Guilherme L. Alexandrino

NIR imaging spectroscopy for quantification of constituents in polymers thin films loaded with paracetamol

Thin films loaded with the drug paracetamol were produced from polymer blends formed by hydroxypropylmethylcellulose (HPMC), polyvinylpyrrolidone (PVP) and polyethyleneglycol (PEG), at various mass ratios of polymers and drug defined by a D-optimal experimental design. NIR hyperspectral images were obtained from each thin film formulation and the pixel-to-pixel quantification of the constituents were carried out by partial least square (PLS) and multivariate curve resolution-alternating least square (MCR-ALS) with three different calibration/validation strategies. These strategies differ in the way to construct the calibration and validation matrices and they had to be carried out to suppress the bias on the quantification of the constituents in the polymer blend. The errors of prediction in the models from MCR-ALS were influenced by the calibration/validation strategy employed, but they were similar to the ones from PLS model. Concentration distribution maps were built after pixel-to-pixel predictions and their characteristics were analyzed.

Monitoring of multiple solid-state transformations at tablet surfaces using multi-series near-infrared hyperspectral imaging and multivariate curve resolution.

The assessment of the solid-state stability of active pharmaceutical ingredient (API) and/or excipients in solid dosage forms during manufacturing and storage is mandatory for safeguarding quality of the final products. In this work, the solid-state transformations in tablets prepared as blends of piroxicam monohydrate, polyvinylpyrrolidone and the lactose forms monohydrate or anhydrate were studied when the tablets were exposed to the 23-120 °C range. Multi-series near-infrared hyperspectral images were obtained from the surface of each sample for unveiling the local evolution of the solid-state transformations. The preprocessed spectra from the images (dataset) were arranged in augmented matrices, according to the composition of the tablets, and the profile of the overlapped compounds (relative concentration) along the solid-state transformations in the pixels was resolved by using multivariate curve resolution--alternating least squares (MCR-ALS). Therefore, the dehydration of piroxicam and lactose monohydrates could be mapped separately in the samples (explained variances by the models >96%) even when both compounds were being transformed simultaneously (80-120 °C). The images reproduced the same trends obtained from thermogravimetric analysis of the tablets, with the advantage that the pixel-to-pixel heterogeneity of each compound at the surface of the tablets was highlighted.

Discriminating Brazilian crude oils using comprehensive two-dimensional gas chromatography–mass spectrometry and multiway principal component analysis ☆

The geochemical characterization of petroleum is an essential task to develop new strategies and technologies when analyzing the commercial potential of crude oils for exploitation. Due to the chemical complexity of these samples, the use of modern analytical techniques along with multivariate exploratory data analysis approaches is an interesting strategy to extract relevant geochemical characteristics about the oils. In this work, important geochemical information obtained from crude oils from different production basins were obtained analyzing the maltene fraction of the oils by comprehensive two-dimensional gas chromatography coupled to quadrupole mass spectrometry (GC×GC-QMS), and performing multiway principal component analysis (MPCA) of the chromatographic data. The results showed that four MPC explained 93.57% of the data variance, expressing mainly the differences on the profiles of the saturated hydrocarbon fraction of the oils (C13-C18 and C19-C30n-alkanes and the pristane/phytane ratio). The MPC1 grouped the samples severely biodegraded oils, while the type of the depositional paleoenvironments of the oils and its oxidation conditions (as well as their thermal maturity) could be inferred analysing others relevant MPC. Additionally, considerations about the source of the oil samples was also possible based on the overall distribution of relevant biomarkers such as the phenanthrene derivatives, tri-, tetra- and pentacyclic terpanes.

Resolução multivariada de curvas com mínimos quadrados alternantes: descrição, funcionamento e aplicações

Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS) is a resolution method that has been efficiently applied in many different fields, such as process analysis, environmental data and, more recently, hyperspectral image analysis. When applied to second order data (or to three-way data) arrays, recovery of the underlying basis vectors in both measurement orders (i.e. signal and concentration orders) from the data matrix can be achieved without ambiguities if the trilinear model constraint is considered during the ALS optimization. This work summarizes different protocols of MCR-ALS application, presenting a case study: near-infrared image spectroscopy.

Optimizing loop-type cryogenic modulation in comprehensive two-dimensional gas chromatography using time-variable combination of the dual-stage jets for analysis of crude oil

The enhanced chromatographic capability of the comprehensive two-dimensional gas chromatography (GC×GC) has already found several applications in analytical chemistry comprising complex samples. However, setting the appropriate chromatographic conditions that maximize sensitivity and separation efficiency in GC×GC may be more difficult than in conventional one-dimension gas chromatography, mainly due to the additional parameters strictly related to the modulation. Loop-type cryogenic modulators have been currently used for crude oil analysis using GC×GC, requiring sometimes a laborious try-and-error procedure to properly tune the dual-jets elapsed times on modulation. In this work, the advantages of choosing a time-variable combination of cold and hot jets pulses in a loop-type cryogenic modulator is presented when performing the fingerprinting analysis of crude oils using GC×GC-QMS, contrary to the conventional procedure based on a single combination for the dual-stage jets. A design of experiments approach is proposed to most effectively optimize the time-variable combination of the dual-jets elapsed times while modulating the wide hydrocarbons range along the GC×GC analysis. The most abundant classes of hydrocarbons contained in the maltenes fraction of a crude oil sample, such as paraffins, aromatics, steranes and hopanes were successfully resolved.

