Rational and Efficient Preparative Isolation of Natural Products by MPLC-UV-ELSD based on HPLC to MPLC Gradient Transfer.

In natural product research, the isolation of biomarkers or bioactive compounds from complex natural extracts represents an essential step for de novo identification and bioactivity assessment. When pure natural products have to be obtained in milligram quantities, the chromatographic steps are generally labourious and time-consuming. In this respect, an efficient method has been developed for the reversed-phase gradient transfer from high-performance liquid chromatography to medium-performance liquid chromatography for the isolation of pure natural products at the level of tens of milligrams from complex crude natural extracts. The proposed method provides a rational way to predict retention behaviour and resolution at the analytical scale prior to medium-performance liquid chromatography, and guarantees similar performances at both analytical and preparative scales. The optimisation of the high-performance liquid chromatography separation and system characterisation allows for the prediction of the gradient at the medium-performance liquid chromatography scale by using identical stationary phase chemistries. The samples were introduced in medium-performance liquid chromatography using a pressure-resistant aluminium dry load cell especially designed for this study to allow high sample loading while maintaining a maximum achievable flow rate for the separation. The method has been validated with a mixture of eight natural product standards. Ultraviolet and evaporative light scattering detections were used in parallel for a comprehensive monitoring. In addition, post-chromatographic mass spectrometry detection was provided by high-throughput ultrahigh-performance liquid chromatography time-of-flight mass spectrometry analyses of all fractions. The processing of all liquid chromatography-mass spectrometry data in the form of an medium-performance liquid chromatography x ultra high-performance liquid chromatography time-of-flight mass spectrometry matrix enabled an efficient localisation of the compounds of interest in the generated fractions. The methodology was successfully applied for the separation of three different plant extracts that contain many diverse secondary metabolites. The advantages and limitations of this approach and the theoretical chromatographic background that rules such as liquid chromatography gradient transfer are presented from a practical viewpoint.

Retention time prediction for dereplication of natural products (CxHyOz) in LC-MS metabolite profiling.

The detection and early identification of natural products (NPs) for dereplication purposes require efficient, high-resolution methods for the profiling of crude natural extracts. This task is difficult because of the high number of NPs in these complex biological matrices and because of their very high chemical diversity. Metabolite profiling using ultra-high pressure liquid chromatography coupled to high-resolution mass spectrometry (UHPLC­HR-MS) is very efficient for the separation of complex mixtures and provides molecular formula information as a first step in dereplication. This structural information alone or even combined with chemotaxonomic information is often not sufficient for unambiguous metabolite identification. In this study, a representative set of 260 NPs containing C, H, and O atoms only was analysed in generic UHPLC­HR-MS profiling conditions. Two easy to use quantitative structure retention relationship (QSRR) models were built based on the measured retention time and on eight simple physicochemical parameters calculated from the structures. First, an original approach using several partial least square (PLS) regressions according to the phytochemical classes provided satisfactory results with an easy calculation. Secondly, a unique artificial neural network (ANN) model provided similar results on the whole set of NPs but required dedicated software. The retention prediction methods described in this study were found to improve the level of confidence of the identification of given analytes among putative isomeric structures. Its applicability was verified for the dereplication of NPs in model plant extracts.

Differentiation of lemon essential oil based on volatile and non-volatile fractions with various analytical techniques: a metabolomic approach.

Due to the importance of citrus lemon oil for the industry, fast and reliable analytical methods that allow the authentication and/or classification of such oil, using the origin of production or extraction process, are necessary. To evaluate the potential of volatile and non-volatile fractions for classification purposes, volatile compounds of cold-pressed lemon oils were analyzed, using GC-FID/MS and FT-MIR, while the non-volatile residues were studied, using FT-MIR, (1)H-NMR and UHPLC-TOF-MS. 64 Lemon oil samples from Argentina, Spain and Italy were considered. Unsupervised and supervised multivariate analyses were sequentially performed on various data blocks obtained by the above techniques. Successful data treatments led to statistically significant models that discriminated and classified cold-pressed lemon oils according to their geographic origin, as well as their production processes. Studying the loadings allowed highlighting of important classes of discriminant variables that corresponded to putative or identified chemical functions and compounds.

Comprehensive profiling and marker identification in non-volatile citrus oil residues by mass spectrometry and nuclear magnetic resonance.

