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Commentary|Articles|March 17, 2026
Leveraging “Digital Twins” to Predict Treatment Response in Brain Cancer
Author(s)Sabrina Serani, Baharan Meghdadi, PhD
Fact checked by: Andrea Eleazar, MHS
Digital twin modeling plus metabolomics predicts which drugs can starve glioblastoma, enabling faster, personalized treatment testing.
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Despite decades of advancements in surgical techniques, chemotherapy, and radiotherapy, the clinical outlook for patients diagnosed with primary brain tumors remains sobering. While glioblastoma and other high-grade gliomas are relatively rare compared with other malignancies, they represent a disproportionate burden of cancer-related mortality. According to researchers at the University of Michigan, the lack of significant progress in survival outcomes necessitates a paradigm shift toward highly personalized, data-driven therapeutic strategies.
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