Monitoring drug nanocarriers in human blood by near-infrared fluorescence correlation spectroscopy

Abstract

Nanocarrier-based drug delivery is a promising therapeutic approach that offers unique possibilities for the treatment of various diseases. However, inside the blood stream, nanocarriers' properties may change significantly due to interactions with proteins, aggregation, decomposition or premature loss of cargo. Thus, a method for precise, in situ characterization of drug nanocarriers in blood is needed. Here we show how the fluorescence correlation spectroscopy that is a well-established method for measuring the size, loading efficiency and stability of drug nanocarriers in aqueous solutions can be used to directly characterize drug nanocarriers in flowing blood. As the blood is not transparent for visible light and densely crowded with cells, we label the nanocarriers or their cargo with near-infrared fluorescent dyes and fit the experimental autocorrelation functions with an analytical model accounting for the presence of blood cells. The developed methodology contributes towards quantitative understanding of the in vivo behavior of nanocarrier-based therapeutics.

Fig. 1

NIR-FCS experiments in aqueous solutions. a Schematic representation of the NIR-FCS setup. It is based on customized commercial equipment, modified so that both the excitation laser wavelength and the detected fluorescence are in the NIR spectral range. See Methods for details. b Fluorescence intensity time trace recorded for CB1 and c the corresponding experimental autocorrelation curve (symbols). The red line represents a fit with Eq. (3)

Fig. 2

Overview of the NIR-FCS experiments and data analysis in flowing blood. a Monitoring NIR fluorescent species in flowing blood. Blood containing CB1 (8 nM) was pumped through a flow channel at a defined velocity of 50 µL h⁻¹. The FCS observation volume was consequently either free (schematics 1) or occupied (schematics 2) by a blood cell. Correspondingly, the fluorescence intensity time trace revealed high (1) and low (2) intensity time segments. b The experimental autocorrelation curve (squares) was fitted (line) with analytical model, Eq. (3), combining standard and inverse FCS thus taking into account contributions of fluorescent species and blood cells, respectively. c The information extracted from the fit in panel (c) was used to subtract the cells’ contribution and obtain an autocorrelation curve (squares) resembling that of a standard FCS experiment (Eq. ( 6)). A fit with Eq. (1) (line) yields diffusion properties of the fluorescent species

Fig. 3

NIR-FCS measurement of IRDye®CW800-DBCO in flowing blood. a Autocorrelation curve fitted with Eq. (2) comprising contributions from fluorescent dyes and blood cells. b Contribution from the blood cells was subtracted (Eq. (6)) from the autocorrelation curve of IRDye®CW800-DBCO in blood (red). For comparison, the autocorrelation curve of IRDye®CW800-DBCO in water (black) is also shown

Fig. 4

NIR-FCS studies of the loading stability of core-crosslinked micelle nanocarriers in blood. Normalized autocorrelation curves (symbols) and the corresponding fits (lines) are shown for core-crosslinked micelles that were either covalently (M1, blue color) or noncovalently (M2, green color) loaded with IRDye®800CW. a Measurements in water. The dye is mainly loaded to the core-crosslinked micelles and only a small fraction of free dye was detected for both systems. b Measurements in the blood flow (velocity of 50 µL h⁻¹) upon incubation with blood for 30 h (at 4 °C). The dye is fully released from M2, but still loaded to M1