Evaluation of data preprocessings for the comparison of GC-MS chemical profiles of seized cannabis samples.

Cannabis is the most frequently used illicit drug in Belgium, where it is mainly cultivated indoor. To improve the fight against this drug, cannabis-profiling methods are required. Cannabis is a natural product and its chemical composition depends on many factors, which cause a high heterogeneity and variability in the secondary metabolites, and make this study challenging. The aim of this study is to combine cannabis profiling with statistical methodology to evaluate the intra (within)- and inter (between)-plantation variabilities with the goal to define a suitable approach linking seized marijuana to given plantations. The data set used contains 46 samples from 9 locations. The chemical profiles, consisting of data from eight cannabinoids, are obtained by gas chromatography - mass spectrometry. The raw data (peak areas) is pretreated with different preprocessing methods. The Pearson correlation coefficients between intra-location profiles were calculated after each pre-treatment, and the 95 and 99 % confidence limits determined. All preprocessed data were then compared with the internal standard normalization reference method with the aim to minimize the overlap between intra- and inter-location results, i.e. to reduce the number of false positives, and to obtain the best discrimination. Furthermore, cross-validation was used to evaluate the model originating from the most efficient data pre-treatment technique. The best results were obtained, when the peak areas were normalized to the internal standard with subsequent calculation of the fourth root. It results in a reduction of false positives for both confidence limits to 11 % and 14 % compared to 21 % and 27 % for the reference method. Cross-validation reveals similar false positive results as for the calibration set. In conclusion, when preprocessing the data, an improved model is obtained resulting in a significant decrease in the number of false positives. After studying the predictive performance of the model, it appears to be representative for the entire plantation information.

Flavonoids from Boldoa purpurascens inhibit proinflammatory cytokines (TNF-α and IL-6) and the expression of COX-2.

The flavonoids comprise a large class of plant metabolites distributed in food plants. These compounds have antioxidant, antitumor, antiallergic, and anti­inflammatory effects. The molecular mechanisms of their biological activities remain to be clearly understood. We investigated the in vitro anti­inflammatory potential of a flavonoid mixture and isolated compounds from the leaves of Boldoa purpurascens. Our results provide direct evidence of the anti­inflammatory effects of the mixture, which are mediated by the inhibition of the proinflammatory cytokines tumor necrosis factor α and interleukin 6 as well as the modulation of the expression of cyclooxygenase 2.

Breakage and drying behaviour of granules in a continuous fluid bed dryer: Influence of process parameters and wet granule transfer.

Although twin screw granulation has already been widely studied in recent years, only few studies addressed the subsequent continuous drying which is required after wet granulation and still suffers from a lack of detailed understanding. The latter is important for optimisation and control and, hence, a cost-effective practical implementation. Therefore, the aim of the current study is to increase understanding of the drying kinetics and the breakage and attrition phenomena during fluid bed drying after continuous twin screw granulation. Experiments were performed on a continuous manufacturing line consisting of a twin-screw granulator, a six-segmented fluid bed dryer, a mill, a lubricant blender and a tablet press. Granulation parameters were fixed in order to only examine the effect of drying parameters (filling time, drying time, air flow, drying air temperature) on the size distribution and moisture content of granules (both of the entire granulate and of size fractions). The wet granules were transferred either gravimetrically or pneumatically from the granulator exit to the fluid bed dryer. After a certain drying time, the moisture content reached an equilibrium. This drying time was found to depend on the applied airflow, drying air temperature and filling time. The moisture content of the granules decreased with an increasing drying time, airflow and drying temperature. Although smaller granules dried faster, the multimodal particle size distribution of the granules did not compromise uniform drying of the granules when the target moisture content was achieved. Extensive breakage of granules was observed during drying. Especially wet granules were prone to breakage and attrition during pneumatic transport, either in the wet transfer line or in the dry transfer line. Breakage and attrition of granules during transport and drying should be anticipated early on during process and formulation development by performing integrated experiments on the granulator, dryer and mill.

Multivariate statistical process control in product quality review assessment - A case study.

