Nadea Leavitt
Clinical Statistician and AI Researcher at IQVIA · 11 quotes across 1 episodes
“Digital twins can be used to predict how a patient would respond to different treatments by leveraging their existing medical history and disease response data.”
Digital Twins: Advancing Clinical Evidence Strategy (Sponsored) · 11/16/2026 · observation
“Digital twins help researchers design better studies, evaluate trial strategies, generate individualized predictions, and in some scenarios, even create comparator cohorts, especially when traditional control groups are difficult to obtain.”
Digital Twins: Advancing Clinical Evidence Strategy (Sponsored) · 11/16/2026 · explanation
“IQVIA Life Science models are a family of foundation models that are powered by multimodal data that create a richer digital twin and make patient-level simulation scalable across diseases and use cases in a way that was previously very difficult.”
Digital Twins: Advancing Clinical Evidence Strategy (Sponsored) · 11/16/2026 · explanation
“Life Science models learn from longitudinal real-world data on more than 200 million patients to understand how diseases progress, how patients respond to treatment, how clinical events unfold over time.”
Digital Twins: Advancing Clinical Evidence Strategy (Sponsored) · 11/16/2026 · observation
“If a digital twin is going to influence a trial design decision, a regulatory submission, or ultimately patient access to therapy, then the question isn't whether the model is sophisticated, the question is whether it's fit for purpose we're asking it to serve.”
Digital Twins: Advancing Clinical Evidence Strategy (Sponsored) · 11/16/2026 · opinion
“You have a real patient with their medical history and how their disease responded to a specific treatment, but what you want to know is how this same patient would respond to a different treatment. This is where digital twins come in.”
Digital Twins: Advancing Clinical Evidence Strategy (Sponsored) · 11/16/2026 · explanation
“A digital twin is created or initialized from data about a real patient, and depending on the use case, can actually be updated or re-estimated as the real patient's clinical state evolves and new data becomes available.”
Digital Twins: Advancing Clinical Evidence Strategy (Sponsored) · 11/16/2026 · explanation
“These combine biological knowledge with data-driven learning, often using things like knowledge graphs, ontologies, or mechanistic constraints to keep predictions clinically plausible or to help model scenarios that are not represented in real-world data, while still benefiting from the scale and flexibility of modern AI.”
Digital Twins: Advancing Clinical Evidence Strategy (Sponsored) · 11/16/2026 · explanation
“Patient-level simulation is now scalable across diseases and use cases, whereas this was previously very difficult to achieve.”
Digital Twins: Advancing Clinical Evidence Strategy (Sponsored) · 11/16/2026 · claim
“The 21st Century Cures Act and subsequent rules have driven adoption of standardized APIs, including FHIR-based APIs that make healthcare data increasingly accessible and exchangeable across health systems in a common format.”
Digital Twins: Advancing Clinical Evidence Strategy (Sponsored) · 11/16/2026 · trend
“Transparency is essential. People need to understand where the underlying data came from, how the model was trained, what assumptions are built into it, and how uncertainty is quantified.”
Digital Twins: Advancing Clinical Evidence Strategy (Sponsored) · 11/16/2026 · opinion