The advance by teams at University of Galway and Massachusetts Institute of Technology (MIT) could lead to intelligent, long-lasting, tailored treatment for patients.
The implantable device can administer a drug – and sense when the body is beginning to reject it - and use AI to change the shape of the device to maintain drug dosage, simultaneously bypassing scar tissue buildup and maintaining treatment. The team’s findings are detailed in Science Robotics.
Implantable medical device technologies offer promise to unlock advanced therapeutic interventions in healthcare, such as insulin release to treat diabetes, but a major issue holding back such devices is the patient’s reaction to a foreign body.
In a statement, Dr Rachel Beatty, University of Galway, and co-lead author on the study, said: “The technology which we have developed, by using soft robotics, advances the potential of implantable devices to be in a patient’s body for extended periods, providing long-lasting therapeutic action. Imagine a therapeutic implant that can also sense its environment and respond as needed using AI - this approach could generate revolutionary changes in implantable drug delivery for a range of chronic diseases.”
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The University of Galway-MIT research team originally developed first-generation soft robotic implants to improve drug delivery and reduce fibrosis. Despite that success, the technology did not account for how individual patients react and respond, or for the progressive nature of fibrosis, where scar tissue builds around the device and eventually forcing it to fail.
“I wanted to tailor drug delivery to individuals but needed to create a method of sensing the foreign body response first,” said Dr Beatty.
The research team deployed mechanotherapy, an emerging technique to help reduce scar tissue formation through the movement of soft robotic implants. The timed, repetitive or varied movements helps to prevent scar tissue from forming.
The implantable device also contains a conductive porous membrane that can sense when pores are blocked by scar tissue.
The researchers measured electrical impedance and scar tissue formation on the membrane, finding a correlation. A machine learning algorithm was also developed to predict the required number and force of actuations to achieve consistent drug dosing, regardless of the level of fibrosis present. Using computer simulations, the researchers explored the potential of the device to release a drug over time with a surrounding fibrotic capsule of different thicknesses.
The research showed that changing the force and number of times the device moved or changed shape allowed the device to release more of the drug, helping to bypass scar tissue build-up.
Professor Ellen Roche, Professor of Mechanical Engineering at MIT, said: “If we can sense how the individual’s immune system is responding to an implanted therapeutic device and modify the dosing regime accordingly, it could have great potential in personalised, precision drug delivery, reducing off-target effects and ensuring the right amount of drug is delivered at the right time. The work presented here is a step towards that goal.”
The research was funded in part by Science Foundation Ireland’s Research Centres for Advanced Materials and BioEngineering Research (AMBER) centre and Medical Devices (CÚRAM), the European Union’s Horizon 2020 framework and the Mechanical Engineering Department at MIT.
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