When you're asleep and your phone's crunching numbers, what data is Project DRUGS actually looking for? Here's the biology behind DreamLab...

Last time we talked about DreamLab – the app that turns your smartphone into a cancer-fighting supercomputer – we were unravelling the tech that makes the number crunching tick.

Today? We’re taking a step back, exploring the biology behind the whole project, and discovering exactly what it is you and your phone are working on every night. Ready to school up on your science? It’s time to step into the lab and find out all about Project DRUGS…

Biology 101: Genes, drugs, and cancer

So what is Project DRUGS (Drug Repositioning Using Grids of Smartphones) actually doing? And what are the team at Imperial College London looking for? To understand that, we need to understand how cancer affects us – and is affected by drugs – at a genetic level.

The important bit is this: when you take cancer samples from two different parts of the body, and from different people, their visible differences belie some pretty strong similarities at the genetic level. That’s because different types of tumours may be the result of the same genetic mutations – they might have the same underlying building blocks. And because of that, there’s a good chance those tumours might respond in the same way to the same drugs.

The aim of Project DRUGS is to trial as many drug combinations as possible on the genetic mutations that we know to be involved with cancer.

To do that, the Imperial College London team are testing these drugs against almost a million cancer samples from around the world, which translates to over 30,000 different cancerous mutations. The amazing thing here is that the data we get will help group patients in a smarter way than we do currently.

Whereas right now we tend to think in terms of the kind of cancer someone has (lung, liver, etc.), and how far it’s progressed (stages 1-4), Project DRUGS is looking to bring us to a point where we can group people by the properties of their genes – and how those genes form or interact with cancerous cells.

The ultimate goal? To learn which combinations of drugs – whether they’re traditionally aimed at cancer or not – have positive effects, and ‘reposition’ them, rather than creating brand new ones from scratch.

As an example, one compound being tested is Sildenafil Citrate, typically used to treat cardiovascular problems. What the team in the lab are looking for here is whether that particular drug might decrease cancer-favouring properties at a molecular level, depending on your DNA.

The more data we collect, the more precise the results, to the point where we might be able to tailor drug combinations to patients based on their exact DNA. Which brings us neatly on to what the future may look like…

The future of crowd-sourced supercomputing

“We’re currently generating huge volumes of health data around the world every day,” says Project DRUGS lead, Dr Kirill Veselkov. “But just a fraction of this is being put to use.

“By harnessing the processing power of thousands of smartphones, we can tap into this invaluable resource and look for clues in the datasets. Ultimately, this could help us to make better use of existing drugs and find more effective combinations of drugs tailored to patients, thereby improving treatments.”

That’s the now. But what about the future? It’s all about refinement, and attempting to hone in on which combinations and doses work best for patients.

The good news is, the more successful this approach is, the more widespread it’ll become. “Every cancer patient in the UK could have their DNA tested within the next decade,” says Dr Veselkov, which he believes could help us enter a new era of “using patients’ own data for more personalised therapy selection.”

In other words? Tomorrow’s cancer treatments will be a lot more specific to you, but only if we keep crunching those numbers! To do your part, download the DreamLab app here and sleep like a hero!

Find out more… What’s the DreamLab app doing while you’re asleep? Here’s how the number crunching works.