Use of NIR spectroscopy and multivariate process spectra calibration methodology for pharmaceutical solid samples analysis

Accomplish high quality of final products in pharmaceutical industry is a challenge that requires the control and supervision of all the manufacturing steps. This request created the necessity of developing fast and accurate analytical methods. Near infrared spectroscopy together with chemometrics, fulfill this growing demand. The high speed providing relevant information and the versatility of its application to different types of samples lead these combined techniques as one of the most appropriated. This study is focused on the development of a calibration model able to determine amounts of API from industrial granulates using NIR, chemometrics and process spectra methodology.

Conformational polymorphism of the antidiabetic drug chlorpropamide

In this paper, the main features of Raman spectroscopy, one of the first choice methods in the study of polymorphism in pharmaceuticals, are presented taking chlorpropamide as a case of study. The antidiabetic drug chlorpropamide (1-[4-chlorobenzenesulphonyl]-3-propyl urea), which belongs to the sulfonylurea class, is known to exhibit, at least, six polymorphic phases. These forms are characterized not only by variations in their molecular packing but also in their molecular conformation. In this study, the polymorphism of chlorpropamide is discussed on the basis of Raman scattering measurements and quantum mechanical calculations. The main spectroscopic features that fingerprint the crystalline forms are correlated with the corresponding crystalline structures. Using a theoretical approach on the energy dependence of the conformers, simulated molecular torsion angles are plotted versus the formation energy, which provides a satisfactory agreement between the torsion angles at the energy minima and the experimental values observed in the different solid forms of chlorpropamide. Copyright (C) 2011 John Wiley & Sons, Ltd.

Identification of pharmaceutical tablets by Raman spectroscopy and chemometrics

Raman spectroscopy has become an attractive tool for the analysis of pharmaceutical solid dosage forms. In the present study it is used to ensure the identity of tablets. The two main applications of this method are release of final products in quality control and detection of counterfeits. Twenty-five product families of tablets have been included in the spectral library and a non-linear classification method, the Support Vector Machines (SVMs), has been employed. Two calibrations have been developed in cascade: the first one identifies the product family while the second one specifies the formulation. A product family comprises different formulations that have the same active pharmaceutical ingredient (API) but in a different amount. Once the tablets have been classified by the SVM model, API peaks detection and correlation are applied in order to have a specific method for the identification and allow in the future to discriminate counterfeits from genuine products. This calibration strategy enables the identification of 25 product families without error and in the absence of prior information about the sample. Raman spectroscopy coupled with chemometrics is therefore a fast and accurate tool for the identification of pharmaceutical tablets.

CNVs and genetic medicine (excitement and consequences of a rediscovery).

The extensive variability of individual human genomes contributes to phenotypic variability. Structural genomic variants, and copy number variants (CNVs) in particular, have recently been rediscovered as contributors to the genomic plasticity and evolution and as pathoetiologic elements for both monogenic and complex traits. Herein we review some of the consequences of CNVs in the context of human inherited diseases.

Detection and chemical profiling of medicine counterfeits by Raman spectroscopy and chemometrics

Raman spectroscopy combined with chemometrics has recently become a widespread technique for the analysis of pharmaceutical solid forms. The application presented in this paper is the investigation of counterfeit medicines. This increasingly serious issue involves networks that are an integral part of industrialized organized crime. Efficient analytical tools are consequently required to fight against it. Quick and reliable authentication means are needed to allow the deployment of measures from the company and the authorities. For this purpose a method in two steps has been implemented here. The first step enables the identification of pharmaceutical tablets and capsules and the detection of their counterfeits. A nonlinear classification method, the Support Vector Machines (SVM), is computed together with a correlation with the database and the detection of Active Pharmaceutical Ingredient (API) peaks in the suspect product. If a counterfeit is detected, the second step allows its chemical profiling among former counterfeits in a forensic intelligence perspective. For this second step a classification based on Principal Component Analysis (PCA) and correlation distance measurements is applied to the Raman spectra of the counterfeits.