The detailed characterization of cold-pressed lemon oils (CPLOs) is of great importance for the flavor and fragrance (F&F) industry. Since a control of authenticity by standard analytical techniques can be bypassed using elaborated adulterated oils to pretend a higher quality, a combination of advanced orthogonal methods has been developed. The present study describes a combined metabolomic approach based on UHPLC-TOF-MS profiling and (1)H NMR fingerprinting to highlight metabolite differences on a set of representative samples used in the F&F industry. A new protocol was set up and adapted to the use of CPLO residues. Multivariate analysis based on both fingerprinting methods showed significant chemical variations between Argentinian and Italian samples. Discriminating markers identified in mixtures belong to furocoumarins, flavonoids, terpenoids and fatty acids. Quantitative NMR revealed low citropten and high bergamottin content in Italian samples. The developed metabolomic approach applied to CPLO residues gives some new perspectives for authenticity assessment.

A Bayesian design space for analytical methods based on multivariate models and predictions.

The International Conference for Harmonization (ICH) has released regulatory guidelines for pharmaceutical development. In the document ICH Q8, the design space of a process is presented as the set of factor settings providing satisfactory results. However, ICH Q8 does not propose any practical methodology to define, derive, and compute design space. In parallel, in the last decades, it has been observed that the diversity and the quality of analytical methods have evolved exponentially, allowing substantial gains in selectivity and sensitivity. However, there is still a lack of a rationale toward the development of robust separation methods in a systematic way. Applying ICH Q8 to analytical methods provides a methodology for predicting a region of the space of factors in which results will be reliable. Combining design of experiments and Bayesian standard multivariate regression, an identified form of the predictive distribution of a new response vector has been identified and used, under noninformative as well as informative prior distributions of the parameters. From the responses and their predictive distribution, various critical quality attributes can be easily derived. This Bayesian framework was then extended to the multicriteria setting to estimate the predictive probability that several critical quality attributes will be jointly achieved in the future use of an analytical method. An example based on a high-performance liquid chromatography (HPLC) method is given. For this example, a constrained sampling scheme was applied to ensure the modeled responses have desirable properties.

Improved quality-by-design compliant methodology for method development in reversed-phase liquid chromatography.

A complete strategy dedicated to quality-by-design (QbD) compliant method development using design of experiments (DOE), multiple linear regressions responses modelling and Monte Carlo simulations for error propagation was evaluated for liquid chromatography (LC). The proposed approach includes four main steps: (i) the initial screening of column chemistry, mobile phase pH and organic modifier, (ii) the selectivity optimization through changes in gradient time and mobile phase temperature, (iii) the adaptation of column geometry to reach sufficient resolution, and (iv) the robust resolution optimization and identification of the method design space. This procedure was employed to obtain a complex chromatographic separation of 15 antipsychotic basic drugs, widely prescribed. To fully automate and expedite the QbD method development procedure, short columns packed with sub-2 µm particles were employed, together with a UHPLC system possessing columns and solvents selection valves. Through this example, the possibilities of the proposed QbD method development workflow were exposed and the different steps of the automated strategy were critically discussed. A baseline separation of the mixture of antipsychotic drugs was achieved with an analysis time of less than 15 min and the robustness of the method was demonstrated simultaneously with the method development phase.

Study of common database feeding with results coming from different analytical methods in the framework of illicit drugs chemical profiling.

Analytical results harmonisation is investigated in this study to provide an alternative to the restrictive approach of analytical methods harmonisation which is recommended nowadays for making possible the exchange of information and then for supporting the fight against illicit drugs trafficking. Indeed, the main goal of this study is to demonstrate that a common database can be fed by a range of different analytical methods, whatever the differences in levels of analytical parameters between these latter ones. For this purpose, a methodology making possible the estimation and even the optimisation of results similarity coming from different analytical methods was then developed. In particular, the possibility to introduce chemical profiles obtained with Fast GC-FID in a GC-MS database is studied in this paper. By the use of the methodology, the similarity of results coming from different analytical methods can be objectively assessed and the utility in practice of database sharing by these methods can be evaluated, depending on profiling purposes (evidential vs. operational perspective tool). This methodology can be regarded as a relevant approach for database feeding by different analytical methods and puts in doubt the necessity to analyse all illicit drugs seizures in one single laboratory or to implement analytical methods harmonisation in each participating laboratory.

