Artificial Intelligence Fulfills Injection Robots

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Demographic change and the lack of supply in rural areas are problematic factors that will require a solution strategy in the future. Various research projects are already examining whether injection robots can help us in our daily clinical routine in the future.

Intravitreal administration of drugs is the therapy of choice for many ophthalmological diseases. The chronic course of the disease, such as the exudative form of age-related macular degeneration, macular edema after retinal vein occlusion, or diabetic maculopathy, makes it necessary to manage patients undergoing treatment with IVOM regularly.

Demographic change and the lack of supply in rural areas are problematic factors that will require a solution strategy in the future. Various research projects are already examining whether injection robots can help us in our daily clinical routine in the future. Just recently, an interesting scientific article was published, which deals with the safety aspects of intravitreal injection by a robot. 

The ARTORG centre develops technical solutions for clinical problems. The combination of clinics and medical technology research within a faculty of medicine makes the ARTORG centre unique in Europe. 

Among other things, it develops artificial organs on a chip, robotics in the field of surgery and rehabilitation, implants of heart valves without failure, new therapies for urinary leakage and tinnitus, as well as applications for smartphones working with artificial intelligence, which serve as diagnostic aids or daily support for diabetic patients.

What role does artificial intelligence play in this project?

Sznitman: First of all, it’s important to know that artificial intelligence is associated with different things these days. Some people already call robotics “artificial intelligence.” I mainly work on AI systems that analyze input signals from, for example, medical images. This process is supposed to be automated. In this project, the AI ​​image recognition capability was automated. The objective was automatically to estimate the physical force applied to the eye during intravitreal injection by injection robots.

How does your method improve the safety profile of intravitreal injections by injection robots?

Sznitman: Artificial intelligence is supposed to provide a protective mechanism for the injection process: during an intravitreal injection performed by an injection robot, the amount of force the eye is exposed to during the process injection can be calculated by looking at the image data from the camera. If this force is too high, the robot can be told to move away from the eye. If the force is sufficient, the injection can be continued.

When do you think intravitreal injections by injection robots will become part of our clinical routine?

Sznitman: This project is still very futuristic. This is a conceptual prototype. With her, we wanted to know if intravitreal injections by injection robots are possible. Through this project, we will learn what additional steps and measures are needed to make safe, precise, and personalized intravitreal injection by injection robots a reality.

What are the benefits of artificial intelligence for the healthcare system?

Sznitman: In my view, AI systems are “co-clinical tools.” They are meant to help practising doctors with monotonous tasks. AI systems can automatically recognize biomarkers. They can help quantify subretinal or intraretinal fluid in OCT images. The impact of AI systems on the health system is immense: today, a very large amount of health data is generated. Artificial intelligence can help us ensure that doctors receive the important health data of their patients for their treatment. Projections show that AI systems have great potential for savings in ​​chronic diseases.