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The international company partnered with Ole Miss researcher Mo Maniruzzaman to create a learning algorithm that can help pharmacists and drug manufacturers use 3D printing more easily.

"Essentially, we're creating a bank of information, a reference book for drug manufacturing," said Maniruzzaman, chair and professor of pharmaceutics and drug delivery. "Creating this AI database will be really useful – not just for Colorcon – but for similar companies and even pharma giants.

"They could easily adopt this kind of platform for their own discovery pipeline and leverage our findings to solve problems."

Every medication includes two kinds of components: active ingredients such as acetaminophen in pain-relievers; and inactive ingredients such as the binders, fillers, coloring agents and coating materials that hold a pill together.

Not all inactive ingredients can pair with every active ingredient, meaning each time a drug is manufactured, the researchers behind it must ensure that the medication's ingredients do not interfere with one another.

Maniruzzaman and his lab will create an AI-powered database that can pair the correct inactive ingredients to print whatever medication is needed. This database could pave the way for the widespread use of 3D-printed medication in pharmacies, the researchers said.

"The problem with the conventional dosage form is that the conventional dosage forms are not personalized to the patient," said Kshitij Chitnis, a third-year doctoral student in pharmaceutics and drug delivery and a member of Maniruzzaman's lab. "It would be a difficult thing for the industry to make personalized drugs traditionally."

Using a 3D printer, however, would allow pharmacists to tailor medication to the patient's needs, such as creating a smaller capsule or pill for a child or even creating a timed-release capsule that delivers medication when the patient needs it.

One of the biggest roadblocks to implementing 3D-printed medication on a large scale is the need for pharmacists to learn how to operate the printers.

An AI tool that can select which inactive materials, called excipients, pair best with a drug and tell the printer what to make would streamline that process, said Sujith raj Bashetty, a third-year doctoral student in pharmaceutics and drug delivery and a member of the lab.

"Here we are paving the pathway for scalable and regulated 3D-printed medication," he said. "If we successfully use industrial-grade excipients, we can reduce the burden of large scalability, and if we can print on-demand medication in pharmacies, that will save millions of dollars.

"We are aiming to bridge the advanced manufacturing gap with scalable pharmaceutical development and enabling the future of personalized, high-performance drug delivery."

Top: Doctoral students Kshitij Chitnis (left) and Sujith Bashetty hold a filament that serves as the 'ink' for 3D-printed medication. They are part of an Ole Miss research team that is working to develop an artificial intelligence-powered guide that pharmacies can use to print personalized medications. Photo by Kevin Bain/Ole Miss Digital Imaging Services