DigitalTwin pilot project funded by DoE & NCI

We are developing a Digital Twin (DT) by integrating baseline multi-modal data and repeated measurements for real-time dynamic model training and updating. We will take advantage of innovations in the areas of cancer clinical and biological research, molecular profiling, artificial intelligence, and computing technologies to realize a DT for monitoring treatment response vs. treatment resistance. More specifically, we propose an adaptive dynamic DT to predict response to initial therapy as well as in the maintenance phase to assess resistance mechanisms and enable rapid and effective treatment reassignment. This DT will help physicians make initial treatment determinations, monitor treatment response and effectiveness, and decide when to discontinue or change approach. This work has been funded by the Department of Energy (DoE) & National Cancer Institute (NCI).

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