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Design and development of a biorelevant simulated human lung fluid

Biorelevant fluids are required to enable meaningful in vitro experimental determinations of the biopharmaceutical properties of inhaled medicines, e.g. drug solubility, particle dissolution, cellular uptake. Our aim was to develop a biorelevant simulated lung fluid (SLF) with a well-defined composi...

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Detalles Bibliográficos
Autores principales: Hassoun, Mireille, Royall, Paul G., Parry, Mark, Harvey, Richard D., Forbes, Ben
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6156579/
https://www.ncbi.nlm.nih.gov/pubmed/30283501
http://dx.doi.org/10.1016/j.jddst.2018.08.006
Descripción
Sumario:Biorelevant fluids are required to enable meaningful in vitro experimental determinations of the biopharmaceutical properties of inhaled medicines, e.g. drug solubility, particle dissolution, cellular uptake. Our aim was to develop a biorelevant simulated lung fluid (SLF) with a well-defined composition and evidence-based directions for use. The SLF contained dipalmitoylphosphotidylcholine, dipalmitoylphosphatidylglycerol, cholesterol, albumin, IgG, transferrin and antioxidants. Freshly made SLF had pH 7.2, viscosity 1.138 × 10(−3) Pa s, conductivity 14.5 mS/m, surface tension 54.9 mN/m and density 0.999 g/cm(3). Colour, surface tension and conductivity were the most sensitive indicators of product deterioration. The simulant was stable for 24 h and 48 h at 37 °C and 21 °C, respectively, (in-use stability) and for 14 days when stored in a refrigerator (storage stability). To extend stability, the SLF was vacuum freeze-dried in batches to produce lyophilised powder that can be reconstituted readily when needed at the point of use. In conclusion, we have reported the composition and manufacture of a biorelevant, synthetic SLF, provided a detailed physico-chemical characterisation and recommendations for how to store and use a product that can be used to generate experimental data to provide inputs to computational models that predict drug bioavailability in the lungs.