Patient behavior tracking startup nabs $1.7 million

By: Chris Gullo | Oct 18, 2011        

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Ginger.ioSocial behavior analysis startup recently announced $1.7 million in its first round of funding. The start-up, which was born out of MIT’s Media Lab, is developing software for mobile devices that aims to give pharma companies and providers detailed data on patient behavior to more effectively target new drugs and therapies.

The round was led by Silicon Valley-based True Ventures and also included Kapor Capital, Romulus Capital, and angel investors Bill Warner, Walt Winshall, James Joaquin, and Ty Curry.

A report by Gregory Huang at Xconomy offers some good insight into the company’s business model and future potential. isn’t developing a consumer health and wellness app — instead, it’s a BtoB play:

“A mobile phone can provide crucial information about its owner’s activity level, location, and communication patterns—all in real time, more or less (assuming the person opts in),” Huang writes. “That information could be valuable to drug makers and hospitals looking to track the results of clinical trials, market medications to certain types of patients, or design new therapies for things like diabetes, obesity, or brain disorders.”

Insights gathered from noticing how a target population’s behavior varies due to a new drug or therapy could prove very valuable to companies. Ginger is currently working with healthcare providers and two of the “top five” pharma companies. The startup’s technology has also been used to study inflammatory bowel disease by Cincinnati Children’s Hospital. has a similar focus to other MIT Media Lab-born companies like Affectiva, which aims to quantifiably analyze emotions to improve consumer experiences. Affectiva offers Affdex, an emotion recognition software, and the Q Sensor, a wrist sensor which measures electrodermal activity (EDA), motion and temperature to quantify emotion.The Affdex software uses a computer’s webcam to read emotional states via non-verbal responses such as facial expressions.

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For more, read the Xconomy article here.

  • Evan Freedman

    Finally! A truly passive form of data collection that is still just as insightful (if not more so) than the tedious active data entry that we’ve had to settle with.

    I am going to sound like a curmudgeon in saying this, but even the smallest of nuisances will kill a product. The nuisance factor must be close to zero if you want your users to sustain and follow-through with the product continuously. You’d be surprised how even one extra button to push or one more thing to type in will cause users to simply give up after just a few weeks, even if they started with the best of intentions and probably a good deal of excitement as well. It’s easy as an outsider to dismiss those little tiny nuisances as trivial, but when you have to deal with them constantly day after day after day, they eventually become that which pushes you over the edge and exclaim, “enough already!” 

    So kudos to You have managed to make one of the first passive sensors that not only still manages to offer high quality data, but goes about collecting and evaluating this data in amazingly creative ways. Take for instance how could track a potential onset of depression using  a) accelerometers to see how often you move about and whether you usually stay confined to one room or even leave your home that often, and b) observing your call history to see how often you are placing calls and who you are calling, looking for sudden downswings in those trends. Now how does that compare to apps that prompt you to pick the most appropriate smiley or frowny face everyday to evaluate and track your mood? I mean really, come on.