Hybrid bioprinter creates capillary networks narrower than 10 micrometers

In the United States, over 100,000 people are currently on the waiting list for organ transplants, with a new individual added to the list every ten minutes. Transplant recipients must take immunosuppressive medications for the rest of their lives, increasing their risk of infections and requiring a strict lifestyle. The success of a transplant also hinges on the organ not being rejected by the recipient's body.

Scientists have been working for decades to bioprint tissues and organs using a patient's own cells, aiming to circumvent the need for organ transplant and the associated risks. However, replicating the intricate vascular networks of the human body, particularly capillaries, remains a significant challenge. Capillaries are the smallest blood vessels that deliver oxygen and nutrients to every cell, making them vital to any viable bioengineered tissue model.

Yanliang Zhang, an Advanced Materials and Manufacturing Collegiate Professor at the University of Notre Dame, and his team have developed a novel hybrid bioprinting technique that can produce capillary networks with vessels narrower than 10 micrometers in diameter. Capillaries are smaller than a human hair, and printing them with the necessary precision while maintaining scalability and structural integrity has been a major hurdle in current bioprinting methods.

The hybrid printing approach combines two distinct 3D printing techniques—extrusion and aerosol jet printing (AJP)—and incorporates machine learning to automatically optimize printing parameters for each desired vascular configuration. Extrusion, a widely used method, creates a soft, gel-like scaffold that mimics real tissue by dispersing biomaterials layer by layer.

Within this matrix, thin threads of gelatin are deposited by aerosol jet printing, which are later removed to create channels embedded within the matrix. The unique aerodynamic focusing feature of AJP allows for dynamic adjustments, enabling the printing of channel sizes from hundreds of micrometers down to several micrometers, replicating the varied architecture of natural vessels.

Yanliang Zhang and his colleagues integrated a machine learning framework to efficiently determine the ideal combination of printing parameters for each channel size. This autonomous optimization significantly boosts the efficiency of producing the desired quality and precision in the printed channels.

The researchers successfully created hierarchical vascular networks in one, two, and three dimensions using this hybrid printing method. The printed channels were then seeded with endothelial cells, which line the body's blood and lymphatic vessels, leading to the formation of single-cell layers resembling those found in living human tissues. The cells rapidly attached and spread along the inner walls of the channels, replicating the barrier function of real human capillaries.

This breakthrough in bioprinting capillary networks offers promising solutions for therapeutic discovery, regenerative medicine, and organ engineering. By accurately mimicking human vascular networks at the microscopic level, such models can serve as new organ-on-a-chip platforms for testing drug safety and efficacy. Moreover, using patient-specific cells to create these models holds potential for personalized medicine, allowing for the evaluation of therapeutic responses within the model system before full-scale treatment.

Yanliang Zhang's ultimate goal is to develop an autonomous, intelligent bioprinter capable of producing fully functional tissues and organs, including the heart, kidney, and liver. In the near term, his research group at Notre Dame and collaborators at Harvard aim to build an enhanced version of the hybrid bioprinter and pursue the fabrication of lab-grown organs. The potential impact of this technology is immense, particularly in alleviating the severe shortage of organ transplants and improving human health.