Screening of the most relevant parameters for method development in ultra-high performance hydrophilic interaction chromatography.

The goal of the present work was to provide some guidelines for method development in hydrophilic interaction chromatography (HILIC). For this purpose, a training set of 82 representative pharmaceutical compounds possessing diverse polarity and including acidic, basic and neutral properties was analyzed. All these drugs were injected on five short HILIC columns packed with sub-2µm particles and dedicated for UHPLC (ultra-high performance liquid chromatography) operation. Four different pH conditions ranging from pH 3 to 6 were tested at two ionic strengths (10 and 50mmol/L) and finally, the reference organic modifier in HILIC, namely acetonitrile was modified with small amounts of methanol or isopropanol. From these experiments and using multivariate data analysis, it is clear that the stationary phase was the most relevant parameters for tuning selectivity in HILIC, since the types of interactions (i.e. dipole-dipole, hydrogen bonding and ion exchange) with analytes strongly vary between columns. Among the selected phases, the diol phase was the less interesting one, in terms of selectivity and peak shape. The zwitterionic phase was attractive, as it allowed a better retention of acidic compounds. Finally, the bare silica phase was the most versatile HILIC column packed with sub-2µm particles in terms of retention, peak shape and selectivity. Mobile phase pH was the other important parameter to achieve an appropriate selectivity and retention, even if it remains always difficult to assess precisely the mobile phase pH, analyte pKa and silanols pKa, when working with more 70% acetonitrile. Finally, buffer ionic strength and organic modifier nature could be considered as secondary parameters for HILIC method development. In conclusion, screening four different columns packed with sub-2µm particles at two mobile phase pH, using a fast gradient seems to be a good generic approach for initial HILIC method development. The total time for such a screening was estimated at ∼1h, including reequilibration.

Development of a generic micellar electrokinetic chromatography method for the separation of 15 antimalarial drugs as a tool to detect medicine counterfeiting.

Since antimalarial drugs counterfeiting is dramatically present on the African market, the development of simple analytical methods for their quality control is of great importance. This work consists in the CE analysis of 15 antimalarials (artesunate, artemether, amodiaquine, chloroquine, piperaquine, primaquine, quinine, cinchonine, mefloquine, halofantrine, sulfadoxine, sulfalen, atovaquone, proguanil, and pyrimethamine). Since all these molecules cannot be ionized at the same pH, MEKC was preferred because it also allows separation of neutral compounds. Preliminary experiments were first carried out to select the most crucial factors affecting the antimalarials separation. Several conditions were tested and four parameters as well as their investigation domain were chosen: pH (5-10), SDS concentration (20-90 mM), ACN proportion (10-40%), and temperature (20-35°C). Then, the experimental design methodology was used and a central composite design was selected. Mathematical modeling of the migration times allowed the prediction of optimal conditions (29°C, pH 6.6, 29 mM SDS, 36% ACN) regarding analyte separation. The prediction at this optimum was verified experimentally and led to the separation of 13 compounds within 8 min. Finally, the method was successfully applied to the quality control of African antimalarial medicines for their qualitative and quantitative content.

Predictive elution window stretching and shifting as a generic search strategy for automated method development for liquid chromatography.

We report on the possibilities of a new method development (MD) algorithm that searches the chromatographic parameter space by systematically shifting and stretching the elution window over different parts of the time-axis. In this way, the search automatically focuses on the most promising areas of the solution space. Since only the retention properties of the first and last eluting compounds of the sample need to be (approximately) known, the algorithm can be directly applied to samples with unknown composition, and the proposed solutions are not sensitive to any modeling errors. The search efficiency of the algorithm has been evaluated on an extensive set of random-generated in silico samples covering a broad range of different retention properties. Compared to a pure grid-based search, the algorithm could reduce the number of missed components by 50% and more. The algorithm has also been applied to solve three different real-world separation problems from the pharmaceutical industry. All problems could be successfully solved in a very short time (order of 12 h of instrument time).

Application of design of experiments and design space methodology for the HPLC-UV separation optimization of aporphine alkaloids from leaves of Spirospermum penduliflorum Thouars.

