Automated digital design for 3D-printed individualized therapies

Area of Science:

• Pharmaceutical Sciences
• Biomedical Engineering
• Materials Science

Background:

• Personalized medicine requires customizable pharmaceutical products, but current manufacturing and supply chains lack on-demand capabilities.
• Three-dimensional (3D) printing offers a potential solution for tailoring drug dose, release profiles, and physical characteristics like size and shape.

Purpose of the Study:

• To develop and validate a computational algorithm for designing customized, grid-like orodispersible films (ODFs) based on prescribed drug dosages.
• To demonstrate the feasibility of 3D printing these individualized ODFs with incorporated cannabidiol (CBD) for personalized medicine applications.

Main Methods:

• A proof-of-concept computational algorithm was designed to calculate optimal ODF dimensions for specific doses.
• The algorithm generates digital design files for 3D printing individualized ODFs.
• Cannabidiol (CBD)-loaded ODFs were fabricated using 3D printing and characterized for physicochemical, mechanical, disintegration, and drug release properties.

Main Results:

• The algorithm accurately estimated drug doses and enabled the reproducible manufacturing of individualized ODFs.
• In vitro drug release and performance were significantly influenced by the ODF's grid structure dimensions (thickness and volume).
• The 3D-printed ODFs demonstrated suitable physicochemical and mechanical properties for pharmaceutical use.

Conclusions:

• The developed computational algorithm and 3D printing approach offer a viable method for automated, on-demand manufacturing of personalized medications.
• This technology can facilitate decentralized pharmaceutical production at points of care, such as hospitals and local pharmacies.
• The study highlights the potential of 3D printing for creating customized drug delivery systems tailored to individual patient requirements.