Elbadawi, M;
McCoubrey, LE;
Gavins, FKH;
Jie Ong, J;
Goyanes, A;
Gaisford, S;
Basit, AW;
(2021)
Harnessing Artificial Intelligence for the Next Generation of 3D Printed Medicines.
Advanced Drug Delivery Reviews
10.1016/j.addr.2021.05.015.
(In press).
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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.
| Type: | Article |
|---|---|
| Title: | Harnessing Artificial Intelligence for the Next Generation of 3D Printed Medicines |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.addr.2021.05.015 |
| Publisher version: | https://doi.org/10.1016/j.addr.2021.05.015 |
| Language: | English |
| Additional information: | © 2021 The Authors. Published by Elsevier B.V. under a Creative Commons license (https://creativecommons.org/licenses/by/4.0/). |
| Keywords: | Additive Manufacturing; Digital pharmaceutics and pharmaceutical sciences; Digital therapeutics and healthcare; Drug product design and development; Computer aided design of printlets; Computational modeling and finite element analysis; Fabricating gastrointestinal drug delivery systems and dosage forms; Personalized pharmaceuticals and medical devices; Mass customization and machine learning; Falsified and counterfeit oral pharmaceutical products |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > UCL School of Pharmacy UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > UCL School of Pharmacy > Pharmaceutics |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10128431 |
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