Oncology ↔ Statistical Physics

Tumor vascular network fragmentation under adaptive therapy maps directly onto percolation-threshold transitions studied in statistical physics.

PROPOSED
oncology statistical-physics network-science

🔭 Overview

When a tumor's blood-supply network is disrupted below its percolation threshold, large-scale connectivity collapses and nutrient delivery fails — the same phase transition that physicists use to model connectivity in random graphs and porous media. Adaptive therapy (cycling drug doses to exploit competitive suppression) may be deliberately tuned to keep the network near — but just below — the percolation threshold, maximising tumor fragmentation while avoiding full drug-resistance selection. Neither oncologists nor physicists have yet jointly designed dosing schedules using percolation-threshold mathematics as the objective function.

⚙️ The Mathematical Bridge

This bridge connects Oncology and Statistical Physics through shared mathematical structure. Status: Proposed connection.

↔️ Translation Table

Domain A Term Domain B Term Note
bond percolation probabilityvessel patency under treatment pressureFraction of edges (vessel segments) still functional
giant connected componentviable tumour vascular coreThe dominant connected region supplying nutrients
percolation threshold p_cminimum viable vascular densityCritical fraction below which nutrient supply collapses
cluster size distributionisolated tumour micro-regionsDisconnected fragments starved of blood supply
renormalisation groupadaptive dosing schedule optimisationMulti-scale description of how local drug actions aggregate to global effects

🗺️ Why Hasn't This Been Unified?

Oncology journals rarely cite statistical-physics literature, and vice versa. Clinical trials measure tumour volume or survival endpoints, not topological graph metrics. The toolchains (MATLAB/Python network libraries vs. medical imaging suites) are largely siloed, and grant bodies do not routinely fund physics-oncology hybrids.

🌱 Cross-Pollination Opportunities

🧪 Crosscheck — Prove This Bridge

Runnable experiment protocols promoted from this bridge. USDR maps what connects; Crosscheck proves it.

Synthetic-lattice giant-component fraction as a percolation-derived treatment-response metric

READY desktop

On an L=32 square site-percolation lattice, mean giant-component fraction S(p) (largest cluster / L^2) and top-bottom spanning fraction are measurable at occupancies p in {0.40, 0.50, 0.59, 0.70} with 8 trials per p. ...

Protocol p-b-percolation-oncology-gcc

Crosscheck manifesto · Generate more drafts: python scripts/generate_crosscheck.py --bridge b-percolation-oncology --write

❓ Open Questions

📚 References