Chemometrically assisted high-throughput methotrexate sensing strategy based on a pH-switchable optical nanosensor

MILAGROS MONTEMURRO; DAMIÁN URIARTE; HÉCTOR C. GOICOECHEA; SEBASTIÁN COLLINS; MARÍA JULIA CULZONI

Roma

Congreso; XVIII Chemometrics in Analytical Chemistry; 2022

Methotrexate (MTX) is an antineoplastic drug used in high doses for the treatment of different types of cancer. Given the need to carry out therapeutic monitoring in patients undergoing treatment with MTX to minimize the risk of toxicity [1], the development of analytical methods for its determination is of great importance. In this sense, nanotechnology, a multidisciplinary field that focuses on the study and application of materials at the nanoscale level, has emerged as a tool for the development of new analytical methodologies. During the last decade, there has been an accelerated increase in the study of ultra-small metallic nanoclusters (NCs) with luminescent properties, such as AuNCs and AgNCs.In this work, an analytical method for the quantitation of MTX is presented. The methodology is based on a pH gradient coupled with UV absorbance detection for second-order data generation, and AgNCs as signal enhancement agents. First, AgNCs were synthesized by a chemical reduction method in an alkaline medium at room temperature, as previously reported in the literature [2]. The synthesized AgNCs were characterized by UV-Vis spectroscopy, DLS, and TEM. The pH gradient for MTX sensing was generated using an Agilent 1260 LC instrument, equipped with a diode array detector. The carrier solution consisted in 1000-fold diluted AgNCs in 0.01 mol L-1 sodium citrate (pH = 9.0), while the sample buffer was 0.01 mol L-1 sodium citrate (pH = 4.0). The carrier solution was pumped through an 800 mm length and 0.5 mm i.d. flexible mixing coil flowing at 0.1 mL min−1, at 25 ºC. UV absorbance spectra were recorded in the range of 220-400 nm, every 2 nm, for 2.50 min. The data matrices registered for each sample were of size 375 × 91, for temporal and spectral modes, respectively. When the sample at acidic pH is injected, the generated pH gradient induces the dispersion of the AgNCs in the carrier solution and the consequent enhancement of the spectroscopic signal of MTX. Calibration and validation samples, containing MTX, and test samples, containing MTX and three potential interferences (dexamethasone, prednisolone, and vincristine), were analyzed. Data modeling was performed by extended MCR-ALS and U-PLS/RBL algorithms. The predictive ability of the model in the absence and the presence of uncalibrated components (second-order advantage) was assessed. Besides, to evaluate the advantages of the proposed methodology, the same samples were analyzed without including AgNCs in the carrier solution. The validation samples were successfully modeled by extended MCR-ALS. However, the results obtained for the test samples were not satisfactory, as the effect of the interferences on the signal could not be modeled due to high collinearity in both the spectral and concentration modes. On the contrary, these latter samples could be modeled by U-PLS/RBL. The results obtained are presented in Table 1. The developed method showed a significant improvement in both the predictive ability and analytical figures of merit, compared to the AgNCs-free system.