Solvothermal Preparation of Drug Crystals: Didanosine

For the first time, crystals of suitable size for X-ray diffractometry structure determination (Dian important anti-HI V drug were prepared under solvothermal conditions. In this study, the crystal structure of didanosine (2`,3`-dideoxyinosine, ddI) in the form of a hydrate was determined using single-crystal X-ray diffractometry. Powder X-ray diffraction analysis revealed that the solid-state phase of the drug incorporated into pharmaceutical solid dosage forms is isostructural to the solvothermally prepared ddI material, even though they do not exhibit an identical chemical composition due to different water fractions occupying hydrophobic channels formed within the crystal lattice. Two ddI conformers are present in the structure, in agreement with a previous structure elucidation attempt. Concerning the keto enol equilibrium of ddI, our crystal data and vibrational characterizations by Fourier transform infrared (FTIR) and FT-Raman spectroscopy techniques were conclusive to state that both conformers exist in the keto form, contrary to solid-state NMR spectroscopic assignments that suggested ddI molecules occur as enol tautomers. In addition, characterizations by thermal (differential scanning calorimetry) and spectroscopic techniques allowed us to understand the structural similarities and the differences related to the hydration pattern of the nonstoichiometric hydrates.

Emprego de redes neurais artificiais supervisionadas e não supervisionadas no estudo de parâmetros reológicos de excipientes farmacêuticos sólidos

In this paper artificial neural network (ANN) based on supervised and unsupervised algorithms were investigated for use in the study of rheological parameters of solid pharmaceutical excipients, in order to develop computational tools for manufacturing solid dosage forms. Among four supervised neural networks investigated, the best learning performance was achieved by a feedfoward multilayer perceptron whose architectures was composed by eight neurons in the input layer, sixteen neurons in the hidden layer and one neuron in the output layer. Learning and predictive performance relative to repose angle was poor while to Carr index and Hausner ratio (CI and HR, respectively) showed very good fitting capacity and learning, therefore HR and CI were considered suitable descriptors for the next stage of development of supervised ANNs. Clustering capacity was evaluated for five unsupervised strategies. Network based on purely unsupervised competitive strategies, classic "Winner-Take-All", "Frequency-Sensitive Competitive Learning" and "Rival-Penalize Competitive Learning" (WTA, FSCL and RPCL, respectively) were able to perform clustering from database, however this classification was very poor, showing severe classification errors by grouping data with conflicting properties into the same cluster or even the same neuron. On the other hand it could not be established what was the criteria adopted by the neural network for those clustering. Self-Organizing Maps (SOM) and Neural Gas (NG) networks showed better clustering capacity. Both have recognized the two major groupings of data corresponding to lactose (LAC) and cellulose (CEL). However, SOM showed some errors in classify data from minority excipients, magnesium stearate (EMG) , talc (TLC) and attapulgite (ATP). NG network in turn performed a very consistent classification of data and solve the misclassification of SOM, being the most appropriate network for classifying data of the study. The use of NG network in pharmaceutical technology was still unpublished. NG therefore has great potential for use in the development of software for use in automated classification systems of pharmaceutical powders and as a new tool for mining and clustering data in drug development

Molecularly Imprinted Solid Phase Extraction Of Fluconazole From Pharmaceutical Formulations.

This work encompasses a direct and coherent strategy to synthesise a molecularly imprinted polymer (MIP) capable of extracting fluconazole from its sample. The MIP was successfully prepared from methacrylic acid (functional monomer), ethyleneglycoldimethacrylate (crosslinker) and acetonitrile (porogenic solvent) in the presence of fluconazole as the template molecule through a non-covalent approach. The non-imprinted polymer (NIP) was prepared following the same synthetic scheme, but in the absence of the template. The data obtained from scanning electronic microscopy, infrared spectroscopy, thermogravimetric and nitrogen Brunauer-Emmett-Teller plot helped to elucidate the structural as well as the morphological characteristics of the MIP and NIP. The application of MIP as a sorbent was demonstrated by packing it in solid phase extraction cartridges to extract fluconazole from commercial capsule samples through an offline analytical procedure. The quantification of fluconazole was accomplished through UPLC-MS, which resulted in LOD≤1.63×10(-10) mM. Furthermore, a high percentage recovery of 91±10% (n=9) was obtained. The ability of the MIP for selective recognition of fluconazole was evaluated by comparison with the structural analogues, miconazole, tioconazole and secnidazole, resulting in percentage recoveries of 51, 35 and 32%, respectively.

