The National Science Foundation Division of Mathematical Sciences awarded the University of Massachusetts $558,159 on November 1, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049) to develop a theranostic digital twin computational model for personalized radiopharmaceutical therapy dosing in cancer treatment.
The project will create a continuously updated virtual patient model built from imaging scans and blood biomarkers collected before and during treatment. The digital twin combines mathematical equations describing drug transport through the body with artificial intelligence methods trained on patient data to forecast radiation dose distribution to tumors and healthy organs before each treatment cycle and recommend patient-tailored injection dosages. The framework addresses current clinical limitations in radiopharmaceutical therapy, where fixed dosages regardless of patient variation in body size, tumor burden, or organ clearance rates leave some patients undertreated while exposing others to organ toxicity. The mathematical framework applies to any radiopharmaceutical drug that can be imaged and delivered over multiple treatment cycles, with potential extension to cancers including neuroendocrine tumors.
Work is performed in Amherst, Massachusetts, with a period of performance from November 1, 2026, through October 31, 2029.