| Literature DB >> 34238624 |
Moe Elbadawi1, Laura E McCoubrey1, Francesca K H Gavins1, Jun J Ong1, Alvaro Goyanes2, Simon Gaisford3, Abdul W Basit4.
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.Entities:
Keywords: 3D Printed drug products and formulations; Industry 4.0 and digital health; additive manufacturing; biomedical engineering and pharmaceutical sciences; personalized oral drug delivery systems and medical devices; translational pharmaceutics
Year: 2021 PMID: 34238624 DOI: 10.1016/j.tips.2021.06.002
Source DB: PubMed Journal: Trends Pharmacol Sci ISSN: 0165-6147 Impact factor: 14.819