Swarm Robotics Promises to Boost Diagnostics, Treat Cancer

Swarm Robotics Promises to Boost Diagnostics, Treat Cancer

Source: ClipArt.com

January 03, 2019      

Inga Shugalo

The concept of swarming is characterized by individual organisms creating a real-time system with continuous feedback and unified behavior. It can be seen in ants in colonies, bees in hives, or birds in flocks. This swarm intelligence allows them to amplify individual cognitive abilities and helps the group reach critical survival goals, such as migrating, providing, and defending from predators. Swarm robotics follows this natural model and offers benefits to healthcare.

With artificial intelligence, we can emulate swarm intelligence by giving multiple small robots different tasks. Swarming robots can be used across many industries, including education, agriculture, and manufacturing. In our humble opinion, however, the most fascinating application for swarm robotics can be achieved in healthcare.

Once we understand the basics of swarm robotics, let’s look at two already in-test directions for them in patient diagnostics and treatment.

The whys and hows of swarm robotics

Swarm robotics is a new approach to managing simple physical robots comprising multi-robot systems. Scientists are studying how individually engineered robots functioning autonomously can self-organize and achieve bigger goals when cooperating in a swarm.

Each robot operates with limited information, communicates with other robots within the system, and follows basic preset rules on how to interact with the environment. The combination of given information and rules across all the robots forms collective behaviors and allows the swarm to collaborate to accomplish different tasks, such as collecting, clustering, or transporting objects.

Distributed and self-coordinating swarm robotics offers several advantages, including the following:

  • Scalability. The system isn’t limited to a particular number of separate agents and can become as large or small as necessary.
  • Failure resistance. The robot swarm won’t stop operating if any of its agent malfunctions.
  • Flexibility. The swarm can adapt to different environments by altering the group behavior.

Robot swarms for diagnosis

In a recent study, researchers came up with the idea to harness swarming robots for achieving better precision in locating pre-cancerous pathologies in the gastrointestinal lumen.

They first tested out the hypothesis by employing swarm intelligence algorithms to define metastases on bone scintigraphy images. Bone scans are usually performed in patients diagnosed with lung, breast, and prostate cancer. The experimental 10,000 swarm agents were able to process the scans and accurately trace the abnormalities.

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The researchers said that the algorithm could enhance current robotic endoscopy efforts with the swarm intelligence. The use of small robots instead of a long insertion tube to study a patient’s gastrointestinal system is moving from science fiction to to smart diagnosis.

Swarm robotics could be able to finish the task faster and identify pathologies with higher precision. In case an anomaly is found, the robot swarm could be seamlessly repurposed to sew the tissue, remove the foreign object, or transport the medication exactly to the target area.

Swarm robotics in cancer treatment

No matter how advanced, most of the available cancer treatments still cause side effects by spreading across the patient’s body from the bloodstream, attacking both healthy and cancerous cells. To minimize the harm, the therapy should be focused on attacking malignancies only.

Precision medicine and personalized therapies promise to minimize side effects by being tailored to patient genetics. However, such treatment can’t be applied to all cancer types and to any patient. Swarm robotics has the potential to take personalized cancer treatment up a notch.

Swarming nanobots might interact with cancerous cells and destroy the tumor from within, injecting the drug directly, and unlocking the possibility to avoid any impact on healthy tissue.

Other researchers are exploring the idea of nanobots being the treatment itself, drilling into cancerous cells and blasting them in just one minute. These bots are able to identify malignant cells and attach to them. When being activated with light, the bots spin with the speed of about 2 million to 3 million times per second, killing the cell without any chemicals used.

According to one of the researchers, Dr. Robert Pal, “once developed, this approach could provide a potential step change in noninvasive cancer treatment and greatly improve survival rates and patient welfare globally.”

As a swarm, the nanobots will be able to move fast and destroy whole tumors from within. No drug required, no exhaustive chemotherapies, and no more years-long treatment courses.

If the swarms can be programmed to take down different types of cancer, this might make consign them to diseases of the past, such as bubonic plague, leprosy, or polio.

How long until swarming robots change healthcare?

Being both powerful and challenging, swarming robots have the potential to become the new standard in healthcare.

Healthcare technology vendors, such as Itransition, Practice Fusion, Cerner, eClinicalWorks, and others have worked to improve their offerings with the cloud, CRM, blockchain, and AI. It took them about five years to fully grasp some of the technologies.

How fast it may happen with swarm robotics? We would give this innovation about 10 to 15 years before its full-blown market appearance, considering that it will have to pass clinical trials to become part of the care cycle.

Inga Shugalo

About the author

Inga Shugalo is a healthcare industry analyst at Itransition, a custom software development company headquartered in Denver, Colo. She focuses on healthcare IT, highlighting the industry challenges and technology solutions that tackle them. Shugalo’s articles explore diagnostic potential of healthcare IoT, opportunities of precision medicine, robotics and virtual reality in healthcare, and more.

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