Hybrid modelling of pharmaceutical mixture properties : predictive solutions for particle size, shape, flow, and density

Salehian, Mohammad and Moores, Jonathan and Ibrahim, Isra' Tayseer Mohammad and Abbas, Faisal and Markl, Daniel (2023) Hybrid modelling of pharmaceutical mixture properties : predictive solutions for particle size, shape, flow, and density. In: 10th International Granulation Conference, 2023-06-20 - 2023-06-23.

ORCID iDs

Salehian, Mohammad ORCID: https://orcid.org/0000-0003-4073-292X

Markl, Daniel ORCID: https://orcid.org/0000-0003-0411-733X

• Share and Export
  

  RDF+XMLBibTeXRIOXX2 XMLRDF+N-TriplesJSONDublin CoreAtomSimple MetadataReferMETSHTML CitationASCII CitationOpenURL ContextObjectEndNoteOpenURL ContextObject in SpanMODSMPEG-21 DIDLEP3 XMLData Cite XMLRIS (EndNote Online, Zotero, Ref manager, etc)RDF+N3Multiline CSV
• Item metadata

  Item type:	Conference or Workshop Item(Poster)
  ID code:	85953
  Dates:	Date Event 20 June 2023 Published
  Keywords:	computational modelling, artificial intelligence, model-based optimisation framework, Pharmaceutical technology, Pharmaceutical Science
  Subjects:	Medicine > Pharmacy and materia medica > Pharmaceutical technology
  Department:	Faculty of Science > Strathclyde Institute of Pharmacy and Biomedical Sciences
  Depositing user:	Pure Administrator
  Date deposited:	27 Jun 2023 14:18
  Last modified:	28 Jun 2023 02:36
  URI:	https://strathprints.strath.ac.uk/id/eprint/85953