In Silico Trials, Real Impacts!

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.
 
 
 
 
 
 

Revolutionising Drug Discovery with Digital Twins

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. 
 
 
 

Unlocking the Future of Medicines with PBPK Modelling

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. 
 
 
 
 
 
 
 
 
 

Can Computer Simulations Provide Trustworthy Regulatory Evidence?

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. 
 
 
 
 
 
 

The Digital Revolution in Medical Imaging Trials: The VICTRE Trial

In this episode, we explore the fascinating world of in silico trials—a cutting-edge approach that could revolutionize how new medical technologies are tested and approved. Imagine conducting clinical trials entirely within a computer simulation, bypassing the need for expensive and time-consuming real-world testing. This futuristic-sounding method is already being utilized today, offering a glimpse into the future of healthcare.
We delve into a groundbreaking study that leveraged in silico trials to test a new breast cancer screening technology called Digital Breast Tomosynthesis (DBT). Unlike traditional mammograms, DBT provides a detailed 3D image of breast tissue, potentially improving early detection of cancer. By creating virtual patients and using advanced computer models, researchers simulated the effectiveness of DBT, achieving results that aligned with real-world clinical trials.
Join us as we discuss the implications of this technology not only for imaging but for drug development and personalized medicine. Could this be the end of traditional clinical trials? While in silico trials show immense potential, challenges remain, and real-world testing will still play a crucial role. Nevertheless, this innovative approach represents a significant step towards a more efficient and safer future in medical research and treatment.
Badano A, Graff CG, Badal A, Sharma D, Zeng R, Samuelson FW, Glick SJ, Myers KJ. Evaluation of Digital Breast Tomosynthesis as Replacement of Full-Field Digital Mammography Using an In Silico Imaging Trial. JAMA Netw Open. 2018 Nov 2;1(7):e185474. 
 
 
 
 
 
 
 
 
 

Virtual Trials and the Future of Medical Imaging

In this episode, we embark on a journey into the world of virtual trials, particularly in the realm of medical imaging. Discover how digital twins—virtual replicas of human anatomy—are revolutionizing healthcare by offering safer, faster, and more efficient methods for testing new imaging technologies.
Learn about the incredible potential of virtual trials to optimize medical imaging techniques and personalize patient care. We discuss the challenges of accessibility, diversity, and reproducibility in this emerging field, and highlight the importance of collaboration among researchers, regulators, and patients.
Tune in to understand how virtual trials are not only advancing medical imaging but also driving a revolution that puts patients at the forefront of innovation. Join us as we uncover the real-world impact of these digital breakthroughs in healthcare.
 
Abadi E, Barufaldi B, Lago M, Badal A, Mello-Thoms C, Bottenus N, Wangerin KA, Goldburgh M, Tarbox L, Beaucage-Gauvreau E, Frangi AF, Maidment A, Kinahan PE, Bosmans H, Samei E. Toward widespread use of virtual trials in medical imaging innovation and regulatory science. Med Phys. 2024 Oct 6. doi: 10.1002/mp.17442.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

The Brain's Hidden Power: Self-Healing Aneurysms

Ever wondered if your brain has the ability to heal itself? In this episode, we delve into a medical mystery that feels like science fiction: the phenomenon of spontaneous thrombosis, where brain aneurysms may naturally seal themselves off. Discover how researchers are using advanced computer modelling with virtual patients to explore this incredible process.
We explain the basics of aneurysms, likening them to weak spots in a garden hose, and explore how size and shape affect their ability to self-heal. Larger and taller aneurysms are more prone to clotting due to slower blood flow, much like a still pond versus a rushing river.
Intriguingly, high blood pressure might actually hinder this self-repair process by creating turbulent blood flow. Through a detailed study of a virtual patient's aneurysm, researchers found that high blood pressure increases the shear rate, making clot formation less likely.
Join us as we explore the potential for leveraging the brain's natural healing abilities to treat aneurysms, moving towards a future where treatment is less invasive and more aligned with the body's innate capabilities. This research opens the door to personalized medicine and new hope for medical breakthroughs.
 
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. doi: 10.1063/5.0144848.