Design of Experiments Leads to Scalable Analgesic Near-Infrared Fluorescent Coconut Nanoemulsions

Abstract

Background: Pain is a complex phenomenon characterized by unpleasant experiences with profound heterogeneity influenced by biological, psychological, and social factors. According to the National Health Interview Survey, 50.2 million U.S. adults (20.5%) experience pain on most days, with the annual cost of prescription medication for pain reaching approximately USD 17.8 billion. Theranostic pain nanomedicine therefore emerges as an attractive analgesic strategy with the potential for increased efficacy, reduced side-effects, and treatment personalization. Theranostic nanomedicine combines drug delivery and diagnostic features, allowing for real-time monitoring of analgesic efficacy in vivo using molecular imaging. However, clinical translation of these nanomedicines are challenging due to complex manufacturing methodologies, lack of standardized quality control, and potentially high costs. Quality by Design (QbD) can navigate these challenges and lead to the development of an optimal pain nanomedicine. Our lab previously reported a macrophage-targeted perfluorocarbon nanoemulsion (PFC NE) that demonstrated analgesic efficacy across multiple rodent pain models in both sexes. Here, we report PFC-free, biphasic nanoemulsions formulated with a biocompatible and non-immunogenic plant-based coconut oil loaded with a COX-2 inhibitor and a clinical-grade, indocyanine green (ICG) near-infrared fluorescent (NIRF) dye for parenteral theranostic analgesic nanomedicine. Methods: Critical process parameters and material attributes were identified through the FMECA (Failure, Modes, Effects, and Criticality Analysis) method and optimized using a 3 × 2 full-factorial design of experiments. We investigated the impact of the oil-to-surfactant ratio (w/w) with three different surfactant systems on the colloidal properties of NE. Small-scale (100 mL) batches were manufactured using sonication and microfluidization, and the final formulation was scaled up to 500 mL with microfluidization. The colloidal stability of NE was assessed using dynamic light scattering (DLS) and drug quantification was conducted through reverse-phase HPLC. An in vitro drug release study was conducted using the dialysis bag method, accompanied by HPLC quantification. The formulation was further evaluated for cell viability, cellular uptake, and COX-2 inhibition in the RAW 264.7 macrophage cell line. Results: Nanoemulsion droplet size increased with a higher oil-to-surfactant ratio (w/w) but was no significant impact by the type of surfactant system used. Thermal cycling and serum stability studies confirmed NE colloidal stability upon exposure to high and low temperatures and biological fluids. We also demonstrated the necessity of a solubilizer for long-term fluorescence stability of ICG. The nanoemulsion showed no cellular toxicity and effectively inhibited PGE2 in activated macrophages. Conclusions: To our knowledge, this is the first instance of a celecoxib-loaded theranostic platform developed using a plant-derived hydrocarbon oil, applying the QbD approach that demonstrated COX-2 inhibition.

Keywords: Quality by Design (QbD); celecoxib; coconut oil; macrophage; nanoemulsion; pain.

Figure 1

Assessment of manufacturing possibility, formulation compatibility, and process parameters. (A) Droplet size distribution. (B) Polydispersity index (PDI) of large-scale (500 mL) trial in M110P microfluidizer with coconut oil and F127/CrEl surfactant system. (C) Comparative droplet size of two batches of nanoemulsion with and without solubilizer (Miglyol 812). (D) Comparative droplet size of two batches of nanoemulsion manufactured with sonication and microfluidization only. Comparative droplet size of two batches of nanoemulsion processed at (E) 80 psi and 90 psi processing pressure and (F) 15 s and 30 s of sonication. All data in Figure 1 are from the manufacturing trials during screening and are given as n = 1.

Figure 2

Risk assessment. (A) Scoring the risk factors for severity, frequency of occurrence, and detectability. High-risk factor distribution in (B) unit operation and (C) formulation.

Figure 3

Design of experiment (DoE). (A) Color map on correlations among the factors showing the confounding in the experimental design. (B) 2 × 3 level, 2-factor full factorial design with 2 center points. (C) Listed responses will be checked for the 8 runs of nanoemulsion.

Figure 4

Design of experiments results: (A) bivariate fit of day 7 size by O/S ratio with predictive equation for day 7 droplet size; (B) residual vs. predicted plot of day 7 droplet size data; (C) one-way analysis of day 7 size by surfactant system; (D) actual vs. predicted day 7 size plot with interaction terms (surfactant system * O/S ratio); (E) effect summary; (F) actual vs. predicted day 7 size plot without interaction terms (surfactant system * O/S ratio).

Figure 5

Droplet size analysis of nanoemulsion under the design of experiment. Nanoemulsion with the same O/S ratio (w/w) but different surfactant system. (A) O/S ratio 5, (B) O/S ratio 6.5, (C) O/S ratio 8. Nanoemulsion with the same surfactant system but different O/S ratio: (D) surfactant system L1, (E) surfactant system L2, (F) surfactant system L3. The data are given as mean ± SD (n = 3). One-way ANOVA with multiple comparison test, unpaired t-test, ns not significant, * p < 0.05, ** p < 0.005, *** p < 0.0005, **** p < 0.0001.

Figure 6

Colloidal and fluorescence stability, morphology and scale-up of DF NE and CXB NE. Twelve months storage stability in terms of the following: (A) size distribution; (B) fluorescence intensity; (C) stability study after thermal cycling between 4 °C and 50 °C for 8 cycles; (D) stability after 72 h of incubation in serum and serum-free medium; (E) comparison of droplet size between small-scale (100 mL) and large-scale (500 mL) batch; (F) comparison of droplet size between DF NE and CXB NE; (G) comparison of fluorescence intensity between DF NE and CXB NE; (H) comparison of fluorescence stability of batch 1 (without Transcutol) and batch 2 (with Transcutol); (I) representative transmission electron microscopic image of CXB NE. The data are given as mean ± SD (n = 3). Two-way ANOVA with Šídák’s multiple comparison, unpaired t-test, ns not significant.

Figure 7

HPLC quantification and in vitro drug release study: (A) CXB calibration curve with triplicate data points at each concentration; (B) % CXB encapsulation in DoE runs, and large-scale nanoemulsion, quantified using RP-HPLC; (C) cumulative percentage of CXB release from nanoemulsion and free-CXB solution in release media containing 1X PBS: methanol (4:1); (D) cumulative amount of CXB release in µg/mL from nanoemulsion and free-CXB solution. The data are given as mean ± SD (n = 3). Two-way ANOVA with Šídák’s multiple comparison, **** p < 0.0001.

Figure 8

Cell culture experiments. In vitro cell viability, PGE2 release inhibition, and cellular uptake in RAW 264.7 macrophages. Macrophages were exposed to (A) CXB NE and DF NE. (B) CXB in DMSO and CXB NE for 24 h. (A,B) Assay performed using ATP-based CellTiter Glo 2.0. Data represents average ± SD, n= 6. (C) % control of PGE2 release inhibition from LPS-activated macrophages exposed to CXB NE and Free CXB at different concentrations. Data represents an average ± SD, n = 3. (D) Representative overlays of images from the DAPI (blue, nuclei) and ICG channels (purple) of RAW 264.7 macrophages treated with nanoemulsion (ICG-labeled nanoemulsion, purple). Images were taken on the Keyence microscope at 40X magnification.