AI-Enhanced Catheter for Medication-Free UTI Prevention

A 3D-printed catheter creates a miniature obstacle course to thwart microbes, addressing widespread infections in hospital settings.

Over 100 million people globally need a urinary catheter annually, which is crucial post-surgery. Yet, around one quarter in developing nations and about an eighth in the U.S. who use them may experience catheter-associated urinary tract infections (CAUTI) due to bacterial accumulation in the tube.

Assisted by artificial intelligence, researchers have developed a novel catheter aiming to decrease bacterial contamination significantly—up to two orders of magnitude—without resorting to antibiotics. The catheter’s interior features three-dimensional geometric shapes that impede bacteria, presenting promising results, according to Glenn Werneburg, a Cleveland Clinic urologist not involved in the study, as reported in Science Advances.

“In a conventional catheter, there’s no internal structure,” explains study co-author Animashree Anandkumar, a computer scientist at the California Institute of Technology. This absence of physical shape provides a smooth pathway for bacteria to ascend from the exterior and establish colonies on the inner surface. Accumulation near the bladder in the catheter can result in bacteria entering the urinary tract, contributing to catheter-associated urinary tract infections (CAUTI).

Historically, doctors have employed coatings like antibiotics or metallic agents to combat bacterial growth on catheter walls, but these methods can be costly and increasingly ineffective against antibiotic-resistant bacteria. The innovative device takes a different approach, using simple geometry rather than specialized coatings. Tiny 3D-printed ridges in the shape of sharp triangles line the catheter’s interior, creating an obstacle course for bacteria. This design, as bacteria navigate the ridges, could potentially reduce reliance on costly antibiotics and extend catheter usage.

How a New Al-Optimized Catheter Design Blocks Bacteria

Escherichia coli and similar bacteria move against the current by employing a “run and tumble” motion, alternating between moving in one direction and brief stops for reorientation. A catheter tube designed with artificial intelligence optimization utilizes this movement pattern to guide harmful bacteria downstream, effectively preventing infections.

Anandkumar and her team employed AI to efficiently simulate tens of thousands of digitally modeled catheters efficiently, seeking the optimal bacteria-repelling labyrinth. After identifying a design that effectively obstructed virtual bacteria across various scenarios, they 3D printed a prototype and tested it in the lab using a broth containing Escherichia coli bacteria. Results showed that after 24 hours, the experimental device accumulated nearly 100 times fewer bacterial colonies compared to a traditional catheter 3D printed and tested alongside it.

The current version of the new catheter is specifically designed to resist E. coli, a prevalent microbe linked to CAUTIs. While effective against this bacterium, other species can colonize catheters and lead to infections. Glenn Werneburg notes that bacteria on catheters form biofilms, and different bacterial species behave differently. To address this, the team might need to create a modified design in the future that is also impervious to other microbes, such as Enterococcus and Proteus bacteria.

Anandkumar acknowledges the need for additional research, emphasizing the necessity of more data on the physical and chemical properties of various microbes to model new designs accurately. Before widespread production, the team must conduct clinical testing. Anandkumar envisions the broader potential of AI modeling, extending beyond catheters. She aspires to leverage AI for designing drugs, energy-efficient airplane propellers, and various applications, stating that this marks just the beginning of AI’s potential impact.

Read the original article on: Scientific American

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