Probability & Patients: The Stochastic Science Behind In Silico Trial Breakthroughs

Probability & Patients: The Stochastic Science Behind In Silico Trial Breakthroughs

𝗪𝗵𝗮𝘁 𝗶𝗳 𝘁𝗵𝗲 𝗻𝗲𝘅𝘁 𝗰𝗹𝗶𝗻𝗶𝗰𝗮𝗹 𝘁𝗿𝗶𝗮𝗹 𝗯𝗿𝗲𝗮𝗸𝘁𝗵𝗿𝗼𝘂𝗴𝗵 𝗶𝘀 𝗮𝗹𝗿𝗲𝗮𝗱𝘆 𝗶𝗻 𝘆𝗼𝘂𝗿 𝗰𝗼𝗺𝗽𝘂𝘁𝗲𝗿? This episode explores the fascinating world of virtual patient models and stochastic engineering, unveiling how digital simulations are revolutionising healthcare clinical trials. Discover how simulated trials using sophisticated virtual patient models—complete with variations in age, body size, and disease progression—are introducing groundbreaking innovations in patient care.

We delve into stochastic engineering models that cleverly integrate uncertainty into device design, offering more precise and realistic predictions of clinical outcomes. Learn about the power prior method—a dynamic approach to combining digital and real-world evidence in clinical trials, enhancing efficiency and accelerating device delivery to patients whilst maintaining rigorous safety and accuracy standards.

Join us for an illuminating discussion at the cutting edge of healthcare innovation, where virtual modelling meets real-world patient impact.

Haddad T, Himes A, Thompson L, Irony T, Nair R; MDIC Computer Modeling and Simulation Working Group Participants. Incorporation of stochastic engineering models as prior information in Bayesian medical device trials. J Biopharm Stat. 2017;27(6):1089-1103.

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