TY - JOUR

T1 - Automated digital design for 3D-printed individualized therapies

AU - Eleftheriadis, Georgios K.

AU - Kantarelis, Efthymios

AU - Monou, Paraskevi Kyriaki

AU - Andriotis, Eleftherios G.

AU - Bouropoulos, Nikolaos

AU - Tzimtzimis, Emmanouil K.

AU - Tzetzis, Dimitrios

AU - Rantanen, Jukka

AU - Fatouros, Dimitrios G.

PY - 2021

Y1 - 2021

N2 - Customization of pharmaceutical products is a central requirement for personalized medicines. However, the existing processing and supply chain solutions do not support such manufacturing-on-demand approaches. In order to solve this challenge, three-dimensional (3D) printing has been applied for customization of not only the dose and release characteristics, but also appearance of the product (e.g., size and shape). A solution for customization can be realized via non-expert-guided processing of digital designs and drug dose. This study presents a proof-of-concept computational algorithm which calculates the optimal dimensions of grid-like orodispersible films (ODFs), considering the recommended dose. Further, the algorithm exports a digital design file which contains the required ODF configuration. Cannabidiol (CBD) was incorporated in the ODFs, considering the simple correspondence between the recommended dose and the patient's weight. The ODFs were 3D-printed and characterized for their physicochemical, mechanical, disintegration and drug release properties. The algorithm was evaluated for its accuracy on dose estimation, highlighting the reproducibility of individualized ODFs. The in vitro performance was principally affected by the thickness and volume of the grid-like structures. The concept provides an alternative approach that promotes automation in the manufacturing of personalized medications in distributed points of care, such as hospitals and local pharmacies.

AB - Customization of pharmaceutical products is a central requirement for personalized medicines. However, the existing processing and supply chain solutions do not support such manufacturing-on-demand approaches. In order to solve this challenge, three-dimensional (3D) printing has been applied for customization of not only the dose and release characteristics, but also appearance of the product (e.g., size and shape). A solution for customization can be realized via non-expert-guided processing of digital designs and drug dose. This study presents a proof-of-concept computational algorithm which calculates the optimal dimensions of grid-like orodispersible films (ODFs), considering the recommended dose. Further, the algorithm exports a digital design file which contains the required ODF configuration. Cannabidiol (CBD) was incorporated in the ODFs, considering the simple correspondence between the recommended dose and the patient's weight. The ODFs were 3D-printed and characterized for their physicochemical, mechanical, disintegration and drug release properties. The algorithm was evaluated for its accuracy on dose estimation, highlighting the reproducibility of individualized ODFs. The in vitro performance was principally affected by the thickness and volume of the grid-like structures. The concept provides an alternative approach that promotes automation in the manufacturing of personalized medications in distributed points of care, such as hospitals and local pharmacies.

KW - 3D printing

KW - Fused deposition modeling

KW - Digital health

KW - Algorithm

KW - Personalization

KW - Orodispersible films

KW - Cannabidiol

U2 - 10.1016/j.ijpharm.2021.120437

DO - 10.1016/j.ijpharm.2021.120437

M3 - Journal article

C2 - 33662466

VL - 599

JO - International Journal of Pharmaceutics

JF - International Journal of Pharmaceutics

SN - 0378-5173

M1 - 120437

ER -