According to the Food and Drug Administration and the European Good Manufacturing Practices (GMP) guidelines, Annual Product Review (APR) is a mandatory requirement in GMP. It consists of evaluating a large collection of qualitative or quantitative data in order to verify the consistency of an existing process. According to the Code of Federal Regulation Part 11 (21 CFR 211.180), all finished products should be reviewed annually for the quality standards to determine the need of any change in specification or manufacturing of drug products. Conventional Statistical Process Control (SPC) evaluates the pharmaceutical production process by examining only the effect of a single factor at the time using a Shewhart's chart. It neglects to take into account the interaction between the variables. In order to overcome this issue, Multivariate Statistical Process Control (MSPC) can be used. Our case study concerns an APR assessment, where 164 historical batches containing six active ingredients, manufactured in Morocco, were collected during one year. Each batch has been checked by assaying the six active ingredients by High Performance Liquid Chromatography according to European Pharmacopoeia monographs. The data matrix was evaluated both by SPC and MSPC. The SPC indicated that all batches are under control, while the MSPC, based on Principal Component Analysis (PCA), for the data being either autoscaled or robust scaled, showed four and seven batches, respectively, out of the Hotelling T2 95% ellipse. Also, an improvement of the capability of the process is observed without the most extreme batches. The MSPC can be used for monitoring subtle changes in the manufacturing process during an APR assessment.

A label-free detector for liquid chromatography systems using mm-wave technology: First proof of concept.

The development of millimeter-wave (mm-wave) technology has enabled the study of bio-molecular interactions by means of electromagnetic waves with frequencies between 30 and 300GHz. In this study, an attempt has been made to exploit the possibility of mm-wave technology as alternative detection technique for liquid chromatographic (LC) systems. The goal is to design and fabricate a label-free mm-wave detector that is compatible with LC systems. As proof-of-concept experiments, the UV absorbing compounds praziquantel and trans-stilbene-oxide as well as a non-UV absorbing compound sorbitol are injected in an open capillary as well as a capillary with stationary phase and measured by both mm-wave and UV detectors. The in-house developed mm-wave detector is capable of detecting all compounds without the need for labelling. Although the detection limit of such detector still needs to be verified and occasionally improved in the future, it already shows great potential as an additional detection technique for LC systems.

Azithromycin assay in drug formulations: Validation of a HPTLC method with a quadratic polynomial calibration model using the accuracy profile approach.

Many different assaying high performance thin layer chromatography (HPTLC) methods have been developed and validated in order to be used in routine analysis in different analytical fields. Validation often starts by the evaluation of the linearity of the calibration curve. Frequently, if the correlation coefficient is close to one, the linear calibration curve model is considered to be proper to predict the unknown concentration in the sample. But is this simple model effective to assess the behavior of the response of an HPTLC method as a function of concentration. To answer this question, a method for the determination of azithromycin by HPTLC has been developed and validated following both the classical approach and that based on the accuracy profile. Silica gel plates with fluorescence indicator F254 and chloroform - ethanol - 25% ammonia 6:14:0.2 (v/v/v) as mobile phase were used. Analysis was carried out in reflectance mode at 483nm. The RF of azithromycin was 0.53. The validation based on the classical approach, shows that the behavior is not linear, even though r2=0.999 because the lack of fit test is significant (P<0.05). Validation based on the accuracy profile approach considering both the straight line and the quadratic regression model, show that the former results is a ß-expectation tolerance interval outside the acceptance limits, while with the latter, this interval is within the limits of ±5% acceptability for a range which extends from 0.2 to 1.0µg/zone. With the quadratic model, the method showed to be precise and accurate.

Discrimination and classification techniques applied on Mallotus and Phyllanthus high performance liquid chromatography fingerprints.

