Disrupting 3D printing of medicines with machine learning.

Journal: Trends in pharmacological sciences
Published Date:

Abstract

3D printing (3DP) is a progressive technology capable of transforming pharmaceutical development. However, despite its promising advantages, its transition into clinical settings remains slow. To make the vital leap to mainstream clinical practice and improve patient care, 3DP must harness modern technologies. Machine learning (ML), an influential branch of artificial intelligence, may be a key partner for 3DP. Together, 3DP and ML can utilise intelligence based on human learning to accelerate drug product development, ensure stringent quality control (QC), and inspire innovative dosage-form design. With ML's capabilities, streamlined 3DP drug delivery could mark the next era of personalised medicine. This review details how ML can be applied to elevate the 3DP of pharmaceuticals and importantly, how it can expedite 3DP's integration into mainstream healthcare.

Authors

  • Moe Elbadawi
    UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK; School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London E1 4DQ, UK. Electronic address: m.elbadawi@qmul.ac.uk.
  • Laura E McCoubrey
    UCL School of Pharmacy, University College London , London, UK.
  • Francesca K H Gavins
    Department of Pharmaceutics, UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK.
  • Jun J Ong
    Department of Pharmaceutics, UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK.
  • Alvaro Goyanes
    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 Compostela, 15782, Spain. Electronic address: a.goyanes@FabRx.co.uk.
  • Simon Gaisford
    UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK. Electronic address: s.gaisford@ucl.ac.uk.
  • Abdul W Basit
    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.