CRTC2 polymorphism as a risk factor for the incidence of metabolic syndrome in patients with solid organ transplantation.

NlmCategory="UNASSIGNED">Metabolic syndrome after transplantation is a major concern following solid organ transplantation (SOT). The CREB-regulated transcription co-activator 2 (CRTC2) regulates glucose metabolism. The effect of CRTC2 polymorphisms on new-onset diabetes after transplantation (NODAT) was investigated in a discovery sample of SOT recipients (n1=197). Positive results were tested for replication in two samples from the Swiss Transplant Cohort Study (STCS, n2=1294 and n3=759). Obesity and other metabolic traits were also tested. Associations with metabolic traits in population-based samples (n4=46'186, n5=123'865, n6>100,000) were finally analyzed. In the discovery sample, CRTC2 rs8450-AA genotype was associated with NODAT, fasting blood glucose and body mass index (Pcorrected<0.05). CRTC2 rs8450-AA genotype was associated with NODAT in the second STCS replication sample (odd ratio (OR)=2.01, P=0.04). In the combined STCS replication samples, the effect of rs8450-AA genotype on NODAT was observed in patients having received SOT from a deceased donor and treated with tacrolimus (n=395, OR=2.08, P=0.02) and in non-kidney transplant recipients (OR=2.09, P=0.02). Moreover, rs8450-AA genotype was associated with overweight or obesity (n=1215, OR=1.56, P=0.02), new-onset hyperlipidemia (n=1007, OR=1.76, P=0.007), and lower high-density lipoprotein-cholesterol (n=1214, β=-0.08, P=0.001). In the population-based samples, a proxy of rs8450G>A was significantly associated with several metabolic abnormalities. CRTC2 rs8450G>A appears to have an important role in the high prevalence of metabolic traits observed in patients with SOT. A weak association with metabolic traits was also observed in the population-based samples.The Pharmacogenomics Journal advance online publication, 8 December 2015; doi:10.1038/tpj.2015.82.

Thermal analysis and compatibility studies of prednicarbate with excipients used in semi solid pharmaceutical form

Differential Scanning Calorimetry (DSC), thermogravimetry/derivative thermogravimetry (TG/DTG) and infrared spectroscopy (IR) techniques were used to investigate the compatibility between prednicarbate and several excipients commonly used in semi solid pharmaceutical form. The thermoanalytical studies of 1:1 (m/m) drug/excipient physical mixtures showed that the beginning of the first thermal decomposition stage of the prednicarbate (T (onset) value) was decreased in the presence of stearyl alcohol and glyceryl stearate compared to the drug alone. For the binary mixture of drug/sodium pirrolidone carboxilate the first thermal decomposition stage was not changed, however the DTG peak temperature (T (peak DTG)) decreased. The comparison of the IR spectra of the drug, the physical mixtures and of the thermally treated samples confirmed the thermal decomposition of prednicarbate. By the comparison of the thermal profiles of 1:1 prednicarbate:excipients mixtures (methylparaben, propylparaben, carbomer 940, acrylate crosspolymer, lactic acid, light liquid paraffin, isopropyl palmitate, myristyl lactate and cetyl alcohol) no interaction was observed.

