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

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.

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 

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.

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

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-

Koldeweij CJM, Dibbets AC, Ceulemans M, de Vries LC, Franklin BD, Scheepers

Koldeweij C, Kleuskens M, Litjens C, Franklin BD, Scheepers HCJ, de Wildt SN.

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.

This week, we explore the ground-breaking potential of digital twins (DTs) to transform drug discovery and clinical trials. Generative AI, capable of creating realistic virtual representations of biological systems, is at the heart of this revolution. From simulating drug responses in individual cells to predicting patient outcomes in clinical trials, DTs promise to accelerate drug development and enhance precision medicine. We examine current applications and discuss challenges, including data scarcity and the need for greater model interpretability. Join us as we look ahead to the future of DTs, with a focus on multimodal and foundation models that offer a holistic understanding of complex biological systems.

Bordukova M, Makarov N, Rodriguez-Esteban R, Schmich F, Menden MP. Generative artificial intelligence empowers digital twins in drug discovery and clinical trials. Expert Opin Drug Discov. 2024 Jan-Jun;19(1):33-42. 

In this episode, we dive into the fascinating field of Physiologically Based Pharmacokinetic (PBPK) modelling, a revolutionary approach to transforming drug development. Discover how digital replicas of the human body are created to predict drug behaviour, offering a safer, more efficient, and more precise method for developing medications.

Explore the potential of PBPK to personalize medicine, reduce animal testing, and foresee long-term drug effects. Learn about the challenges and opportunities in this evolving field, and how it promises to reshape the future of healthcare.

Whether you're a researcher, regulator, or just curious about the future of medicine, join us as we uncover the real-world impact of computer-simulated trials. Get ready to witness how algorithms and data are saving lives, and the exciting possibilities that lie ahead in the world of PBPK modeling.

Frechen S, Rostami-Hodjegan A. Quality Assurance of PBPK Modeling Platforms and Guidance on Building, Evaluating, Verifying and Applying PBPK Models Prudently under the Umbrella of Qualification: Why, When, What, How and By Whom? Pharm Res. 2022 Aug;39(8):1733-1748. 

This episode asks: Can computer simulations provide credible regulatory evidence?

Learn about the hierarchical framework that ensures the trustworthiness of virtual trials, using a Lego analogy to break down complex processes into manageable pieces. Understand how virtual devices, patients, and even surgeons are modelled to reflect real-world scenarios.

We also discuss the broader implications of this innovative framework and how it could lead to faster, more personalized, and more inclusive medical device development. Tune in to uncover the future of medicine and the role you can play in shaping it.

Aycock KI, Battisti T, Peterson A, Yao J, Kreuzer S, Capelli C, Pant S, Pathmanathan P, Hoganson DM, Levine SM, Craven BA. Toward trustworthy medical device in silico clinical trials: a hierarchical framework for establishing credibility and strategies for overcoming key challenges. Front Med (Lausanne). 2024 Aug 12;11:1433372.