Study of the Homogeneity of Drug Loaded in Polymeric Films Using Near-Infrared Chemical Imaging and Split-Plot Design

Split-plot design (SPD) and near-infrared chemical imaging were used to study the homogeneity of the drug paracetamol loaded in films and prepared from mixtures of the biocompatible polymers hydroxypropyl methylcellulose, polyvinylpyrrolidone, and polyethyleneglycol. The study was split into two parts: a partial least-squares (PLS) model was developed for a pixel-to-pixel quantification of the drug loaded into films. Afterwards, a SPD was developed to study the influence of the polymeric composition of films and the two process conditions related to their preparation (percentage of the drug in the formulations and curing temperature) on the homogeneity of the drug dispersed in the polymeric matrix. Chemical images of each formulation of the SPD were obtained by pixel-to-pixel predictions of the drug using the PLS model of the first part, and macropixel analyses were performed for each image to obtain the y-responses (homogeneity parameter). The design was modeled using PLS regression, allowing only the most relevant factors to remain in the final model. The interpretation of the SPD was enhanced by utilizing the orthogonal PLS algorithm, where the y-orthogonal variations in the design were separated from the y-correlated variation.

Blood-Based Lipidomics Approach to Evaluate Biomarkers Associated With Response to Olanzapine, Risperidone, and Quetiapine Treatment in Schizophrenia Patients

This is the first study to identify lipidomic markers in plasma associated with response of acutely ill schizophrenia patients in response to specific antipsychotic treatments. The study population included 54 schizophrenia patients treated with antipsychotics for 6 weeks. Treatment led to significant improvement in positive and negative symptoms for 34 patients with little or no improvement for 20 patients. In addition, 37 patients showed an increase in body mass index after the 6 week treatment period, consistent with effects on metabolism and the association of such effects with symptom improvement. Profiling of plasma samples taken prior to therapy using liquid chromatography tandem mass spectrometry (LC-MS/MS) resulted in identification of 38, 10, and 52 compounds associated with the olanzapine, risperidone, and quetiapine treatment groups, which could be used to distinguish responders from non-responders. Limitations include the retroactive active nature of the study and the small sample size. Further investigations with larger sample sets could lead to the development of a molecular test that could be used to help psychiatrists determine the best treatment options for each patient.

Classical Least Squares Combined with Spectral Interval Selection Using Genetic Algorithm for Prediction of Constituents in Pharmaceutical Solid Dosage Forms from near Infrared Chemical Imaging Data

A new algorithm that combines spectral interval selection using genetic algorithm and classical least squares (GA-iCLS) is presented for the prediction of the active pharmaceutical ingredients and excipients in various pharmaceutical solid dosage forms from near infrared chemical imaging data. The algorithm is based on the CLS approach, selecting the best wavenumber intervals in the unfolded hyper-cube of each sample (D), and in pure-compound reference spectra (S), wherein the pixel-to-pixel prediction capability of the compounds, obtained by C = DST(SST)−1, is optimised for the samples. The wavelength intervals were selected (GA optimisation) while minimising the error between the mean concentrations of the ith compound predicted in the pixels and the nominal concentration in the corresponding sample (known a priori). The excluded wavenumber intervals from D (and S), for each sample, were interpreted based on systematic deviations from D = CST + E (CLS approach) due to the scattering effects and/or intermolecular interactions in mixtures of the pure compounds. The comparison of the chemical images generated from the predictions performed using the GA-iCLS algorithms with similar images obtained without spectral interval selection, using direct CLS and multivariate curve resolution–alternating least squares, revealed the potential applicability of the proposed algorithm for analytical purposes for pharmaceuticals using chemical imaging data.

Comprehensive two-dimensional gas chromatography–mass spectrometry combined with multivariate data analysis for pattern recognition in Ecuadorian spirits

The current methodology used in quality control of Ecuadorian beverages such as Pájaro azúl, Puro and Pata de vaca is carried out by using conventional gas chromatography; however, it does not allow the fingerprinting of these Ecuadorian spirit beverages and their possible cases of adulteration. In order to overcome this drawback, comprehensive two-dimensional gas chromatography–mass spectrometry (GC × GC–MS) was combined with multivariate data analysis, revealing that compounds like citronellal, citronellol, geraniol, methyl anthranilate, (−)-trans-α-bergamotene, (−)-cis-α-bergamotene and d-limonene can be considered key elements for pattern recognition of these traditional beverages and product adulteration cases. Thus, the two-dimensional chromatographic fingerprints obtained by GC × GC–MS coupled with chemometric analysis, using Principal Component Analysis and Fisher-ratio can be considered as a potential strategy for adulteration recognition, and it may used as a quality assurance system for Ecuadorian traditional spirits.