Ideas in this flowchart

• Digital twins are AI-driven technologies for predicting patient outcomes and personalizing treatment.
• AI-driven technologies improve clinicians’ ability to predict outcomes and personalize treatment plans.
• Digital twins are virtual, continuously updated models of individual patients.
• They integrate EHRs, clinical evaluations, multi-omics, and lifestyle information.
• They simulate disease progression, predict treatment responses, and guide treatment based on each patient’s biology.
• Digital twins also show promise in clinical trial settings.
• Their trial use is particularly relevant to pediatric and rare cancers, where patient enrollment may be limited.
• They can function as synthetic control arms to augment or replace conventional controls.
• These applications are described by Mollica et al. (2024) in ESMO Real World Data and Digital Oncology.