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Lipid nanoparticles (LNPs) for RNA and DNA delivery have attracted considerable attention for their ability to treat a broad range of diseases and to vectorize mRNA for COVID vaccines. LNPs are produced by mixing biomolecules and lipids, which self-assemble to form the desired structure. In this domain, microfluidics shows clear advantages: high mixing quality, low-stress conditions, and fast preparation. Studies of LNPs produced in micromixers have revealed, in certain ranges of flow rates, a degradation in performance in terms of size, monodispersity and encapsulation efficiency. In this study, we focus on the ring micromixer, which is well adapted to high throughput. We reveal three regimes, side-by-side, transitional and highly mixed, that control the mixing performance of the device. Furthermore, using cryo-TEM and biochemical analysis, we show that the mixing performances are strongly correlated to the characteristics of the LNPs we produce. We emphasize the importance of the flow-rate ratio and propose a physical criterion based on the onset of temporal instabilities for producing LNPs with optimal characteristics in terms of geometry, monodispersity and encapsulation yield. These criteria are generally applicable. [ABSTRACT FROM AUTHOR]

Purpose: To predict the crystallization time of amorphous solid dispersions by controlling the combined effect of temperature and moisture content. Methods: The authors exposed amorphous samples of spray-dried API and Hydroxypropylmethylcellulose Phtalate to various temperature and humidity conditions below and above the glass transition temperature (Tg) until crystallization of the API was observed. The crystallization of API was detected by XRPD, while the T and the water absorption by the amorphous dispersion are quantified by mDSC and water sorption analysis. Results: Extrapolation of the data obtained at a temperature above T to conditions below T gives only a qualitative trend. By contrast, in conditions below T the logarithm of onset of crystallization time was shown to vary linearly with the T /T ratio. A statistical analysis shows that the data obtained in the highest temperature/humidity conditions, for which the onset of crystallization is below 3 months, can be extrapolated over 15 months. Conclusions: The proposed methodology can be used as a stress program to predict long-term stability from a relatively short observation period and to design appropriate temperature and humidity conditions for long-term storage to prevent crystallization. [ABSTRACT FROM AUTHOR]