Digital twin (tumor)
Also known as: digital twin · patient-specific digital twin
Computational models calibrated to an individual tumor or model system to simulate growth and treatment response; examples in the library are TumorTwin, anatomy-aware simulation of GBM xenografts and a proteome-calibrated GBM astrocyte twin (preprint). None has been prospectively validated for clinical use. VC0134 VC0133 VC0071 · preprint
Review pending Version 0.1.0 · status: draft · last expert review: not yet reviewed
Relations
| Subject | Relation | Object | Confidence | Evidence (role) |
|---|---|---|---|---|
| TumorTwin | associated with | Digital twin | high | VC0134 supports From: entity record |
Appears in research topics
- AI virtual cell models (Models)
Appears in library items (4)
Items whose title, tags or one-line summary match this entity (derived from the data), plus the items cited as evidence for the description.
- VC0077 Generative AI for spatial tumor growth on MRI: a proof-of-principle study in pediatric diffuse midline glioma. — Laslo D et al., BMC medicine, 2026
- VC0134 TumorTwin: a Python framework for patient-specific digital twins in oncology — Kapteyn et al., BMC Med Inform Decis Mak, 2026
- VC0071 · preprint A Proteome-Calibrated Mechanistic Digital Twin of the Glioblastoma Astrocyte Derived from Patient Multi-Omic Data — Mayfield JD., bioRxiv, 2026
- VC0133 Anatomically aware simulation of patient-specific glioblastoma xenografts — Malik et al., PLoS Comput Biol, 2026
For research and education only. Not medical advice and not a recommendation of any diagnosis, treatment or product. Patients should consult their own physicians.