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Building an AI Army of Digital Twins to Fight Cancer


 

The Long Push Forward

One big hurdle to making digital twins more widely available is that regulation for the technology is still in progress.

“We’re developing the technology, and what’s also happening is the regulatory framework is being developed in parallel. So we’re almost developing things blindly on the basis that we think this is what the regulators would want,” explained Asghar.

“It’s really important that these technologies are regulated properly, just like drugs, and that’s what we’re pushing and advocating for,” said Asghar, noting that people need to know that like drugs, a digital twin has strengths and limitations.

And while a digital twin can be a cost-saving approach in the long run, it does require funding to get a program built, and finding funds can be difficult because not everyone knows about the technology. More funding means more trials.

With more data, Asghar is hopeful that within a few years, a digital twin model could be available for clinicians to use to help inform treatment decisions. This could lead to more effective treatments and, ultimately, better patient outcomes.

A version of this article appeared on Medscape.com.

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