A review of bioanalytical methods for the therapeutic drug monitoring of ß-lactam antibiotics in critically ill patients: Evaluation of the approaches used to develop and validate quality attributes.

Due to their broad spectrum of activity and wide therapeutic index, ß-lactam antibiotics (ß-LA) are commonly used to treat severe sepsis in critically ill patients in intensive care units. This group of patients experiences important physiological changes that alter their pharmacokinetics, and thus, therapeutic drug monitoring (TDM) of ß-LA is increasingly used to improve personalized medicine by optimizing doses and minimizing the emergence of drug-resistant bacterial strains. Reliable and high-quality bioanalytical methods are needed in clinical practice. This review principally focuses on evaluating the development and validation of state-of-the-art analytical methods for the determination of ß-LA in biological samples from critically ill patients. When mentioned, method optimization was performed using a univariate strategy, the currently used analytical quality by design (AQbD) tools were not used for method optimization in any study. Liquid chromatography methods coupled with UV or MS detectors were the main techniques used, and the pretreatment procedures were still considerably complex for a hospital laboratory setting. Given the poly-medication status of many patients, the selectivity of the procedure must be specifically analyzed to avoid possible interference from other drugs. However, this aspect has been assessed in very few studies. We also identified inconsistencies in analytical ranges selected in many published methods, since they are not centered in the therapeutic concentrations of the antibiotics. The precision, accuracy and linearity were mainly evaluated using diverse bioanalytical validation guidelines; however, more detailed information could have been provided about the calibration strategy used for routine laboratory assessments.

Enhanced MCR-ALS modeling of HPLC with fast scan fluorimetric detection second-order data for quantitation of metabolic disorder marker pteridines in urine.

This work presents the development of a liquid chromatographic method based on modeling entire fast scan fluorimetric detection second-order data with the multivariate curve resolution alternating least squares algorithm, for the simultaneous determination of five marker pteridines in urine samples. The modeling strategy involves the building of a single MCR-ALS model composed of matrices augmented in the spectral mode, i.e. time profiles remain invariant while spectra may change from sample to sample. This approach allowed us to separate and determine the whole analytes at once. The developed approach enabled us to determine five of the most important metabolic disorder marker pteridines: biopterin, neopterin, isoxanthopterin, pterin and xanthopterin, three of them presenting emission spectra with the same emission wavelength maxima. In addition, some of these analytes present overlapped time profiles. As a consequence of using the entire data sets, a considerable reduction of the data processing experimental time can be achieved. Results are compared with a previous strategy in which data were split in five different regions, and information about the figures of merit of the new strategy compared with the previously reported strategy is reported.

Determination of marker pteridines in urine by HPLC with fluorimetric detection and second-order multivariate calibration using MCR-ALS.

A liquid chromatographic method has been developed, in combination with the multivariate curve resolution-alternating least squares algorithm (MCR-ALS), for the simultaneous determination of marker pteridines in urine samples. A central composite design has been applied to optimize the factors influencing the separation (buffer concentration, buffer pH, flow rate, oven temperature, mobile-phase composition). A set of 15 calibration samples were randomly prepared, in a concentration range of 0.5-10.5 ng mL(-1) for neopterin, biopterin, and pterin; 4.0-8.0 ng mL(-1) for xanthopterin; and 0.5-4.5 ng mL(-1) for isoxanthopterin. The validation was carried out with fortified urine samples from healthy adults. The optimized conditions were a mobile-phase composition of 10 mM citric buffer at pH 5.44 and acetonitrile (94.5/5.5, v/v), a flow rate of 1.0 mL min(-1), and an oven temperature of 25 °C. The detection system consisted of a fast-scanning spectrofluorimeter, which allows obtaining of second-order data matrices containing the fluorescence intensity as a function of retention time and emission wavelength. In this work, MCR-ALS was used to cope with coeluting interferences, on account of the second-order advantage inherent to this algorithm which, in addition, is able to handle data sets deviating from trilinearity, like the high-performance liquid chromatography data analyzed in the present report. The developed approach enabled us to determine five pteridines, some of them with overlapped profiles, reducing the experimental time and reagent consumption. Ratio values for pteridines/creatinine in urine, for infected children with different pathologies, are reported in this work.

Solving matrix-effects exploiting the second order advantage in the resolution and determination of eight tetracycline antibiotics in effluent wastewater by modelling liquid chromatography data with multivariate curve resolution-alternating least squares and unfolded-partial least squares followed by residual bilinearization algorithms I. Effect of signal pre-treatment.

The effect of piecewise direct standardization (PDS) and baseline correction approaches was evaluated in the performance of multivariate curve resolution (MCR-ALS) algorithm for the resolution of three-way data sets from liquid chromatography with diode-array detection (LC-DAD). First, eight tetracyclines (tetracycline, oxytetracycline, chlorotetracycline, demeclocycline, methacycline, doxycycline, meclocycline and minocycline) were isolated from 250 mL effluent wastewater samples by solid-phase extraction (SPE) with Oasis MAX 500 mg/6 mL cartridges and then separated on an Aquasil C18 150 mm x 4.6mm (5 microm particle size) column by LC and detected by DAD. Previous experiments, carried out with Milli-Q water samples, showed a considerable loss of the most polar analytes (minocycline, oxitetracycline and tetracycline) due to breakthrough. PDS was applied to overcome this important drawback. Conversion of chromatograms obtained from standards prepared in solvent was performed obtaining a high correlation with those corresponding to the real situation (r2 = 0.98). Although the enrichment and clean-up steps were carefully optimized, the sample matrix caused a large baseline drift, and also additive interferences were present at the retention times of the analytes. These problems were solved with the baseline correction method proposed by Eilers. MCR-ALS was applied to the corrected and uncorrected three-way data sets to obtain spectral and chromatographic profiles of each tetracycline, as well as those corresponding to the co-eluting interferences. The complexity of the calibration model built from uncorrected data sets was higher, as expected, and the quality of the spectral and chromatographic profiles was worse.

Solving matrix effects exploiting the second-order advantage in the resolution and determination of eight tetracycline antibiotics in effluent wastewater by modelling liquid chromatography data with multivariate curve resolution-alternating least squares and unfolded-partial least squares followed by residual bilinearization algorithms II. Prediction and figures of merit.

A new powerful algorithm (unfolded-partial least squares followed by residual bilinearization (U-PLS/RBL)) was applied for first time on second-order liquid chromatography with diode array detection (LC-DAD) data and compared with a well-known established method (multivariate curve resolution-alternating least squares (MCR-ALS)) for the simultaneous determination of eight tetracyclines (tetracycline, oxytetracycline, meclocycline, minocycline, metacycline, chlortetracycline, demeclocycline and doxycycline) in wastewaters. Tetracyclines were pre-concentrated using Oasis Max C18 cartridges and then separated on a Thermo Aquasil C18 (150 mm x 4.6mm, 5 microm) column. The whole method was validated using Milli-Q water samples and both univariate and multivariate analytical figures of merit were obtained. Additionally, two data pre-treatment were applied (baseline correction and piecewise direct standardization), which allowed to correct the effect of breakthrough and to reduce the total interferences retained after pre-concentration of wastewaters. The results showed that the eight tetracycline antibiotics can be successfully determined in wastewaters, the drawbacks due to matrix interferences being adequately handled and overcome by using U-PSL/RBL.