Mallotus and Phyllanthus genera, both containing several species commonly used as traditional medicines around the world, are the subjects of this discrimination and classification study. The objective of this study was to compare different discrimination and classification techniques to distinguish the two genera (Mallotus and Phyllanthus) on the one hand, and the six species (Mallotus apelta, Mallotus paniculatus, Phyllanthus emblica, Phyllanthus reticulatus, Phyllanthus urinaria L. and Phyllanthus amarus), on the other. Fingerprints of 36 samples from the 6 species were developed using reversed-phase high-performance liquid chromatography with ultraviolet detection (RP-HPLC-UV). After fingerprint data pretreatment, first an exploratory data analysis was performed using Principal Component Analysis (PCA), revealing two outlying samples, which were excluded from the calibration set used to develop the discrimination and classification models. Models were built by means of Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Classification and Regression Trees (CART) and Soft Independent Modeling of Class Analogy (SIMCA). Application of the models on the total data set (outliers included) confirmed a possible labeling issue for the outliers. LDA, QDA and CART, independently of the pretreatment, or SIMCA after "normalization and column centering (N_CC)" or after "Standard Normal Variate transformation and column centering (SNV_CC)" were found best to discriminate the two genera, while LDA after column centering (CC), N_CC or SNV_CC; QDA after SNV_CC; and SIMCA after N_CC or after SNV_CC best distinguished between the 6 species. As classification technique, SIMCA after N_CC or after SNV_CC results in the best overall sensitivity and specificity.

Chiral separability of boron cluster species studied by screening approaches utilizing polysaccharide-based chiral stationary phases.

In this study, the screening steps of chiral separation strategies with polysaccharide-based chiral stationary phases were applied on boron cluster compounds in normal-phase liquid chromatography (NPLC) and polar organic solvents chromatography (POSC). Since the screening steps were initially developed to analyze organic compounds, their applicability for boron clusters was investigated. Overall, the screening steps in NPLC were applicable for the separation of zwitterions, while for anions mostly no elution was observed. A hypothesis for the latter behavior is precipitation of anions in the nonpolar mobile phases. Ten out of 11 compounds could be partially or baseline separated on the NPLC screening systems. In POSC, all zwitterions were separated on at least one of the screening systems, with an overall lower retention as in NPLC. Anions were detected but not separated in the majority of the experiments. Also their retention on the chiral stationary phases was very limited. This study showed that the chiral discrimination potential of chemically modified polysaccharides is meaningful for chiral separations of structurally chiral boron cluster species, but needs further systematic research, in which recognition mechanisms should be further explored. In addition, some unusual peaks also indicated that conditions with a high separation efficiency must first be searched for some of the tested systems.

Accuracy profiles assessing the validity for routine use of high-performance thin-layer chromatographic assays for drug formulations.

The accuracy profile, based on total error, integrates several validation parameters, such as trueness, precision and linearity, providing one statistic which enables decision on the suitability of a method for its intended purpose. Two assay methods for formulations are validated using accuracy profiles as an alternative approach to classic method validation. It concerns high-performance thin-layer chromatography (HPTLC) methods, which initially were validated using the classic approach. The first method assayed sulfamethoxazole and trimethoprim, and the second lamivudine, stavudine and nevirapine. Both formulations are fixed-dose combination tablets. The resulting accuracy profiles showed that the 95% ß-expectation tolerance limits for all compounds fell well within the bias acceptance limits set at ±5%. This means that the two analytical thin-layer chromatographic methods are capable of making accurate results at the studied concentration ranges of each compound. Measurement uncertainties of every compound at each concentration level could also be determined from the accuracy profile data.

Multivariate data analysis to evaluate the fingerprint peaks responsible for the cytotoxic activity of Mallotus species.

The Mallotus genus comprises numerous species used as traditional medicines in oriental countries and provides scientists a broad basis in the search for pharmacologically active constituents. In this paper, the cytotoxicity of 39 Mallotus extracts, different in species, part of the plant used, origin, and harvest season, is evaluated combining cytotoxicity assays with fingerprint technology and data handling tools. At first, the antiproliferative activity of the plant extracts is analyzed both on a non-cancerous cell line (WI-38--human lung fibroblast) and on a cancerous cell line (HeLa human cervix carcinoma). The results are linked to a data set of high-performance liquid chromatographic fingerprint profiles of the samples using multivariate calibration techniques. The regression coefficients of the multivariate model are then evaluated to indicate those peaks potentially responsible for the cytotoxic activity of the Mallotus extracts. In a final step, the cytotoxic extracts are analyzed by HPLC-MS and the indicated peaks identified.

