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Real-world Data Can Make Up for Clinical Trial Weaknesses, Says Viraj Narayanan

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Real-world data can help resolve some challenges commonly faced in clinical trails, said Viraj Narayanan, MBA, vice president of Life Sciences at COTA Healthcare.

Real-world data can help resolve some challenges commonly faced in clinical trails, said Viraj Narayanan, MBA, vice president of Life Sciences at COTA Healthcare.

Transcript:

How can the use of real-world data help provide additional insights into patients that clinical trials miss?

So from a pre approval process, the idea of using an external comparitor for a single arm trial is really a fundamental change. The way we think about this is it's a little bit of an ethical issue. Would you want a loved one to be on a placebo arm of a cancer trial? I think most people would say no. So why can't we start using real world data as that placebo group to compare the new investigational agent that the sponsor is considering? If that really becomes a norm, we're going to see a complete rewiring of the traditional clinical trial process from a pre-approval standpoint. From a post-approval standpoint, as oncology trials have become more and more narrow, in getting approval on this narrow cohort, this is where real-world data has a really exciting role to play. We know inherently that a narrow population is not all patients. It’s just not. So from a post-approval process where real-world data can have a big impact is looking at patients that are really representative of real patients and seeing how they do, relative to the clinical trial. Are they getting the same clinical response as patients in the clinical trial? Are they getting the same safety response as patients in the clinical trial? Are there super responders, are there under responders? From a post-approval process, it's really looking at a more representative data set to see how patients are doing.

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