional study among European healthcare practitionersand pregnant women. Front Pharmacol. 2024 Aug 15;15:1403747. doi:10.3389/fphar.2024.1403747.
Koldeweij C, Kleuskens M, Litjens C, Franklin BD, Scheepers HCJ, de Wildt SN.Perceived barriers and facilitators for model-informed dosing in pregnancy: aqualitative study across healthcare practitioners and pregnant women. BMC Med.2024 Jun 18;22(1):248. doi: 10.1186/s12916-024-03450-8. 
 
 
 
 
 
 

Can Synthetic Data Solve Healthcare's Bias Problems?

Ever wondered how scientists test new treatments without real patients? Discover how cutting-edge technology creates 'virtual twins' for medical research, ensuring everyone's fairly represented. Learn how this groundbreaking approach revolutionises healthcare testing while keeping it safer and more inclusive for all.
Draghi B, Wang Z, Myles P, Tucker A. Identifying and handling data bias within primary healthcare data using synthetic data generators. Heliyon. 2024 Jan 10;10(2):e24164. doi: 10.1016/j.heliyon.2024.e24164.