Toward a Digital Twin Maturity Model for Medicine

<p dir="ltr">This presentation was delivered at the 2025 Institute for Mathematical and Statistical Innovation Long Course on Complex Digital Twins.</p><p dir="ltr">To answer the increasingly common question I receive, “Will FDA regulate my digital twin?”, it must first deconstruct it into two foundational inquiries:(1) What is the physical asset being twinned? and(2) What is the context of use for the digital twin? From there, one must also ask whether a digital twin is necessary for that context of use, or whether a simpler computational model or AI-enabled simulation may suffice. Understanding this distinction is critical to determining when a digital twin crosses into regulatory oversight. </p><p dir="ltr">This presentation reviews the current landscape of tools and technologies being referred to as digital twins across the life sciences—from mechanistic organ models and AI-augmented simulations to population-scale synthetic patient cohorts. A Digital Twin Maturity Model will be presented for community input, which characterizes levels of maturity across the different components of a digital twin. Finally, we will propose a framework for mapping digital twin maturity to the existing regulatory ecosystem, highlighting how current FDA guidance documents can be leveraged to determine when and how a digital twin may fall under regulatory purview. The goal is to provide a shared vocabulary and practical structure to help developers, sponsors, and regulators navigate the evolving landscape of digital twins in biomedical research and healthcare.</p>