Le pubblicazioni dei componenti del gruppo di ricerca.
2026
Diego Caccavo; Raffaella De Piano; Francesca Landi; Gaetano Lamberti; Anna Angela Barba
Coaxial Jet Mixing for Pharmaceutical Nanocarrier Production: Experimental Analysis and Mechanistic Modeling Journal Article
In: Pharmaceutics, vol. 18, iss. 4, 2026.
Abstract | Links | BibTeX | Tags: antisolvent precipitation, coaxial jet mixer, computational fluid dynamics, modelling, nanoliposomes, population balance
@article{Caccavo2026d,
title = {Coaxial Jet Mixing for Pharmaceutical Nanocarrier Production: Experimental Analysis and Mechanistic Modeling},
author = {Diego Caccavo and Raffaella De Piano and Francesca Landi and Gaetano Lamberti and Anna Angela Barba},
url = {https://www.mdpi.com/1999-4923/18/4/507/pdf?version=1776679118},
doi = { 10.3390/pharmaceutics18040507 },
year = {2026},
date = {2026-04-20},
journal = { Pharmaceutics},
volume = {18},
issue = {4},
abstract = {This study addresses the need for scalable and predictive strategies linking mixing conditions to nanocarrier properties by developing and analyzing a coaxial jet antisolvent process for the continuous production of pharmaceutical nanocarriers. Methods: A single experimental platform was used to generate both curcumin-based nanoparticles and nanoliposomes, enabling direct comparison of how mixing regime and formulation variables influence product characteristics. Results: Fluid-dynamic behavior was first characterized using tracer and micromixing experiments, revealing a strong dependence of mixing time on flow conditions, with characteristic mixing times decreasing from \>1000 ms under laminar conditions to approximately 10\textendash30 ms in turbulent regimes. Nanoparticles and liposomes obtained under optimized conditions exhibited mean sizes in the range of 120\textendash250 nm, with polydispersity indices typically below 0.2 under optimized turbulent conditions. To rationalize these observations, a computational framework was implemented, combining Reynolds-averaged computational fluid dynamics with a population balance formulation solved by the method of moments. The model provided spatially resolved insight into solvent exchange, supersaturation development, and nucleation\textendashgrowth dynamics, showing good agreement with experimental trends and capturing the effect of mixing conditions on particle size across different regimes. Conclusions: Although simplified, the modeling approach establishes the basis for future extensions toward full population-balance distribution simulations capable of predicting complete particle size distributions, highlighting the ability of the coaxial jet mixer to control supersaturation and particle formation through tunable hydrodynamic conditions. This capability makes the system particularly attractive compared to conventional batch or less controllable mixing technologies, enabling a more rational and scalable design of pharmaceutical nanocarriers, with good encapsulation performance as discussed in the main text.},
keywords = {antisolvent precipitation, coaxial jet mixer, computational fluid dynamics, modelling, nanoliposomes, population balance},
pubstate = {published},
tppubtype = {article}
}
This study addresses the need for scalable and predictive strategies linking mixing conditions to nanocarrier properties by developing and analyzing a coaxial jet antisolvent process for the continuous production of pharmaceutical nanocarriers. Methods: A single experimental platform was used to generate both curcumin-based nanoparticles and nanoliposomes, enabling direct comparison of how mixing regime and formulation variables influence product characteristics. Results: Fluid-dynamic behavior was first characterized using tracer and micromixing experiments, revealing a strong dependence of mixing time on flow conditions, with characteristic mixing times decreasing from >1000 ms under laminar conditions to approximately 10–30 ms in turbulent regimes. Nanoparticles and liposomes obtained under optimized conditions exhibited mean sizes in the range of 120–250 nm, with polydispersity indices typically below 0.2 under optimized turbulent conditions. To rationalize these observations, a computational framework was implemented, combining Reynolds-averaged computational fluid dynamics with a population balance formulation solved by the method of moments. The model provided spatially resolved insight into solvent exchange, supersaturation development, and nucleation–growth dynamics, showing good agreement with experimental trends and capturing the effect of mixing conditions on particle size across different regimes. Conclusions: Although simplified, the modeling approach establishes the basis for future extensions toward full population-balance distribution simulations capable of predicting complete particle size distributions, highlighting the ability of the coaxial jet mixer to control supersaturation and particle formation through tunable hydrodynamic conditions. This capability makes the system particularly attractive compared to conventional batch or less controllable mixing technologies, enabling a more rational and scalable design of pharmaceutical nanocarriers, with good encapsulation performance as discussed in the main text.