MAY - 202119TECH OUTLOOKHow Can Artificial Intelligence Improve Clinical Trials?By Yuri Martina, Head of Development at Grünenthal and Jorine Putter, Head of Advanced Analytics at GrünenthalNew digital technologies are transforming R&D in the pharmaceutical industry. They are empowering researchers to create better medicines faster and at a lower cost. We asked two of our experts ­ Yuri Martina, Head of Clinical Operations, and Jorine Putter, Head of Programming, ­ to explain how machine learning and predictive analytics can help us enhance clinical trials and be more patient-centric. How are new digital technologies being used in clinical trials?Yuri Martina: Machine learning and predictive analytics are able to make sense of large amounts of data much more quickly than a human ever could. This puts us in a stronger position to make accurate predictions about a range of issues that shape the success of a clinical trial ­ from deciding if, when and how a drug will work best, through to choosing which patients to include and predicting dropout rates, selecting a site, identifying and connecting the right patients to the right clinical trials, or defining the sample size and dosage.What are the benefits?Yuri Martina: It's ultimately about increasing R&D productivity and becoming more patient-centric. Currently, only around 10 per cent of drugs that are tested in human subjects receive FDA approval ­ and the research process can be extremely lengthy and cost millions of dollars. Many drugs fail because of inaccurate predictions which results in incorrect planning clinical developments and clinical trials. That's why machine learning and predictive analytics are so exciting for CXO INSIGHTSJorine Putter
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