Issue 1, 2023

Liposome manufacturing under continuous flow conditions: towards a fully integrated set-up with in-line control of critical quality attributes

Abstract

Continuous flow manufacturing (CFM) has shown remarkable advantages in the industrial-scale production of drug-loaded nanomedicines, including mRNA-based COVID-19 vaccines. Thus far, CFM research in nanomedicine has mainly focused on the initial particle formation step, while post-formation production steps are hardly ever integrated. The opportunity to implement in-line quality control of critical quality attributes merits closer investigation. Here, we designed and tested a CFM setup for the manufacturing of liposomal nanomedicines that can potentially encompass all manufacturing steps in an end-to-end system. Our main aim was to elucidate the key composition and process parameters that affect the physicochemical characteristics of the liposomes. Total flow rate, lipid concentration and residence time of the liposomes in a high ethanol environment (i.e., above 20% v/v) emerged as critical parameters to tailor liposome size between 80 and 150 nm. After liposome formation, the pressure and the surface area of the filter in the ultrafiltration unit were critical parameters in the process of clearing the dispersion from residual ethanol. As a final step, we integrated in-line measurement of liposome size and residual ethanol content. Such in-line measurements allow for real-time monitoring and in-process adjustment of key composition and process parameters.

Graphical abstract: Liposome manufacturing under continuous flow conditions: towards a fully integrated set-up with in-line control of critical quality attributes

Supplementary files

Article information

Article type
Paper
Submitted
21 May 2022
Accepted
04 Nov 2022
First published
21 Nov 2022

Lab Chip, 2023,23, 182-194

Liposome manufacturing under continuous flow conditions: towards a fully integrated set-up with in-line control of critical quality attributes

M. Sheybanifard, L. P. B. Guerzoni, A. Omidinia-Anarkoli, L. De Laporte, J. Buyel, R. Besseling, M. Damen, A. Gerich, T. Lammers and J. M. Metselaar, Lab Chip, 2023, 23, 182 DOI: 10.1039/D2LC00463A

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