Mass production and size control of lipid-polymer hybrid nanoparticles through controlled microvortices - PubMed (original) (raw)

. 2012 Jul 11;12(7):3587-91.

doi: 10.1021/nl301253v. Epub 2012 Jun 20.

Affiliations

Mass production and size control of lipid-polymer hybrid nanoparticles through controlled microvortices

Yongtae Kim et al. Nano Lett. 2012.

Erratum in

Abstract

Lipid-polymer hybrid (LPH) nanoparticles can deliver a wide range of therapeutic compounds in a controlled manner. LPH nanoparticle syntheses using microfluidics improve the mixing process but are restricted by a low throughput. In this study, we present a pattern-tunable microvortex platform that allows mass production and size control of LPH nanoparticles with superior reproducibility and homogeneity. We demonstrate that by varying flow rates (i.e., Reynolds number (30-150)) we can control the nanoparticle size (30-170 nm) with high productivity (∼3 g/hour) and low polydispersity (∼0.1). Our approach may contribute to efficient development and optimization of a wide range of multicomponent nanoparticles for medical imaging and drug delivery.

PubMed Disclaimer

Conflict of interest statement

Conflict of Interest Disclosure: In compliance with the Brigham and Women's Hospital and Harvard Medical School institutional guidelines, O.C.F. discloses his financial interest in BIND Biosciences and Selecta Biosciences, two biotechnology companies developing nanoparticle technologies for medical applications. BIND and Selecta did not support the aforementioned research, and currently these companies have no rights to any technology or intellectual property developed as part of this research.

Figures

Figure 1

Figure 1. Mass production and size control of lipid-polymer hybrid (LPH) nanoparticles through controlled microvortices

(a, b) Schematic (a) and cross section views (b) of a simple, single-layer, and three-inlet microfluidic platform generating two symmetric microvortices and a 3D focusing pattern. (c) Illustrative structure of LPH nanoparticles synthesized in the microfluidic platform. (d) Microvortex nanoparticle synthesis shows 1000 times higher productivity than PLGA-PEG synthesis using diffusive mixing in a microfluidic flow-focusing pattern at a flow rate of 10 μL/min. Our microvortex approach enables 200 times faster production than previous lipid-polymeric nanoparticle synthesis using convective mixing in a Tesla Mixer. For comparison, the productivity (g/hour) represents the amount of PLGA (5 mg/mL) included in the produced nanoparticles, which was varied by altering the Reynolds number (Figure S3). After removing the free lipids by the purification process, the PLGA is assumed to be essentially 100% effective as previously reported., (e) Average distribution of the nanoparticles produced through the controlled microvortices. The average sizes are 55 nm (Re=150) and 81 nm (Re=75). The Reynolds number was computed by the microfluidic dimensions and flow rate used in the experiment (Figure S1). (f, g) Transmission electron microscopy (TEM) images that demonstrate the synthesized nanoparticles with two distinct sizes for Re=150 (f) and Re=75 (g) with only changes of flow rates (i.e. Reynolds number (Re)). The scale bars are both 100 nm.

Figure 2

Figure 2. Size-controllable nanoparticle syntheses with variation of the Reynolds number in controlled microvortex patterns

(a) Nanoparticle size map controlled by varying Reynolds number with given PLGA-to-lipid weight ratios. The size represents the average value in the monodisperse distribution that occupies more than 85% of the overall volume of the produced nanoparticles (Figure S4). (b) Nanoparticle size manipulated by controlled microvortex patterns that vary the polymer-lipid mixing times. Error bars are standard deviations of different nanoparticle batches (n=5). (c) Microvortex patterns predicted by the computational fluid dynamics simulations and visualized by microscopic images (Figure S5; for methods see Supporting Information). The patterns exhibited very good agreement between simulations and images. In simulation, the color map represents mass fraction of the polymer and lipid streams. In visualization, the central stream has a 10% black ink diluted with deionized water. The scale bar is 200 μm.

Figure 3

Figure 3. Nanoparticle size variations to controlled microvortex patterns

(a) Effect of flow rate ratios (1:5, 1:10, and 1:20) of [PLGA stream] to [outer lipid streams] on nanoparticle size with respect to Reynolds number (30, 75, and 150) and PLGA-to-lipid ratios (10, 25, and 50). (b) Effect of PLGA-to-lipid ratios (10, 25, and 50) on nanoparticle size with respect to Reynolds number (30, 75, and 150) and flow rate ratios (1:5, 1:10, and 1:20). Error bars are standard deviations of different nanoparticle batches (n=5). (c) Controllable microvortices in the xy and yz planes. In a flow rate ratio of 1:5, microvortex patterns were not well developed due to relatively higher portion of the central stream in the channel while the vortices were well developed in flow rate ratios of 1:10 and 1:20. Increasing the Reynolds number resulted in clearer microvortex formation while vortex patterns were undeveloped at Re=3 (Figure S5).

Figure 4

Figure 4. Comparison of nanoparticle size and distribution using two different approaches: bulk synthesis using conventional nanoprecipitation and microvortex mass production (Re=150)) with given PLGA-to-lipid weight rations of 10, 25, and 50

(a) Nanoparticle size. (b) Polydispersity of the average distribution. Error bars are both standard deviations of different batches (n=5). (c, d) Nanoparticle size distributions: (c) bulk and (d) microvortex. The solid, dotted, and dashed lines represent the PLGA-to-lipid weight ratios of 10, 25, and 50, respectively.

References

    1. Schubert S, Delaney JT, Schubert US. Soft Matter. 2011;7(5):1581–1588.
    1. Chan JM, Valencia PM, Zhang L, Langer R, Farokhzad OC. Methods in molecular biology (Clifton, NJ) 2010;624:163–75. - PubMed
    1. Shi JJ, Xiao ZY, Kamaly N, Farokhzad OC. Accounts of Chemical Research. 2011;44(10):1123–1134. - PubMed
    1. Zhang L, Chan JM, Gu FX, Rhee JW, Wang AZ, Radovic-Moreno AF, Alexis F, Langer R, Farokhzad OC. Acs Nano. 2008;2(8):1696–1702. - PMC - PubMed
    1. Chan JM, Zhang L, Yuet KP, Liao G, Rhee JW, Langer R, Farokhzad OC. Biomaterials. 2009;30(8):1627–34. - PubMed

Publication types

MeSH terms

Substances

Grants and funding

LinkOut - more resources