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Off to the data mines
September 2013
by Jeffrey Bouley  |  Email the author


When Ariana Pharma announced this summer that the WIN Consortium had chosen it to develop new personalized cancer medicine software through the consortium's WINTHER trial, it wasn't just a validation of Paris-based Ariana's data management skills in life science, notes Dr. David Morley, Ariana's vice president of computational technology—it was also a sign of how much data mining has shifted from its early beginnings in drug discovery to something much more oriented toward clinical trials.  
"It's a very exciting time for data mining, and we've seen a real move from retrospective use of it to a more proactive role," Morley tells DDNews. "In the roughly 10 years Ariana has been bringing data mining to life sciences—after years of use in other industries and areas like marketing, customer analysis and fraud detection—we've seen these techniques move from a very niche mode to being much more mainstream."  
Although Ariana started off marketing data mining for drug discovery primarily—and still does market for that purpose—Morley says that his company's Knowledge Extraction & Management (KEM) technology is overwhelmingly being sought for clinical trial applications now, with significant action in biomarker identification and analysis as well. And with the growth of personalized medicine efforts, the biomarker area is, to some degree, merging with the clinical trial applications for data mining, he adds.
"The WINTHER trial is an example of how data mining has moved from the chemistry side primarily to a role of facilitating adaptive trials and identifying the best responders among patients to truly tailor therapies for them," Morley says. "If you look from the 30,000-foot view, roughly a third of the time when a drug is prescribed, it works, another third of the time it doesn't work and even worse, a third of the time, you have huge adverse effects. Data mining enhances your percentage of success."  
The WINTHER trial is being conducted by Worldwide Innovative Networking in personalized cancer medicine, otherwise known as the WIN Consortium, and is reportedly the first clinical trial offering 100 percent of recruited cancer patients a therapy choice guided by individual patient biology, and it is said to represent "a breakthrough in current oncology practice which at best offers biology-guided therapy to 30 percent of patients. This is because most cancers are diagnosed at a late stage and for the vast majority of patients the therapeutic choice is based on standard protocols." The WINTHER trial promises to offer personalized medicine based on individual DNA, RNA and microRNA profiles, with trial results expected in 2015.
In spring, Ariana's KEM technology was secured for the French government's Innovative Models Initiative, one of the largest national collaborative projects in health in France, which will focus the development of new drugs and personalized medicine approaches in cancer by creating an industrial-scale pipeline that characterizes, standardizes and makes use of predictive cancer models.  
"Data mining is something that's seeing particular use and offers particular promise in the area of oncology," Morley says.  
The burgeoning data mining market in life sciences may be one reason that Research and Markets recently has been promoting a three-year-old publication titled "Pharmaceutical Data Mining," noting,  "In the era of post-genomic drug development, extracting and applying knowledge from chemical, biological and clinical data is one of the greatest challenges facing the pharmaceutical industry."  
Rithme, which is based in France like Ariana and deals with similar customers, noted that data mining "can successfully contribute in the explanation or prediction of complex phenomenon in healthcare and pharmaceutical industries," with some of the key examples being dose-response analysis, cohort analysis, longitudinal and survival analysis, benefit-risk analysis and predictive modeling.  
The need to rely more on data mining, particularly in the area of clinical trials, is one that has been recognized for several years, with the Institute of Medicine noting in a 2010 report that many consider randomized clinical trials, for so long the gold standard in pharmaceutical research, "to be unsustainable as an approach to addressing the large number of research questions that need to be answered because of the time and expense involved." Data mining can help by evaluating trial study feasibility to begin with, refining the process of patient enrollment and even assisting in post-marketing pharmacovigilance.  
In the end, one of the biggest reasons Ariana, Rithme and others will continue to see a boom in data mining interest, though, is money. After all, as the report "How Big Data Can Revolutionize Pharmaceutical R&D" by the McKinsey Global Institute notes, making better use of so-called "big data" could have a $100-billion impact on the healthcare industry just in the United States, resulting from "optimizing innovation, improving the efficiency of research and clinical trials and building new tools for physicians, consumers, insurers and regulators to meet the promise of more individualized approaches."

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