Spirospermum penduliflorum Thouars (Menispermaceae) is an endemic species of Madagascar traditionally used as vasorelaxant. Recently, two aporphine alkaloids known to possess antihypertensive activity (dicentrine and neolitsine) were isolated and identified from the leaves of this plant. In the present study, a HPLC-UV method allowing the separation of all alkaloids and the quantification of dicentrine in the alkaloidic extract of leaves was developed using design of experiments and design space methodology. Three common chromatographic parameters (i.e. the mobile phase pH, the initial proportion of methanol and the gradient slope) were selected to construct a full factorial design of 36 experimental conditions. The times at the beginning, the apex (i.e. the retention time) and the end of each peak were recorded and modelled by multiple linear equations. The corresponding residuals were normally distributed which confirmed that the models can be used for the prediction of the retention times and to optimize the separation. The optimal separation was predicted at pH 3, with a gradient starting at 32% of methanol and a gradient slope of 0.42%/min. Good agreement was obtained between predicted and experimental chromatograms. The method was also validated using total error concept. Using the accuracy profile approach, validation results gave a LOD and LOQ for dicentrine of 3 µg/ml and 10 µg/ml, respectively. A relative standard deviation for intermediate precision lower than 10% was obtained. This method was found to provide accurate results in the concentration range of 10-75 µg/ml of dicentrine and is suitable for routine analysis.

Validation, transfer and measurement uncertainty estimation of an HPLC-UV method for the quantification of artemisinin in hydro alcoholic extracts of Artemisia annua L.

Malaria is the world's most important parasitic infection with 500 millions cases annually and almost 2 millions death per year. This disease is more present in Sub-Saharan Africa where 90% of the infections are found. Artemisinin and its semi synthetic derivatives (artemether, artesunate) have actually the most powerful activity on malaria, even in its complicated forms and resistance cases. Various methods have been proposed for detection and quantification of artemisinin in Artemisia annua L. by HPLC-UV, but the plant extracts used for this quantification were extracts obtained with organic solvents (toluene, petroleum ether, hexane). To be able to use crude A. annua extracts prepared at low cost to formulate antipaludic drugs, we chose the use of a mixture of water and ethanol as solvent of extraction, but no adequate analytical method for this kind of extracts is published. The main objectives of this work were first to develop an analytical method for artemisinin quantification in hydro alcoholic extracts of A. annua. Second, this method had to be thoroughly validated by the research and development laboratory and, third, the transfer of this method to the routine laboratory had to be demonstrated. The final aim was to compare the estimation of measurement uncertainty obtained during the method validation with validation standards to measurement uncertainty estimates obtained during the method transfer study with real samples. The method was validated following the accuracy profile methodology and was found to be accurate in the concentration range of 10.0-54.0 µg/ml with CV<8%. Limit of detection and of quantification were 2.73 and 10.0 µg/ml, respectively. The method was then successfully transferred to a laboratory in Benin by showing that the quality of the results that it will generate during routine application of the method is sufficient. Finally, the measurement uncertainty of the method was estimated from the validation experiments as well as from the transfer study with authentic unspiked samples of A. annua. The comparison of these measurement uncertainty estimations showed that they were coherent. It confirmed thus that the estimation of measurement uncertainty from validation experiments predicts well the measurement uncertainty of real routine samples. This analytical method was thus shown to be convenient for routine analysis of hydro alcoholic extracts of A. annua in Benin.

Application of new methodologies based on design of experiments, independent component analysis and design space for robust optimization in liquid chromatography.

HPLC separations of an unknown sample mixture and a pharmaceutical formulation have been optimized using a recently developed chemometric methodology proposed by W. Dewé et al. in 2004 and improved by P. Lebrun et al. in 2008. This methodology is based on experimental designs which are used to model retention times of compounds of interest. Then, the prediction accuracy and the optimal separation robustness, including the uncertainty study, were evaluated. Finally, the design space (ICH Q8(R1) guideline) was computed as the probability for a criterion to lie in a selected range of acceptance. Furthermore, the chromatograms were automatically read. Peak detection and peak matching were carried out with a previously developed methodology using independent component analysis published by B. Debrus et al. in 2009. The present successful applications strengthen the high potential of these methodologies for the automated development of chromatographic methods.

Optimisation and validation of a fast HPLC method for the quantification of sulindac and its related impurities.

