Advancing non-destructive analysis of 3D printed medicines

Pharmaceutical 3D printing (3DP) has attracted significant interest over the past decade for its ability to produce personalised medicines on demand. However, current quality control (QC) requirements for traditional large-scale pharmaceutical manufacturing are irreconcilable with the production offered by 3DP. The US Food and Drug Administration (FDA) and the UK Medicines and Healthcare Products Regulatory Agency (MHRA) have recently published documents supporting the implementation of 3DP for point-of-care (PoC) manufacturing along with regulatory hurdles.

Highlights

• 3D printing of medicines holds the potential to revolutionise therapeutic regimens and manufacture by offering tuneable, personalised, and on-demand manufacture at a small scale and at the PoC.
• Regulatory authorities have established expert working groups and have called for stakeholder feedback to develop new, additional regulatory guidelines concerning implementation and QC for decentralised and PoC manufacturing.
• Recent research has demonstrated the applications of non-destructive analytical techniques (herein PATs) as measures to assess the quality of the printed therapeutics. In particular, spectroscopic and chemical imaging techniques have been highlighted.
• Moreover, some research has demonstrated the feasibility of implementing process control monitoring tools to assure the quality of 3D printed drug products.

The importance of process analytical technology (PAT) and non-destructive analytical tools in translating pharmaceutical 3DP has experienced a surge in recognition. This review seeks to highlight the most recent research on non-destructive pharmaceutical 3DP analysis, while also proposing plausible QC systems that complement the pharmaceutical 3DP workflow. In closing, outstanding challenges in integrating these analytical tools into pharmaceutical 3DP workflows are discussed.

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Advancing non-destructive analysis of 3D printed medicines, Anna Kirstine Jørgensen, Jun Jie Ong, Maryam Parhizkar, Alvaro Goyanes, Abdul W. Basit, Open AccessPublished:April 24, 2023 DOI:https://doi.org/10.1016/j.tips.2023.03.006

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