Listar GI-IRlab-Artigos por autor "Elbadawi, Moe"
Mostrando ítems 1-2 de 2
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M3DISEEN: A novel machine learning approach for predicting the 3D printability of medicines
Elbadawi, Moe; Muñiz, Brais; Gavins, Francesca K.H.; Ong, Jun Jie; Gaisford, Simon; Pérez, Gilberto; Basit, Abdul W; Cabalar, Pedro; Goyanes, Álvaro (Elsevier B.V., 2020-11)[Abstract]: Artificial intelligence (AI) has the potential to reshape pharmaceutical formulation development through its ability to analyze and continuously monitor large datasets. Fused deposition modeling (FDM) ... -
Machine learning predicts 3D printing performance of over 900 drug delivery systems
Muñiz, Brais; Elbadawi, Moe; Ong, Jun Jie; Pollard, Thomas; Song, Zhe; Gaisford, Simon; Pérez, Gilberto; Basit, Abdul W; Cabalar, Pedro; Goyanes, Álvaro (Elsevier B.V., 2021-09)[Abstract]: Three-dimensional printing (3DP) is a transformative technology that is advancing pharmaceutical research by producing personalized drug products. However, advances made via 3DP have been slow due to the lengthy ...