\nHere\u2019s how GSK is modernizing the way it approaches clinical data management\u2014an undertaking that\u2019s involved replacing multiple EDCs and complex processes\u2014and how it made progress in half the time expected, accelerating delivery in 18 months due to an agile methodology.\n<\/p>\n
Putting data at the center<\/strong><\/h2>\n\nHistorically, explained Mayank, the industry had overlooked clinical data for years, preferring to focus on medical writing, stats, and submissions systems. But now, as companies embrace hybrid digital trial models and struggle with a proliferation of digital data sources, effective data management has become a key driver of trial success.\n<\/p>\n
\nThat\u2019s why GSK decided to implement Veeva CDB<\/a>, a clinical database that speeds data cleaning and standardization to allow its data to be managed, reported, and analyzed. Not only will this make clinical research more agile, but it will also enable more advanced tools, such as NLP and visualizations, to be applied, while making artificial intelligence (AI) and machine learning initiatives more successful in the future, Mayank said.\n<\/p>\nIdentifying GSK\u2019s \u201cwhy\u201d<\/strong><\/h2>\n\nAs the company began its modernization project, it started by clearly articulating its \u201cwhy\u201d for change. As Mayank noted, GSK\u2019s three main goals were to:<\/p>\n
\n- \nSimplify the operating model.<\/strong> Before adopting Veeva, GSK was using at least four different types of EDCs within its clinical data ecosystem, and each of them had been customized to such an extent that the result resembled a jigsaw puzzle. It was important to reduce the complexity that had built up over the years.\n<\/li>\n
- \nEmploy technology enablers.<\/strong> As Mayank explained, the industry interpreted technology very narrowly, as though changing the EDC platform was enough. However, there are many different technology enablers to help clinical teams do their jobs better, with significant advances in areas such as AI and machine learning to leverage.\n<\/li>\n
- \nAccelerate delivery.<\/strong> Mayank emphasized the importance of speeding up the delivery of life-saving treatments with a sobering statistic: for certain diseases, two afflicted patients die every minute. \u201cOur patients are waiting,\u201d he stressed. \u201cJust imagine the number of lives being lost if the industry continues to do clinical study locks in 21 weeks, instead of four or even two weeks.\u201d\n<\/li>\n<\/ol>\n
![\"\"](\"\/eu\/wp-content\/uploads\/2021\/11\/GSK-Puts-Data-First-in-New-Clinical-Agility-Benchmarks-1.png\")
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Aligning on a single CDM platform<\/strong><\/h2>\n\nTo escape the complexity of its jigsaw puzzle of EDCs, GSK adopted Veeva Clinical Data<\/a> as its single, core CDM platform. However, this time, its data specialists avoided customization and, instead, chose a platform based on its own inherent capabilities. \u201cOnce you adopt a new platform, you shouldn\u2019t spend the next 10 years recreating the same complexity that you had with the previous one,\u201d Mayank said.\n<\/p>\n\nMoving to a single platform will ultimately help GSK improve data review. Over the years, the company had created additional complexity and slowed its processes by collecting and reviewing every single data point from a trial. It treated all data as critical, when in fact, \u201call data is not equal,\u201d said Mayank, explaining that value-driven data cleaning is now a key strategy.\n<\/p>\n
Identifying GSK\u2019s \u201cwhy\u201d<\/strong><\/h2>\n\nAs the company began its modernization project, it started by clearly articulating its \u201cwhy\u201d for change. As Mayank noted, GSK\u2019s three main goals were to:<\/p>\n
\n- \nSimplify the operating model.<\/strong> Before adopting Veeva, GSK was using at least four different types of EDCs within its clinical data ecosystem, and each of them had been customized to such an extent that the result resembled a jigsaw puzzle. It was important to reduce the complexity that had built up over the years.\n<\/li>\n
- \nEmploy technology enablers.<\/strong> As Mayank explained, the industry interpreted technology very narrowly, as though changing the EDC platform was enough. However, there are many different technology enablers to help clinical teams do their jobs better, with significant advances in areas such as AI and machine learning to leverage.\n<\/li>\n
- \nAccelerate delivery.<\/strong> Mayank emphasized the importance of speeding up the delivery of life-saving treatments with a sobering statistic: for certain diseases, two afflicted patients die every minute. \u201cOur patients are waiting,\u201d he stressed. \u201cJust imagine the number of lives being lost if the industry continues to do clinical study locks in 21 weeks, instead of four or even two weeks.\u201d\n<\/li>\n<\/ol>\n
<\/p>\n
Aligning on a single CDM platform<\/strong><\/h2>\n\nTo escape the complexity of its jigsaw puzzle of EDCs, GSK adopted Veeva Clinical Data<\/a> as its single, core CDM platform. However, this time, its data specialists avoided customization and, instead, chose a platform based on its own inherent capabilities. \u201cOnce you adopt a new platform, you shouldn\u2019t spend the next 10 years recreating the same complexity that you had with the previous one,\u201d Mayank said.\n<\/p>\n\nMoving to a single platform will ultimately help GSK improve data review. Over the years, the company had created additional complexity and slowed its processes by collecting and reviewing every single data point from a trial. It treated all data as critical, when in fact, \u201call data is not equal,\u201d said Mayank, explaining that value-driven data cleaning is now a key strategy.\n<\/p>\n
<\/p>\n
Aligning on a single CDM platform<\/strong><\/h2>\n\nTo escape the complexity of its jigsaw puzzle of EDCs, GSK adopted Veeva Clinical Data<\/a> as its single, core CDM platform. However, this time, its data specialists avoided customization and, instead, chose a platform based on its own inherent capabilities. \u201cOnce you adopt a new platform, you shouldn\u2019t spend the next 10 years recreating the same complexity that you had with the previous one,\u201d Mayank said.\n<\/p>\n\nMoving to a single platform will ultimately help GSK improve data review. Over the years, the company had created additional complexity and slowed its processes by collecting and reviewing every single data point from a trial. It treated all data as critical, when in fact, \u201call data is not equal,\u201d said Mayank, explaining that value-driven data cleaning is now a key strategy.\n<\/p>\n
\nMoving to a single platform will ultimately help GSK improve data review. Over the years, the company had created additional complexity and slowed its processes by collecting and reviewing every single data point from a trial. It treated all data as critical, when in fact, \u201call data is not equal,\u201d said Mayank, explaining that value-driven data cleaning is now a key strategy.\n<\/p>\n
![\"\"](\"\/eu\/wp-content\/uploads\/2021\/11\/employ-technology-enablers-on-a-core-platform-1.png\")
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