The European Pharmacopoeia describes a liquid chromatography (LC) method for the quantification of sulindac, using a quaternary mobile phase including chloroform and with a rather long run time. In the present study, a new method using a short sub-2 µm column, which can be used on a classical HPLC system, was developed. The new LC conditions (without chloroform) were optimised by means of a new methodology based on design of experiments in order to obtain an optimal separation. Four factors were studied: the duration of the initial isocratic step, the percentage of organic modifier at the beginning of the gradient, the percentage of organic modifier at the end of the gradient and the gradient time. The optimal condition allows the separation of sulindac and of its 3 related impurities in 6 min instead of 18 min. Finally, the method was successfully validated using an accuracy profile approach in order to demonstrate its ability to accurately quantify these compounds.

Innovative development and validation of an HPLC/DAD method for the qualitative and quantitative determination of major cannabinoids in cannabis plant material.

GC is commonly used for the analysis of cannabis samples, e.g. in forensic chemistry. However, as this method is based on heating of the sample, acidic forms of cannabinoids are decarboxylated into their neutral counterparts. Conversely, HPLC permits the determination of the original composition of plant cannabinoids by direct analysis. Several HPLC methods have been described in the literature, but most of them failed to separate efficiently all the cannabinoids or were not validated according to general guidelines. By use of an innovative methodology for modelling chromatographic responses, a simple and accurate HPLC/DAD method was developed for the quantification of major neutral and acidic cannabinoids present in cannabis plant material: Delta9-tetrahydrocannabinol (THC), THC acid (THCA), cannabidiol (CBD), CBD acid (CBDA), cannabigerol (CBG), CBG acid (CBGA) and cannabinol (CBN). Delta8-Tetrahydrocannabinol (Delta8-THC) was determined qualitatively. Following the practice of design of experiments, predictive multilinear models were developed and used in order to find optimal chromatographic analytical conditions. The method was validated following an approach using accuracy profiles based on beta-expectation tolerance intervals for the total error measurement, and assessing the measurements uncertainty. This analytical method can be used for diverse applications, e.g. plant phenotype determination, evaluation of psychoactive potency and control of material quality.

CE-MS method development for peptides analysis, especially hepcidin, an iron metabolism marker.

A method for the resolution of a peptides mixture including hepcidin-25, an iron metabolism marker, was developed by CE-ESI-MS. Several strategies were tested to optimize peptide separation, such as the addition of cyclodextrins or organic solvents in the BGE or the use of coated capillaries. Best results in terms of resolution, symmetry and efficiency were obtained with a BGE made of 500 mM ammonium acetate pH 4.5/ACN 70:30 v/v. Using the methodology of experimental design, BGE concentration, sheath liquid composition and MS-coupling parameters were then optimized in order to obtain the best signal intensity for hepcidin. Finally, a 225 mM BGE and a sheath liquid composed of isopropanol/water 80:20 v/v containing 0.5% v/v formic acid were selected as it constitutes the best compromise for selectivity, peak shape and sensitivity.

A new statistical method for the automated detection of peaks in UV-DAD chromatograms of a sample mixture.

One of the major issues within the context of the fully automated development of chromatographic methods consists of the automated detection and identification of peaks coming from complex samples such as multi-component pharmaceutical formulations or stability studies of these formulations. The same problem can also occur with plant materials or biological matrices. This step is thus critical and time-consuming, especially when a Design of Experiments (DOE) approach is used to generate chromatograms. The use of DOE will often maximize the changes of the analytical conditions in order to explore an experimental domain. Unfortunately, this generally provides very different and "unpredictable" chromatograms which can be difficult to interpret, thus complicating peak detection and peak tracking (i.e. matching peaks among all the chromatograms). In this context, Independent Components Analysis (ICA), a new statistically based signal processing methods was investigated to solve this problem. The ICA principle assumes that the observed signal is the resultant of several phenomena (known as sources) and that all these sources are statistically independent. Under those assumptions, ICA is able to recover the sources which will have a high probability of representing the constitutive components of a chromatogram. In the present study, ICA was successfully applied for the first time to HPLC-UV-DAD chromatograms and it was shown that ICA allows differentiation of noise and artifact components from those of interest by applying clustering methods based on high-order statistics computed on these components. Furthermore, on the basis of the described numerical strategy, it was also possible to reconstruct a cleaned chromatogram with minimum influence of noise and baseline artifacts. This can present a significant advance towards the objective of providing helpful tools for the automated development of liquid chromatography (LC) methods. It seems that analytical investigations could be shortened when using this type of methodologies.