Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/29059
Title: A case study on decentralized manufacturing of 3D printed medicines
Authors: Seoane-Viaño, I
Xu, X
Ong, JJ
Teyeb, A
Gaisford, S
Campos-Álvarez, A
Stulz, A
Marcuta, C
Kraschew, L
Mohr, W
Basit, AW
Goyanes, A
Keywords: Real-time release testing;Direct powder extrusion of personalized pharmaceuticals;Process analytical technologies;Decentralised and distributed fabrication of formulations;Additive manufacturing of drug products and drug delivery systems;Digital healthcare and industry 4.0;Three-dimensional printing using M3DIMAKER
Issue Date: 7-Jun-2023
Publisher: Elsevier
Citation: Seoane-Viaño, I. et al. (2023). ‘A case study on decentralized manufacturing of 3D printed medicines’, International Journal of Pharmaceutics: X. Vol.5., pp.1-9. doi: https://doi.org/10.1016/j.ijpx.2023.100184.
Abstract: Pharmaceutical 3D printing (3DP) is one of the emerging enabling technologies of personalised medicines as it affords the ability to fabricate highly versatile dosage forms. In the past 2 years, national medicines regulatory authorities have held consultations with external stakeholders to adapt regulatory frameworks to embrace point-of-care manufacturing. The proposed concept of decentralized manufacturing (DM) involves the provision of feedstock intermediates (pharma-inks) prepared by pharmaceutical companies to DM sites for manufacturing into the final medicine. In this study, we examine the feasibility of this model, with respect to both manufacturing and quality control. Efavirenz-loaded granulates (0–35%w/w) were produced by a manufacturing partner and shipped to a 3DP site in a different country. Direct powder extrusion (DPE) 3DP was subsequently used to prepare printlets (3D printed tablets), with mass ranging 266–371 mg. All printlets released more than 80% drug load within the first 60 min of the in vitro drug release test. An in-line near-infrared spectroscopy system was used as a process analytical technology (PAT) to quantify the printlets' drug load. Calibration models were developed using partial least squares regression, which showed excellent linearity (R2 = 0.9833) and accuracy (RMSE = 1.0662). Overall, this work is the first to report the use of an in-line NIR system to perform real-time analysis of printlets prepared using pharma-inks produced by a pharmaceutical company. By demonstrating the feasibility of the proposed distribution model through this proof-of-concept study, this work paves the way for investigation of further PAT tools for quality control in 3DP point-of-care manufacturing.
URI: http://bura.brunel.ac.uk/handle/2438/29059
DOI: http://dx.doi.org/10.1016/j.ijpx.2023.100184
Other Identifiers: Article No.: 100184
ORCiD: Ahmed Teyeb https://orcid.org/0000-0003-0300-1845
ORCiD: Abdul Basit https://orcid.org/0000-0002-5368-6603
ORCiD: Alvaro Goyanes https://orcid.org/0000-0002-3378-6797
ORCiD: Iria Seoane-Viaño https://orcid.org/0000-0003-3910-2074
ORCiD: Xiaoyan Xu https://orcid.org/0000-0002-2218-6278
ORCiD: Simon Gaisford https://orcid.org/0000-0003-1000-3208
ORCiD: Jun Jie Ong https://orcid.org/0000-0001-9341-9561
Appears in Collections:Brunel Innovation Centre

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