The American Heart Association’s Precision Medicine Platform built by Hitachi Vantara is accelerating the research process by making data more accessible. Health Tech World spoke to Paul Watson, vice president of healthcare and life sciences, about how the platform is driving innovation and fostering collaboration between researchers across the world
In the world of research, accessing data can be a long and laborious task. Huge amounts of research data is generated every year in the global medical community, however a lack of a centralised repository to store this data means the research process can slow the research process down.
Researchers find themselves spending valuable time and money on searching or replicating data.
A researcher first has to find out who the data owner is, then make a request to use it. Once they have the go ahead from the owner to use the data, they may still need to apply for ethical approval. Once they eventually have approval, the researcher will need to know where to store the data.
The process does not end there. The scientist will also need adequate compute power to work with the information and the tools to join it with their own data. It can take several months or longer to have the data, storage, equipment and software ready to carry out the research.
American Heart Association’s Precision Medicine Platform alliance with Hitachi Vantara, the digital infrastructure, data management, and digital solutions subsidiary of Hitachi Ltd., is aiming to solve this problem
Vice president of healthcare and life sciences at Hitachi Vantara, Paul Watson, described the platform as one end-to-end process.
“It really does automate the [process] right from looking for data, understanding access and privilege, orchestrating the workflow, provisioning the workspace and moving the data up into that environment so people can do their research,” Watson told Health Tech World.
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The platform has the ability to search curated datasets by various common parameters such as a patient group or cohort. It then reveals to the researcher all of the datasets that match their criteria, whether public or private.
An ingrained security layer provides information about the owner of the data and what types of research it can be used for.
Once the researcher starts using the data it orchestrates a workflow for the approval process and allows them to manage funding, whether they are paying directly or via grant funding.
Scientists can then choose what kind of computing infrastructure they need. Following that it provides a secure workspace in the cloud which allows other members of the research team to access the data and tools.
“What this is doing is focusing on collaboration. It’s allowing multi-organisational teams to work within a common environment,” Watson added.
“They can also bring their own data in so let’s say you might be working with [some] data but then you have some study data that an industry partner wants to bring in. They can bring all of that into that common environment and work in the same place, with the same tools, developer and whatever else they’re using for their research. They can then publish the findings from that environment.”
The platform is also democratising research by making data more accessible to researchers with smaller budgets.
Watson continued: “It means that everybody, no matter whether you’re an independent researcher in a low-income country or you’re working for a pharma company or you’re involved with an academic study, all of these people get access to the same data on the same compute platform in the cloud, with or without grant funding.
“And they’re not hampered by not having the right tools or not having access to the compute infrastructure. It’s really putting everyone on a level playing field, rather than it only [being] the people who have access to the right equipment or technology who can do research.”
Automating the process of accessing data has reduced timescales down from weeks to just hours or days by breaking down the barriers that have historically slowed down the research process.
“The tool is an enabler,” Watsond added. “It is the scientists and the clinicians that are going to advance healthcare. What it should be doing is driving improved collaboration and accelerating science.
“I think the other thing it will do is hopefully foster more collaboration by providing a platform for collaboration.”
Hitachi Vantara began working together with American Heart Association’s Precision Medicine Platform in late 2015.
In May 2021, the American Heart Association decided to white label the Precision Medicine Platform to allow more organisations to benefit from it and bring in different datasets without needing to complete a similar development programme.
Hitachi Vantara has recently started working with a number of other organisations which now sit on a customised version of the Precision Medicine Platform.
“Different things will change so the way that you might search for your cohorts or your data sets might look different compared to the cardiovascular characteristics,” Watson said.
“Maybe some of the analytical tools in the workspaces will change as well but our view was that [if] we can white label it and repeat it, it lowers the investment cost and accelerates the timescales for the customers to deliver a similar platform.”
Watson sees Precision Medicine Platformevolving to start fostering communities among healthcare organisations that use the platform, creating a scaled collaboration model through which organisations exchange data and further drive the pace of research.
“You want as many perspectives as possible in [research]. People understand data in different ways and view connections between datasets in different ways,” Watson said.
“I think the more [we] can drive effective collaboration and partnerships, the smarter the research will be, and the more accurate it will be.
“The response times to emerging threats will be faster, because it’ll be faster and faster to turn the key on the research required to address those problems.”