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M3DISEEN: A novel machine learning approach for predicting the 3D printability of medicines.
Elbadawi, Moe; Muñiz Castro, Brais; Gavins, Francesca K H; Ong, Jun Jie; Gaisford, Simon; Pérez, Gilberto; Basit, Abdul W; Cabalar, Pedro; Goyanes, Alvaro.
Afiliação
  • Elbadawi M; Department of Pharmaceutics, UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK.
  • Muñiz Castro B; IRLab, CITIC Research Center, Department of Computer Science, University of A Coruña, Spain.
  • Gavins FKH; Department of Pharmaceutics, UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK.
  • Ong JJ; Department of Pharmaceutics, UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK.
  • Gaisford S; Department of Pharmaceutics, UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK; FabRx Ltd., 3 Romney Road, Ashford, Kent TN24 0RW, UK.
  • Pérez G; IRLab, CITIC Research Center, Department of Computer Science, University of A Coruña, Spain. Electronic address: gilberto.pvega@udc.es.
  • Basit AW; Department of Pharmaceutics, UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK; FabRx Ltd., 3 Romney Road, Ashford, Kent TN24 0RW, UK. Electronic address: a.basit@ucl.ac.uk.
  • Cabalar P; IRLab, Department of Computer Science, University of A Coruña, Spain.
  • Goyanes A; Department of Pharmaceutics, UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK; FabRx Ltd., 3 Romney Road, Ashford, Kent TN24 0RW, UK; Departamento de Farmacología, Farmacia y Tecnología Farmacéutica, I+D Farma Group (GI-1645), Universidade de Santiago de
Int J Pharm ; 590: 119837, 2020 Nov 30.
Article em En | MEDLINE | ID: mdl-32961295
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Tecnologia Farmacêutica Idioma: En Ano de publicação: 2020 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Tecnologia Farmacêutica Idioma: En Ano de publicação: 2020 Tipo de documento: Article