Google Cloud exec: Real-world data could eliminate the need for placebos in clinical trials

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Google Cloud exec: Real-world data could eliminate the need for placebos in clinical trials


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The life-saving Covid-19 vaccines made by Pfizer and Moderna were developed and cleared by the Food and Drug Administration just 11 months after the U.S. classified the spread of the disease as a public health emergency. The dire circumstances of the pandemic drove this rapid timeline, as well as the drugmakers’ pioneering use of mRNA technology. 

The speed of these vaccines’ trials should inspire the pharmaceutical and medical device industries to accelerate an decentralize its clinical testing, Shweta Maniar, Google Cloud’s director for healthcare and life sciences, wrote in a Wednesday company blog post. She argued that harnessing real-world data will make faster clinical trials achievable for all therapeutics and devices.

Real-world data refers to information on the health outcomes of a diverse population living in a real-world setting. This data is often derived from a variety of sources, such as EMRs, patient surveys and claims submitted to payers. Since the collection of this heterogeneous data can paint a picture of the health outcomes across a wide population, it may be able to replace the placebo arm in a clinical trial one day, Maniar said in an interview.

“Companies are looking to apply real-world data in clinical trials so that in the future, you don’t even need a placebo,” she said. “You’d have enough historical information from real-world evidence to support that component.”

When clinical researchers use real-world data, they can view more data from more people, potentially deepening their understanding of how diseases behave in the body and how different populations take to treatments. The automatic collection of this data enables researchers to conduct clinical trials — the element that takes the longest time in the pharmaceutical and medical device supply chains — on a more efficient timeline.

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Real-world data is collected remotely, so it also allows researchers to include more participants in their trials. A November PwC study showed that 67% of Americans said they were less likely to join in a clinical trial if they were required to travel outside their local area to get to the research site. This gives drugmakers and devicemakers the opportunity to take clinical trials out of hospitals and universities and into virtual settings.

Some startups are built purely based on real-data’s potential to hasten and expand clinical trials. One of them is Medable, a decentralized clinical trials company that has raised $521 million since it was founded in 2012. The startup’s software makes it easier for pharmaceutical companies to remotely obtain trial participants’ consent, offers telehealth visits and harnesses data from remote monitoring devices. Thread is another prominent player using real-world data in the decentralized clinical trial space. In March, the company partnered with AWS to help scale and embed more predictive analytics into its real-world data platform. 

CVS was one of the biggest names to join the decentralized clinical trials movement last year. The health giant formed a clinical trials business to help drugmakers and contract research organizations recruit patients for studies. The company said it spun out the company to help address issues regarding low enrollment and a lack of diversity in clinical testing.

Google Cloud has also developed a solution for real-world data management for clinical trials. In 2019, the company released its Real-World Insights platform, which it co-developed with the FDA. The platform is based on FDA MyStudies, the agency’s open-source real-world data platform for clinical research. 

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Real-world data platforms like the ones offered by Medable, Thread, CVS and Google Cloud can help drugmakers and devicemakers improve trial enrollment. Maniar said life sciences companies should think about incorporating these platforms into their research sooner rather than later, because no one can predict when the next pandemic will come and create an urgent need for decentralized trials.

Photo: elenabs, Getty Images



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