Porosity measurement of solid pharmaceutical dosage forms by gamma-ray transmission

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Non-conventional applications of computerized tomography: Analysis of solid dosage forms produced by pharmaceutical industry

X-ray computed tomography (CT) refers to the cross-sectional imaging of an object measuring the transmitted radiation at different directions. In this work, we describe a non-conventional application of computerized tomography: visualization and improvements in the understanding of some internal structural features of solid dosage forms. A micro-CT X-ray scanner, with a minimum resolution of 30 μm was used to characterize some pharmaceutical tablets, granules, controlled-release osmotic tablet and liquid-filled soft-gelatin capsules. The analysis presented in this work are essentially qualitative, but quantitative parameters, such as porosity, density distribution, tablets dimensions, etc. could also be obtained using the related CT techniques. © 2010 American Institute of Physics.

Flow-injection spectrophotometric determination of captopril in pharmaceutical formulations using a new solid-phase reactor containing AgSCN immobilized in a polyurethane resin

A simple flow-injection analysis procedure was developed for determining captopril in pharmaceutical formulations employing a novel solid-phase reactor containing silver thiocyanate immobilized in a castor oil derivative polyurethane resin. The method was based on silver mercaptide formation between the captopril and Ag(I) in the solid-phase reactor. During such a reaction, the SCN- anion was released and reacted with Fe3+, which generated the FeSCN2+ complex that was continuously monitored at 480 nm. The analytical curve was linear in the captopril concentration range from 3.0 x 10(-4) mol L-1 to 1.1 x 10(-3) mol L-1 with a detection limit of 8.0 x 10(-5) mol L-1. Recoveries between 97.5% and 103% and a relative standard deviation of 2% for a solution containing 6.0 x 10(-4) mol L-1 captopril (n = 12) were obtained. The sample throughput was 40 h(-1) and the results obtained for captopril in pharmaceutical formulations using this procedure and those obtained using a pharmacopoeia procedure were in agreement at a 95% confidence level.

A LED Based Photometer for Solid Phase Photometry: Zinc Determination in Pharmaceutical Preparation Employing a Multicommuted Flow Analysis Approach

In this work, a LED (light emitting diode) based photometer for solid phase photometry is described. The photometer was designed to permit direct coupling of a light source (LED) and a photodiode to a flow cell with an optical pathlength of 4 mm. The flow cell was filled with adsorbing solid phase material (C-18), which was used to immobilize the chromogenic reagent 1-(2-thiazolylazo)-2-naphthol (TAN). Aiming to allow accuracy assessment, samples were also analyzed employing ICP OES (inductively coupled plasma optical emission spectrometry) methodology. Applying the paired t-test at the 95% confidence level, no significant difference was observed. Other useful features were also achieved: linear response ranging from 0.05 to 0.85 mg L-1 Zn, limit of detection of 9 mu g L-1 Zn (3 sigma criterion), standard deviation of 1.4% (n = 10), sampling throughput of 36 determinations per h, and a waste generation and reagent consumption of 1.7 mL and of 0.03 mu g per determination, respectively.

A LED based photometer for solid phase photometry: zinc determination in pharmaceutical preparation employing a multicommuted flow analysis approach

Neste trabalho é proposto um fotômetro baseado em LED (diodo emissor de luz) para fotometria em fase sólida. O fotômetro foi desenvolvido para permitir o acoplamento da fonte de radiação (LED) e do fotodetector direto na cela de fluxo, tendo um caminho óptico de 4 mm. A cela de fluxo foi preenchida com material sólido (C18), o qual foi utilizado para imobilizar o reagente cromogênico 1-(2-tiazolilazo)-2-naftol (TAN). A exatidão foi avaliada empregando dados obtidos através da técnica ICP OES (espectrometria de emissão por plasma indutivamente acoplado). Aplicando-se o teste-t pareado não foi observada diferença significativa em nível de confiança de 95%. Outros parâmetros importantes encontrados foram faixa de resposta linear de 0,05 a 0,85 mg L-1 Zn, limite de detecção de 9 µg L-1 Zn (n = 3), desvio padrão de 1,4 % (n = 10), frequência de amostragem de 36 determinações por h, e uma geração de efluente e consumo de reagente de 1,7 mL e 0,03 µg por determinação, respectivamente.