Optimization of a reversed-phase-high-performance thin-layer chromatography method for the separation of isoniazid, ethambutol, rifampicin and pyrazinamide in fixed-dose combination antituberculosis tablets.

This paper presents the development of a new RP-HPTLC method for the separation of pyrazinamide, isoniazid, rifampicin and ethambutol in a four fixed-dose combination (4 FDC) tablet formulation. It is a single method with two steps in which after plate development pyrazinamide, isoniazid and rifampicin are detected at an UV wavelength of 280 nm. Then ethambutol is derivatized and detected at a VIS wavelength of 450 nm. Methanol, ethanol and propan-1-ol were evaluated modifiers to form alcohol-water mobile phases. Systematic optimization of the composition of each alcohol in the mobile phase was carried out using the window diagramming concept to obtain the best separation. Examination of the Rf distribution of the separated compounds showed that separation of the compounds with the mobile phase containing ethanol at the optimal fraction was almost situated within the optimal Rf-values region of 0.20-0.80. Therefore, ethanol was selected as organic modifier and the optimal mobile phase composition was found to be ethanol, water, glacial acetic acid (>99% acetic acid) and 37% ammonia solution (70/30/5/1, v/v/v/v). The method is new, quick and cheap compared to the actual method in the International Pharmacopoeia for the assay of the 4 FDC tablets, which involves the use of two separate HPLC methods.

Potentially antioxidant compounds indicated from Mallotus and Phyllanthus species fingerprints.

The genera of Mallotus and Phyllanthus contain several species that are commonly used as traditional medicines in oriental countries. Some species show interesting pharmaceutical activities, such as an antioxidant activity. To produce clinically useful medicines or food supplements (nutraceuticals) from these herbs, the species should be identified and a thorough quality control should be implemented. Nowadays, the integration of chromatographic and chemometric approaches allows a high-throughput identification and activity prediction of medicinal plants. In this study, Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) were applied and compared to distinguish Mallotus and Phyllanthus species. Moreover, peaks from their chromatographic fingerprints, which were responsible for their antioxidant activity were assigned. For the latter purpose, the relevant information was extracted from the chromatographic fingerprints using linear multivariate calibration techniques, i.e., Partial Least Squares (PLS) and Orthogonal Projections to Latent Structures (O-PLS). Results reveal that exploratory analysis using PCA shows somewhat diverging clustering tendencies between Mallotus and Phyllanthus samples than HCA. However, both approaches mainly confirm each other. Concerning the multivariate calibration techniques, both PLS and O-PLS models demonstrate good predictive abilities. By comparing the regression coefficients of the models with the chromatographic fingerprints, the peaks that are potentially responsible for the antioxidant activity of the extracts could be confirmed.

Similarity analyses of chromatographic fingerprints as tools for identification and quality control of green tea.

Similarity assessment of complex chromatographic profiles of herbal medicinal products is important as a potential tool for their identification. Mathematical similarity parameters have the advantage to be more reliable than visual similarity evaluations of often subtle differences between the fingerprint profiles. In this paper, different similarity analysis (SA) parameters are applied on green-tea chromatographic fingerprint profiles in order to test their ability to identify (dis)similar tea samples. These parameters are either based on correlation or distance measurements. They are visualised in colour maps and evaluation plots. Correlation (r) and congruence (c) coefficients are shown to provide the same information about the similarity of samples. The standardised Euclidean distance (ds) reveals less information than the Euclidean distance (de), while Mahalanobis distances (dm) are unsuitable for the similarity assessment of chromatographic fingerprints. The adapted similarity score (ss*) combines the advantages of r (or c) and de. Similarity analysis based on correlation is useful if concentration differences between samples are not important, whereas SA based on distances also detects concentration differences well. The evaluation plots including statistical confidence limits for the plotted parameter are found suitable for the evaluation of new suspected samples during quality assurance. The ss* colour maps and evaluation plots are found to be the best tools (in comparison to the other studied parameters) for the distinction between deviating and genuine fingerprints. For all studied data sets it is confirmed that adequate data pre-treatment, such as aligning the chromatograms, prior to the similarity assessment, is essential. Furthermore, green-tea samples chromatographed on two dissimilar High-Performance Liquid Chromatography (HPLC) columns provided the same similarity assessment. Combining these complementary fingerprints did not improve the similarity analysis of the studied data set.

