Quantum Oncology - Four Ways Physics Is Coming for Cancer

Diamond sensors and gold nanoparticles destroying tumors sound like science fiction, but they are real tools being tested in labs today. While they take time to reach local hospitals, they are opening the door to a future where we finally know exactly how to save patients like Sarah.

Feature · Part 2 of 2 · 4 min read

by Dr Vishala Bodetti,  AI Medical Lead

 

Sarah is still in that room, holding her sixty per cent. Here is what five laboratories are building so the next woman in that chair gets an answer instead of a coin flip.

1	Can we detect cancer before it becomes visible?

By the time a tumour shows up on a scan, it's already about a billion cells and years in the making. That's because today's scans, like MRI, are weak listeners — they only pick up a tiny sliver of the signal they're searching for. A new technique fixes this by making the signal louder instead. Doctors cool a natural body fuel to near absolute zero, then inject it. For a few minutes, it lights up thousands of times brighter than normal — bright enough to show how a tumour is feeding, not just where it sits. That means seeing cancer at work before it ever grows large enough to see .

 

Why it matters — Catch it at Stage 0 and a catastrophe becomes an outpatient afternoon — and a doctor can see if a drug is working in ten days, not ninety. Reality check — Research protocols at a handful of centres. The signal decays within minutes. Nowhere in routine care.

 

2	Can we listen to the earliest cellular signals?

 

 

Chemotherapy affects the whole body and hopes it hurts the tumour more than it hurts the patient. A better idea: something that does nothing at all - until it reaches a cancer cell. Scientists shape tiny gold particles that react only to one specific kind of light, one that passes through skin and tissue safely. They attach the particles to a molecule that sticks only to cancer cells. Once injected, the particles wait quietly. Shine the light, and only the particles near the tumour heat up -destroying it while leaving healthy tissue untouched

Why it matters — Medicine spent two centuries learning to look at cells. This is the first serious attempt to listen to one. Reality check — Cell cultures, not patients. Deploying this in a living human without an immune reaction is unsolved.

 

3	Can we tell cancer cells to self-destruct?

 

   

Chemotherapy affects the whole body and hopes it hurts the tumour more than it hurts the patient. A better idea: something that does nothing at all — until it reaches a cancer cell. Scientists shape tiny gold particles that react only to one specific kind of light, one that passes through skin and tissue safely. They attach the particles to a molecule that sticks only to cancer cells. Once injected, the particles wait quietly. Shine the light, and only the particles near the tumour heat up - destroying it while leaving healthy tissue untouched

 

Why it matters- selectivity in its purest form — especially where surgery is most dangerous. Reality check — Early human trials, not standard care. Light penetrates centimetres, not bodies.

 

4	Can nanoparticles become doctors?

   

 

Treating cancer today is a relay race: one team finds it, another names it, another removes it, another treats what's left - and every handoff wastes time the tumour uses to keep changing. Scientists are now building tiny particles that can do several of these jobs at once. Made small enough, these particles glow in a specific colour doctors can track like a beacon. Attach a piece that sticks only to cancer cells, plus a drug that only releases inside a tumour, and the particle becomes a single tool that finds the cancer, marks it, and delivers treatment directly to it. 

 

Why it matters — Diagnosis and treatment collapse into a single act, and the particle reports back. Reality check — Preclinical. Decades of nanoparticle work have produced spectacular mouse data and disappointing human trials.

 

THE HONEST TIMELINE

Nobody funds this because it works. They fund it because it might, and being late would be unforgivable. IBM put a quantum computer on the Cleveland Clinic campus. Mayo works with Heriot-Watt on sensors — instruments, not computers, the likeliest thing to touch a patient this decade.

Quantum computers will not cure cancer; they are modelling tools, and curing cancer is biology, economics, and access, not arithmetic alone. In routine care today: nothing. In early research: a thin real layer. In the lab: everything else, separated from patients by a graveyard of beautiful mouse studies.

BACK TO SARAH

Picture where this ends. A woman sits three minutes in a scanner that maps what her tissue is doing, not just where it is. Her biopsy carries a simulation of how her exact protein answers to fourteen candidate drugs. Three look promising; two are wrong in a way no classical model had noticed. Ten days in, not ninety, the scan shows her tumour's appetite collapsing.

The oncologist is still in the room — still making the call. She has stopped being a gambler reading odds. She has become an engineer reading a blueprint.

None of it arrives in time for Sarah. She will take the sixty per cent drug and find out which side of it she is on the way every patient always has — by living through it. But the uncertainty in that room is not a permanent feature of the universe. It is a computational limit, and computational limits fall. Quantum oncology will not abolish cancer. What it offers is narrower, and worth more: it turns the lights on in a dark room. It takes away the disease's cruellest weapon, which was never the tumour. It was the not-knowing.

