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Sponsors of global trials face many challenges. One of the most sensitive concerns is appropriate collection and handling of clinical data. Data managers face variation in data collection methods and clinical trial practices among the countries or regions participating in a global trial. PROMETRIKA’s successful approach to data integrity includes strong global oversight and advanced technology and processes.
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The development of ‘artificial intelligence’(AI)-driven tools for data management has accelerated in the past few years. The promise of these systems is to provide a more intuitive experience for data management and sponsor teams, making it easier to track trends, spot anomalies, and generate near-real time data reports. These features, combined with AI’s ability to learn from data, make these tools a modern essential for improving data quality and accelerating clinical trials.
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Members of PROMETRIKA’s Data Management (DM) team attended the recent Society for Clinical Data Management (SCDM) conference, held in Boston this year. This annual conference brings together the global data management community for discussions of the latest developments and challenges faced by DM professionals.
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Over the past 15 – 20 years, projected peak sales and return on investment (ROI) of new drugs has been shrinking (source: Statista and Deloitte Centre for Health Solutions). To offset this, pharmaceutical companies are pushing to get more drugs to market and multiple indications for each agent.
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Decentralized clinical trials (DCT) seems to have burst on to the scene in just the last few years, so it is easy to get swept up into how we can best implement them into our clinical trials. However, it is worth examining the past of this supposedly “new” method of conducting clinical trials.
THOUGHT LEADERSHIP
