Camila Londono is currently an intern at CCRM, taking a break from working on her PhD at the Institute of Biomaterials and Biomedical Engineering at the University of Toronto under the supervision of Dr. Alison McGuigan. Her research focuses on understanding what governs the coordination of motion in groups of cells. She holds a Bachelor of Applied Science in Engineering Science from the University of Toronto.
Knowledge grows at an astonishing pace. It is now impossible for any single person to know everything there is to know. And what we don’t know, well, that’s what the Internet is for, right?
Medical crowdsourcing recently saved a teenager’s life when the boy’s doctor posted a picture, on a medical social network, of a weird-looking branched thing the teen had coughed up. In total, 231 doctors from the U.S. and the UK posted their diagnoses, until a cardiologist nailed down his disease: Fontan’s associated plastic bronchitis, which is fatal if left untreated.
This is not the only example in which informational crowdsourcing has been used by the medical sciences. More and more companies have been harnessing this power in recent years. Foldit is an online game that has greatly advanced what we know about protein folding. Apple recently released ResearchKit, which combines DNA collection with researcher-created apps for monitoring clinical trials.
23andMe, the famed genomics company that, with a simple cheek swab, can tell you about your genetic predisposition for over 100 conditions (as well as your ancestry), allows its customers to sign up for a multitude of research trials. The company is combining the massive amounts of genetic data it collects with individual surveys about personal characteristics, from people all over the world, to unveil new clues to a variety of conditions and disorders, including Parkinson’s. 23andMe has already discovered genetic variants that affect hair curliness or make people susceptible to sneezing when they look at bright light.
One of the latest crowdsourcing efforts reported a win in February 2015, when 212 non-scientist volunteers managed to not only parse nearly 800 documents with over 10,000 annotations in only four weeks, but they did so at a level of accuracy that far surpassed that of a single PhD and nearly matched a team of PhD researchers. They are now moving forward to more literature to try and identify links between supposedly disparate research topics using symptoms, treatments, and readouts to identify potential avenues of investigation for rare genetic disorders (NGLY1 is their current target, but they eventually hope to create pages for all diseases).
You can learn more about this effort in the video below, a TEDx talk by Dr. Andrew Su, who works on bioinformatics at Scripps Research Institute in San Diego, California, and then sign up to help on their website.
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