Harnessing artificial intelligence for the next generation of 3D printed medicines.

Journal: Advanced drug delivery reviews
Published Date:

Abstract

Artificial intelligence (AI) is redefining how we exist in the world. In almost every sector of society, AI is performing tasks with super-human speed and intellect; from the prediction of stock market trends to driverless vehicles, diagnosis of disease, and robotic surgery. Despite this growing success, the pharmaceutical field is yet to truly harness AI. Development and manufacture of medicines remains largely in a 'one size fits all' paradigm, in which mass-produced, identical formulations are expected to meet individual patient needs. Recently, 3D printing (3DP) has illuminated a path for on-demand production of fully customisable medicines. Due to its flexibility, pharmaceutical 3DP presents innumerable options during formulation development that generally require expert navigation. Leveraging AI within pharmaceutical 3DP removes the need for human expertise, as optimal process parameters can be accurately predicted by machine learning. AI can also be incorporated into a pharmaceutical 3DP 'Internet of Things', moving the personalised production of medicines into an intelligent, streamlined, and autonomous pipeline. Supportive infrastructure, such as The Cloud and blockchain, will also play a vital role. Crucially, these technologies will expedite the use of pharmaceutical 3DP in clinical settings and drive the global movement towards personalised medicine and Industry 4.0.

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 Jie 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.