Predicting pharmaceutical inkjet printing outcomes using machine learning

• Published in: International journal of pharmaceutics: X Vol. 5; p. 100181
• Main Authors: Carou-Senra, Paola, Ong, Jun Jie, Castro, Brais Muñiz, Seoane-Viaño, Iria, Rodríguez-Pombo, Lucía, Cabalar, Pedro, Alvarez-Lorenzo, Carmen, Basit, Abdul W., Pérez, Gilberto, Goyanes, Alvaro
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.12.2023; Elsevier
• Subjects: 2D and 3D printed drug products; Additive manufacturing and personalized medications; Artificial intelligence and digital health; Design and fabrication of medicinal products; Desktop ink jet printing of pharmaceuticals and drug delivery systems; Rational formulation development; Special Issue on Interreg project “Site-Specific Drug Delivery”; Additive manufacturing and personalized medications; 2D and 3D printed drug products; Artificial intelligence and digital health; Desktop ink jet printing of pharmaceuticals and drug delivery systems; Rational formulation development; Design and fabrication of medicinal products

Inkjet printing has been extensively explored in recent years to produce personalised medicines due to its low cost and versatility. Pharmaceutical applications have ranged from orodispersible films to complex polydrug implants. However, the multi-factorial nature of the inkjet printing process make...