Are you researching/developing digital twin models to advance cancer research? If so, consider applying for this “Digital Twins Radiation Oncology” administrative supplement opportunity.

Wondering if your research is applicable? Consider these predictive oncology scenarios that could benefit from the implementation of a digital twin model:

• You’re determining the best clinical trial for a patient.
• You’re anticipating possible short- and long-term complications of treatment, and you seek to avoid them.
• You’d like to predict the best frequency for follow-up monitoring.
• You’d like to know which clinical tumor volume margin to use.

Your funding application must:

• propose a new, collaborative digital twin project that merges data science with predictive radiation oncology.
• include at least one innovative use of patient-specific dynamic data to augment predictions and treatment decisions.