The National Institutes of Health (NIH) is working on a solution to a problem faced by a growing number of Americans as the population ages and relies more on prescription drugs: “What is this pill?” Much in the way a Google image search looks for similar images in Google’s vast caches, the NIH’s National Library of Medicine (NLM) desires a tool to match users’ smart phone photos of mystery pills with hi-res images in the NLM’s existing RxIMAGE database of over 3,000 prescription pills and capsules. If successful, such a tool could not only prevent overdoses, but cut down on waste when unidentified drugs are discarded by those who conclude it’s better to be safe than sorry.
Generally, pills have few identifying marks that can serve as a reminder once they are out of the packaging. Many people who take multiple pills set up doses a day or even days in advance using special organizers, but pills can inadvertently become jumbled or dropped, creating confusion and uncertainty. The NIH describes the problem in a Sources Sought notice online:
After this initial pilot RFI (Request for Information), the NIH is planning a Pill Image Recognition Challenge for professionals, students and others who could take a “photograph an unknown prescription pill, possibly under poor lighting conditions, from an angle, or at low resolution,” and find matches in the RxIMAGE database. Documents accompanying the notice provide the following illustration as an example:
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(a) User takes photo of front of unknown prescription pill.
(b) Smart phone app returns one or more possible matches – in this case the images of the fronts and backs of four pills.
The NIH, which plans to make the end product freely available to the public as well as health care providers, would even like the software to take generics into account as well:
Although details are still forthcoming, a Challenge prize will be awarded for the best solution. However, based on the schedule provided in the notice it appears that the competition will not take place until the latter half of 2015 at the earliest.
