I’m planning to launch a citizen science project, , in 2017 which has two distinct ways anyone can help combat antibiotic resistance. I’ve revamped and relaunched what will ultimately become the – please have a look.

The first strand is closer to the light of day and will help the international Tuberculosis consortium, . This global group of researchers, of which I am a part, will be collecting over 100,000 samples from patients with TB. Each sample will be tested to see which antibiotics are effective as well as having the genome of its M.tuberculosis bacterium sequenced. In practice, because each sample is measured at least three different times, that means looking at 300,000 96-well plates. Step forward ! This type of large-scale image classification is exactly the sort of thing Zooniverse Citizen Science projects excel at. I hope to launch this project in early 2017.

The second citizen science project is more complex and I have recently applied for funding. As described in my Research, I am developing methods that can predict whether novel or rarely-observed mutations cause resistance to an antibiotic (or not). These require a lot of computer resource and the idea is to build a volunteer computing project, like [climate prediction.net](http://climate prediction.net), using the , so that volunteers can download a program onto their laptop or desktop. When they’re not using their computer, the program will retrieve part of a problem and run the simulations on their machine before returning the results over the internet. These type of project is more complicated and requires more infrastructure to be setup, but with some luck, I’d hope to have a soft launch late in 2017.