This won't beat cancer. But it could finally answer the one question that's mattered most: will this work on me? To the woman in that chair, that's everything. 

Missed Part One?

The Most Expensive Guess in Medicine — why cancer is a computational problem, not a biological mystery.

Quantum Oncology - The Most Expensive Guess in Medicine: Why Cancer Is a computational problem, not a biological mystery.

 

We can read a tumor's entire genome in an afternoon. We still cannot tell the woman sitting in front of us whether her treatment will work. The reason is stranger than you think.

Feature · Part 1 of 2 · 4 min read

by Dr Vishala Bodetti,  AI Medical Lead

 

Sarah is forty-two. For twenty years, her job has been making sure buildings don't fall down. She never guesses — every beam she designs is checked and double-checked before it's trusted. She doesn't hope a floor will hold. She knows it will

Then she found the lump. Stage III triple-negative breast cancer. Her oncologist offers a plan: Regimen A works in about sixty per cent of women with her tumour profile. If three cycles do nothing, they try Regimen B.

Sarah asks the only question that matters. Will it work on me? The honest answer-the one her doctor is too kind to say outright - is that nobody in the building knows.

Her physician is excellent. Oncology spent a century earning that sixty per cent. But sixty per cent is a fact about a crowd, and Sarah is not a crowd. She is one woman with one tumour, either in the sixty or the forty — and the only way to find out is to spend three months living the answer.

No engineer would open a bridge to traffic without knowing if it holds. In oncology, we start treatment without knowing if it will — and wait three months to find out

This is not negligence. It is the frontier. We have sequencing, imaging, and a diagnostics industry worth billions, and we are still blind to the one thing Sarah needs: how her mutations will meet this molecule. We treat people with averages because averages are the sharpest instrument in the drawer. The question is why—and the answer has almost nothing to do with biology.

THE PROBLEM IS NOT MEDICINE. IT IS ARITHMETIC.

A tumor is not a lump. It is an ecosystem—billions of cells, each carrying its own edits to the code, competing like species on an island. Somewhere in that population sits a cell already immune to the drug Sarah hasn't been given yet.

Inside a single cell, tens of thousands of proteins fold and bind and signal every instant. Most mutations mean nothing. A few decide everything. To model one medium-sized protein exhaustively would take a computer built from more atoms than exist in the observable universe.

And here is the strange part: that cascade is not chemistry. Chemistry is the summary we write afterward. Underneath, it is quantum mechanics—electrons in superposition, particles correlated in ways with no equivalent in the visible world. Every classical computer that simulates a molecule translates a quantum system into ordinary arithmetic, and something is always lost. Our machines aren't too slow. They are the wrong kind of thing.

“Nature isn't classical, dammit — and if you want to make a simulation of nature, you'd better make it quantum mechanical.” — Richard Feynman, 1981. It took the world forty years to admit he was right.

BUILD A MACHINE OUT OF THE WEIRDNESS

A coin on a table is heads or tails. Committed. That is an ordinary bit — every computer you've touched is built from billions of them.

Now spin the coin. While it spins, it is not secretly heads, waiting to be seen. It is genuinely both — a blend with no equivalent in anything you can hold. That is a qubit. Entangle two of them, and they stop being separate objects; they become one system with a shared description. That description doubles with every qubit added: three hundred of them describe more configurations than there are atoms in the known universe, in a device that fits on a desk.

That is why simulating a molecule on an ordinary computer is hopeless — you are trying to write that number down by hand. And it is why a quantum machine changes the game: it does not write the number down. It builds a small, controllable system with the same kind of state space as the molecule, and watches what it does.

A quantum computer does not calculate the molecule. It agrees, briefly, to be the molecule — and then you ask it how it feels.

It will not read an MRI better. It will not fix a billing system. It is a specialized instrument for exactly one class of problem: things whose difficulty comes from being quantum in the first place. Which is, inconveniently, what every molecule in Sarah's body happens to be.

BRINGING TOMORROW'S SCIENCE TO TODAY'S PATIENTS

What stands between Sarah and a real answer is not a missing molecule. It is arithmetic — the gap between how complicated her tumour is and how much complication our instruments can hold. Mortality is a fact. Arithmetic is an engineering problem. Engineering problems get smaller.

Right now, in five laboratories, the answer is taking shape: a scanner that watches a tumour eat instead of measuring how big it is; a sensor built from a flaw in a diamond, listening to a single cell; gold that sits inert inside a tumour until light tells it to cook it; particles that diagnose and treat in the same motion; a machine that could collapse a decade of drug discovery into an afternoon.

Not one is a cure. Every one is real, funded, and further along than you'd guess — though not, for the most part, close enough for Sarah. 

That is Part Two Five Ways Physics Is Coming for Cancer (to be published on 22nd Sep. Bookmark this page and return)