‘Revolutionary’ AI implant a game changer for many illnesses

Dr. AI is almost here.

Researchers from MIT have created a new, “one-size-fits-all” medical implant that strives to make the treatment of several chronic illnesses like diabetes much more patient-friendly.

Such a “tailored treatment” device relies on artificial intelligence (AI) and soft robots, according to MIT and fellow researchers from the University of Galway.

The implant has capabilities of not only administering a drug of all sorts to patients but, through AI, can now determine when the device is being rejected. From there, the high-powered technology can modify its shape to continue drug delivery while also avoiding a build of scar tissue.

“Imagine a therapeutic implant that can also sense its environment and respond as needed using AI,” co-author Dr. Rachel Beatty said of the tech, initially made for fibrosis treatment.

“This approach could generate revolutionary changes in implantable drug delivery for a range of chronic diseases.”

It’s done through an emerging approach known as mechanotherapy — the utilization of soft robots normalizing itself in the human body by actions like inflation and deflation. Its limberness is what helps prevent scar tissue from forming as it’s designed as a “porous membrane that can sense when pores are blocked by scar tissue,” according to the scientists.

A machine learning algorithm had also been created to predict the proper levels of deploying a drug’s dose.

“If we can sense how the individual’s immune system is responding to an implanted therapeutic device…it could have great potential in personalized, precision drug delivery, reducing off-target effects and ensuring the right amount of drug is delivered at the right time,” said MIT mechanical engineering professor Ellen Roche.

“The work presented here is a step towards that goal.”

This breakthrough comes shortly after an AI brain implant allowed a paralyzed Long Island man the ability to lift his arms and regain his sense of feel and another brought back a paralyzed woman’s ability to speak through machines.