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The Rise of Personalized Medicine

January 05, 2016

The Rise of Personalized Medicine


A century-old math formula has an infinite number of monkeys pecking away at an infinite number of typewriters. Eventually, one of those monkeys will type Shakespeare’s Hamlet, French mathematician Émile Borel theorized in 1913. Farfetched as that may seem, Borel’s theorem is mathematically sound, even though it will likely take an eternity to actually come true.1

A century later not much has changed. Borel’s metaphor about processing an endless stream of data aptly describes the dilemma facing bioresearchers today. There is just too much data to process with existing technologies. One estimate of genomics information, for instance, claims that over the next decade, personalized genetic data will total up to 40 exabytes a year. To give you some idea of how immense that is, one exabyte is a million times more information than your average home computer stores. Now add into the mix even more information from a variety of sources thanks to the rise in translational—or personalized medicine—and you have the makings of a proverbial Gordian knot. Researchers from big pharmaceuticals to academic labs are simply drowning in their own data. The truly frustrating thing about all this is that so many potential new medical discoveries and therapies lay buried in those databases with no easy or cost-effective access.2 Until now.

No More Monkeying Around With Big Data

Enter the PerkinElmer Signals for Translational platform. The cloud-based Software-as-a-Service (SaaS) system offers a complete precision medicine workflow that integrates research and clinical data to allow scientists to easily search and retrieve aggregated information from across any number of biological and environmental sources. As a self-service system, it allows researchers to create their own specific queries open-ended and automatically gathers disparate data to help answer even open-ended questions.

“The PerkinElmer Signals for Translational system presents the data in a way a regular scientist will understand,” Daniel Weaver, PerkinElmer’s senior product manager for translational medicine informatics, says. “It is organized around concepts a scientist gets, around the subjects of clinical trials, patient visits, samples collected, etc.”

A New-Age Solution

Unlike traditional systems, the PerkinElmer Signals offering is neither relational nor semantic in its database orientation. Instead, it offers a point in space between the two, Weaver says, allowing scientists to make queries that require only lightweight upfront structuring.  In addition, the PerkinElmer Signals system provides an intuitive web interface that provides researchers with the ability to locate clinical subjects and samples quickly along with any number of related experimental data, including public domain sources like GEO and tranSMART. That data can then be visualized using special TIBCO Spotfire® templates or other third-party visualization platforms to help speed research outcomes that will hopefully lead to new discoveries and clinical treatments faster and maybe even uncover a scientific cause for Hamlet’s bipolar disorder.3


  1. Émile Borel, "La mécanique Statistique et L'rréversibilité," Journal de Physique. 5e série, vol. 3 (1913), pp.189-196.
  2. Robert Gebelhoff, "Sequencing the Genome Creates So Much Data We Don't Know What To Do With It", The Washington Post, July 7, 2015.
  3. Character Analysis of Hamlet: Psychological Disorders, Transmedial Shakespeare: Studying Shakespeare Beyond His Text, October 8, 2012.

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