HPTLC methods to assay active ingredients in pharmaceutical formulations: a review of the method development and validation steps.

High-performance thin-layer chromatography (HPTLC) is still increasingly finding its way in pharmaceutical analysis in some parts of the world. With the advancements in the stationary phases and the introduction of densitometers as detection equipment, the technique achieves for given applications a precision and trueness comparable to high-performance liquid chromatography (HPLC). In this review, the literature is surveyed for developed and validated HPTLC methods to assay active ingredients in pharmaceutical formulations published in the period 2005-2011. Procedures and approaches for method development, validation and quantitative assays are compared with the standard ways of conducting them. Applications of HPTLC in some other areas are also briefly highlighted.

Orthogonal chromatographic descriptors for modelling Caco-2 drug permeability.

The use of chromatographic descriptors as alternative for Caco-2 permeability in drug absorption screening was evaluated. Therefore, retentions were measured on 17 Reversed-Phase Liquid Chromatographic systems, considered to be orthogonal or dissimilar, and an Immobilized Artificial Membrane (IAM) system. Retentions on a Micellar Liquid Chromatography system were taken from the literature. From this set of systems, those found dissimilar for the used data set were selected. The retention factors on these systems were then used as descriptors in QSAR modelling. Modelling was performed using Stepwise Multiple Linear Regression. This resulted in a model using only two chromatographic systems with good descriptive and acceptable predictive properties. A high qualitative model was obtained by combining both chromatographic systems selected in the previous model with a lipophilicity parameter (the squared Moriguchi n-octanol/water partition coefficient) and the molecular volume.

Classification models for neocryptolepine derivatives as inhibitors of the ß-haematin formation.

This paper describes the construction of a QSAR model to relate the structures of various derivatives of neocryptolepine to their anti-malarial activities. QSAR classification models were build using Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Classification and Regression Trees (CART), Partial Least Squares-Discriminant Analysis (PLS-DA), Orthogonal Projections to Latent Structures-Discriminant Analysis (OPLS-DA), and Support Vector Machines for Classification (SVM-C), using four sets of molecular descriptors as explanatory variables. Prior to classification, the molecules were divided into a training and a test set using the duplex algorithm. The different classification models were compared regarding their predictive ability, simplicity, and interpretability. Both binary and multi-class classification models were constructed. For classification into three classes, CART and One-Against-One (OAO)-SVM-C were found to be the best predictive methods, while for classification into two classes, LDA, QDA and CART were.

Pressurized capillary electrochromatography in a screening for possible antioxidant molecules in Mallotus fingerprints: challenges, potentials and prospects.

Because of its eminent high resolution potential and minimal solvent consumption, pressurized capillary electrochromatography (pCEC) may offer an interesting alternative to HPLC for screening applications that need to resolve complex samples. In this paper, its potential was assessed in a screening of plant extracts from Mallotus species to indicate compounds with possible antioxidant activities by means of a PLS model built from their pCEC fingerprints. The main aim of this research was to find out whether pCEC can have an added value for this application. To get a complete overview of the techniques potential for this application, it was also assessed whether the technique can meet the requirements in terms of precision, sensitivity and column robustness. Encountered benefits and downsides were reported. Fingerprints with satisfactory sensitivity and precision could be obtained by concentrating the sample 5-fold and using optimized rinsing procedures, respectively. From the generated pCEC fingerprints of 39 Mallotus samples and their respective DPPH radical scavenging activity test results, a three-component PLS model was being built. The model proved good predictive abilities and easily allowed the indication of possible antioxidant compounds in the fingerprints. Despite its much higher peak capacity, the performance of pCEC to fingerprint the majority of the Mallotus extracts did not surpass that of a custom HPLC method. This was also reflected in its comparable power to indicate possible antioxidant compounds in the fingerprints after modeling. Because of its low detection sensitivity and modest column robustness, the benefit of the lower solvent consumption was partly paid-off by the current need for more system maintenance, also limiting the sample throughput. For the considered screening application, pCEC may suit as a viable but no preferred alternative technique.

