Abstract
Microfluidic liposome production presents a streamlined pathway for expediting the translation of liposomal formulations from the laboratory setting to clinical applications. Using this production method, resultant liposome characteristics can be tuned through the control of both the formulation parameters (including the lipids and solvents used) and production parameters (including the production speed and mixing ratio). Therefore, the aim of this study was to investigate the relationship between not only total flow rate (TFR), the fraction of the aqueous flow rate over the organic flow rate (flow rate ratio (FRR)), and the lipid concentration, but also the solvent selection, aqueous buffer, and production temperature. To achieve this, we used temperature, applying a design of experiment (DoE) combined with machine learning. This study demonstrated that liposome size and polydispersity were influenced by manipulation of not only the total flow rate and flow rate ratio but also through the lipids, lipid concentration, and solvent selection, such that liposome attributes can be in-process controlled, and all factors should be considered within a manufacturing process as impacting on liposome critical quality attributes.
Original language | English |
---|---|
Article number | 1159 |
Number of pages | 19 |
Journal | Pharmaceutics |
Volume | 16 |
Issue number | 9 |
DOIs | |
Publication status | Published - 1 Sept 2024 |
Keywords
- liposomes
- microfluidics
- design of experiments
- manufacturing
- machine learning
Fingerprint
Dive into the research topics of 'Can we simplify liposome manufacturing using a complex DoE approach?'. Together they form a unique fingerprint.Datasets
-
Data For: "Can We Simplify Liposome Manufacturing Using a Complex DoE Approach?"
Lindsay, S. (Creator) & Perrie, Y. (Supervisor), University of Strathclyde, 29 Aug 2024
DOI: 10.15129/f1aff828-eed2-4c52-93a9-b71df5fbee22
Dataset