Artificial intelligence can speed the development of 3D printed bioscaffolds...
Artificial intelligence can speed the development of 3D printed bioscaffolds like the one above to help injuries heal.
Source: Photo by Jeff Fitlow

Machine learning speeds up bioscaffold development

A dose of artificial intelligence can speed the development of 3D-printed bioscaffolds that help injuries heal, according to researchers at Rice University. A team led by computer scientist Lydia Kavraki of Rice's Brown School of Engineering used a machine learning approach to predict the quality of scaffold materials, given the printing parameters.

The work also found that controlling print speed is critical in making high-quality implants. Bioscaffolds developed by co-author and Rice bioengineer Antonios Mikos are bonelike structures that serve as placeholders for injured tissue. They are porous to support the growth of cells and blood vessels that turn into new tissue and ultimately replace the implant.

Mikos has been developing bioscaffolds, largely in concert with the Center for Engineering Complex Tissues, to improve techniques to heal craniofacial and musculoskeletal wounds. That work has progressed to include sophisticated 3D printing that can make a biocompatible implant custom-fit to the site of a wound.

With the help of machine learning techniques, designing materials and developing processes to create implants can be faster and eliminate much trial and error. "We were able to give feedback on which parameters are most likely to affect the quality of printing, so when they continue their experimentation, they can focus on some parameters and ignore the others," said Kavraki, a renowned authority on robotics, artificial intelligence and biomedicine and director of Rice's Ken Kennedy Institute.

Kavraki said the researchers - graduate students Anja Conev and Eleni Litsa in her lab and graduate student Marissa Perez and postdoctoral fellow Mani Diba in the Mikos lab, all co-authors of the paper - took time at the start to establish an approach to a mass of data from a 2016 study on printing scaffolds with biodegradable poly(propylene fumarate), and then to figure out what more was needed to train the computer models.

A “high quality” 3D printed bioscaffold as designed with help from a...
A “high quality” 3D printed bioscaffold as designed with help from a machine learning algorithm developed at Rice University. Scale bar equals 1 millimeter.
Source: Courtesy of the Mikos Research Group

The team explored two modeling approaches. One was a classification method that predicted whether a given set of parameters would produce a "low" or "high" quality scaffold. The other was a regression-based approach that approximated the values of print-quality metrics to come to a result. Kavraki said both relied upon a "classical supervised learning technique" called random forest that builds multiple "decision trees" and "merges" them together to get a more accurate and stable prediction. Ultimately, the collaboration could lead to better ways to quickly print a customized jawbone, kneecap or bit of cartilage on demand.

"A hugely important aspect is the potential to discover new things," Mikos said. "This line of research gives us not only the ability to optimize a system for which we have a number of variables - which is very important - but also the possibility to discover something totally new and unexpected. In my opinion, that's the real beauty of this work. "It's a great example of convergence," he said. "We have a lot to learn from advances in computer science and artificial intelligence, and this study is a perfect example of how they will help us become more efficient."

"In the long run, labs should be able to understand which of their materials can give them different kinds of printed scaffolds, and in the very long run, even predict results for materials they have not tried. We don't have enough data to do that right now, but at some point we think we should be able to generate such models," Kavraki said. "Artificial intelligence has a role to play in new materials, so what the institute offers should be of interest to people on this campus," she said. "There are so many problems at the intersection of materials science and computing, and the more people we can get to work on them, the better."

The research was published Tissue Engineering Part A.

Subscribe to our newsletter

Related articles

3D printed bioceramic implant induces cranial regrowth

3D printed bioceramic implant induces cranial regrowth

A bioceramic implant has proved to stimulate regeneration of natural skull bone so that even large cranial defects can be repaired in a way that has not been possible before.

“Stretching rack” for cells

“Stretching rack” for cells

An ingenious device, only a few micrometers in size, enables to study the reaction of individual biological cells to mechanical stress.

Scientists get soft on 3D printing

Scientists get soft on 3D printing

Researchers have developed a new method of 3D printing gels and other soft materials.

Oxygen-releasing bioink for bioprinting

Oxygen-releasing bioink for bioprinting

Researchers have developed an oxygen-releasing bioink that may be useful in 3D printing bioengineered cell constructs.

A 3D printed device to excite nerves

A 3D printed device to excite nerves

A tiny, thin-film electrode with a 3D-printed housing has been implanted in the peripheral nervous system of songbirds, where it successfully recorded electrical impulses that drive vocalizations.

Aerogel: the micro structural material of the future

Aerogel: the micro structural material of the future

Researchers have now succeeded in making aerogels accessible to microelectronics and precision engineering.

Lego-inspired 3D printed soft tissue bricks

Lego-inspired 3D printed soft tissue bricks

Researchers have developed a tiny, 3D-printed technology that can be assembled like Lego blocks and help repair broken bones and soft tissue.

Pectus Excavatum: 3D printed scaffold implanted

Pectus Excavatum: 3D printed scaffold implanted

Surgeons have implanted a patient suffering from a congenital defect with a novel, absorbable soft tissue reconstruction scaffold.

Sugar: Sweet way to 3D print blood vessels

Sugar: Sweet way to 3D print blood vessels

Scientists have developed a way of using laser-sintering of powdered sugars to produce highly detailed structures that mimick the body’s intricate, branching blood vessels in lab-grown tissues.

Popular articles