Dissimilar chromatographic systems to indicate and identify antioxidants from Mallotus species.

The genus of Mallotus contains several species commonly used as traditional medicines in oriental countries. A data set containing 39 Mallotus samples, differing in species, cultivation conditions, harvest season and/or part of the plant was used to develop fingerprints on two dissimilar chromatographic systems. An exploratory analysis with principal component analysis (PCA) was performed on both data sets individually. The results were also combined to obtain additional information on the unknown samples included in the data set. Furthermore, the antioxidant activity of the samples was measured and modelled as a function of the fingerprints using the orthogonal projections to latent structures (O-PLS) technique. The regression coefficients of the models were studied to indicate the peaks potentially responsible for the antioxidant activity. The indicated peaks were analyzed and identified by HPLC coupled to mass spectrometry (HPLC-MS). Because of the complexity of biological samples, it was aspired to separate co-eluting components based on the significant difference in chromatographic selectivity on the dissimilar systems and consequently obtain additional, complementary information on the contribution of the individual components to the antioxidant activity. The results illustrate the potential use of dissimilar chromatographic systems. Several initially co-eluting compounds could be separated on the dissimilar system. The corresponding regression coefficients provided complementary information on the potential antioxidant activity of the separated compounds.

Development and validation of a normal-phase HPTLC method for the simultaneous analysis of lamivudine, stavudine and nevirapine in fixed-dose combination tablets.

This paper presents the development and validation of an improved method for the simultaneous analysis of lamivudine (LVD), stavudine (STV) and nevirapine (NVP) using high-performance thin-layer chromatography (HPTLC) with densitometric detection. Separation was performed on silica gel 60F(254) plates. The mobile phase is comprised of ethylacetate, methanol, toluene and concentrated ammonia (38.7:19.4:38.7:3.2, v:v:v:v). Detection wavelength was 254 nm. The R(f) values were 0.24±0.03, 0.38±0.04 and 0.69±0.04 (n=8) for LVD, STV and NVP, respectively. An F-test indicated that calibration graphs were adequately linear at the evaluated concentration ranges. The pooled %RSD for repeatability of the percentage amount recovered for LVD, STV and NVP were found to be 0.62, 0.54, and 0.79, and the pooled %RSD for time-different intermediate precision were 1.66, 1.27 and 1.21. The percentage recoveries for the trueness were 99.2%±1.5 for LVD, 98.6%±1.5 for STV and 99.3%±1.7 for NVP (n=3). Most factors evaluated in the robustness test were found to have an insignificant effect on the selected responses at 95% confidence level. This method was successfully used to analyze fixed-dose tablets samples of LVD, STV and NVP.

Influence of putrescine, cadaverine, spermidine or spermine on the formation of N-nitrosamine in heated cured pork meat.

The influence of biogenic amines (i.e. putrescine, cadaverine, spermidine and spermine) on the N-nitrosamine formation in heated cured lean meat was studied in the presence or absence of sodium nitrite and at different meat processing temperatures. Experimental evidence was produced using gas chromatography with thermal energy analysis detection (GC-TEA). Concentration of N-nitrosamines was modelled as a function of the temperature and the nitrite concentration for two situations, i.e. presence or absence of added biogenic amines to the meat. The significance of the influence of the changing parameters was evaluated by ANOVA (Analysis of Variance). It was found that higher processing temperatures and higher added amounts of sodium nitrite increase the yields of N-nitrosodimethylamine (NDMA) and N-nitrosopiperidine (NPIP). Spermidine and putrescine amplify the formation of NDMA, but spermine and cadeverine do not influence the formation of this N-nitrosamine. Spermidine and cadeverine cause a significant increase of NPIP. Beside N-nitrosopyrrolidine (NPYR) in some rare cases, no other volatile N-nitrosamines are detected.