Enhanced monitoring of biopharmaceutical product purity using liquid chromatography-mass spectrometry

LC-MS is a widely used technique for impurity detection and identification. It is very informative and generates huge amounts of data. However, the relevant chemical information may not be directly accessible from the raw data map, particularly in reference to applications where unknown impurities are to be detected. This study demonstrates that multivariate statistical process control (MSPC) based on principal component analysis (PCA) in conjunction with multiple testing is very powerful for comprehensive monitoring and detection of an unknown and co-eluting impurity measured with liquid chromatography-mass spectrometry (LC-MS). It is demonstrated how a spiked impurity present at low concentrations (0.05% (w/w)) is detected and further how the contribution plot provides clear diagnostics of the unknown impurity. This tool makes a fully automatic monitoring of LC-MS data possible, where only relevant areas in the LC-MS data are highlighted for further interpretation.     

Peak purity determination with principal component analysis of high-performance liquid chromatography-diode array detection data

A method is proposed for the determination of chromatographic peak purity by means of principal component analysis (PCA) of high-performance liquid chromatography with diode array detection (HPLC-DAD) data. The method is exemplified with analysis of binary mixtures of lidocaine and prilocaine with different levels of separation. Lidocaine and prilocaine have very similar spectra and the chromatograms used had substantial peak overlap. The samples analysed contained a constant amount of lidocaine and a minor amount of prilocaine (0.02-2 conc.%) and hence the focus was on determining the purity of the lidocaine peak in the presence of much smaller levels of prilocaine. The peak purity determination was made by examination of relative observation residuals, scores and loadings from the PCA decomposition of DAD data over a chromatographic peak. As a reference method, the functions for peak purity analysis in the chromatographic data system used (Chromeleon) were applied. The PCA method showed good results at the same level as the detection limit of baseline-separated prilocaine, outperforming the methods in Chromeleon by a factor of ten. There is a discussion of the interpretation of the result, with some comparisons with evolving factor analysis (EFA). The main advantage of the PCA method for determination of peak purity over methods like EFA lies in its simplicity, short time of calculation and ease of use.     

Application of Computer-Aided Spectral Deconvolution Technique in Validation of High Performance Liquid Chromatographic Peaks

Abstract

Reliable analysis with high performance liquid chromatography (HPLC) requires purity of the eluting peak. The present work has combined the advantages of the availability of full spectral data from HPLC photodiode array UV detector and computer algorithms to perform chromatographic peak purity check. A deconvolution technique based on multicomponent analysis has been applied to the UV spectra of co-eluting components. This method employs residual error (Relative-fit-error, RFE) between predicted spectrum and analyte's spectrum to detect presence of other component or contaminant. Typical RFE values for uncontaminated chromatographic peaks of norethisterone and ethynyloestradiol range between 1 and 3, while contaminated peaks have RFE values as large as 145. A systematic increase in ‘relative-fit error’ from 1.10 to 145 was observed for peaks of norethisterone when contaminated to varied extent with ethynyloestradiol. Extent of peak overlap in chromatogram was also mapped out with this technique. The co-prescribed oral contraceptive, norethisterone and ethynyloestradiol were used as model in this work. An advantage of the method is its applicability when the contaminant's spectrum is unavailable. The method, unlike several earlier techniques, is also applicable to chromatograms with concidental elution time for the components.     

Liquid adsorption chromatography of polyethers: experiments and simulation

The adsorption behavior of poly(ethylene glycol) (PEG) in reversed-phase chromatography is studied both experimentally and theoretically and a computer simulation of chromatograms is performed on the basis of these studies. The experimental conditions were: different reversed-phase adsorbents and a solvent methanol–water system as the mobile phase. At varying mobile phase compositions highly resolved chromatograms of PEG samples were obtained, in which all peaks could be identified, and the dependencies of the distribution coefficient on the degree of polymerization for PEG molecules were evaluated by processing these chromatograms. The data were interpreted by using a theory of homopolymers based on a continuum Gaussian chain model of flexible macromolecules and a slit-like model of pores of stationary phase. The theory proved to describe well the experimental data in the whole range of studied molecular masses, and the thermodynamic parameters characterizing interactions of ethylene oxide repeating units in PEG molecules with the adsorbent pore walls have been determined from the comparison of the theory with the experimental data. The dispersion of chromatographic peaks corresponding to individual oligomer molecules is also estimated. In the system studied the peak width occurred to be proportional to the distribution coefficient of corresponding macromolecule. The theory is used to develop a computer-assisted procedure for simulation of chromatograms for samples of linear homopolymers. Using the obtained data on the thermodynamic parameters and the estimates of peak dispersion, chromatograms are simulated for PEG samples at two different chromatographic conditions. These simulated chromatograms were in good quantitative agreement with the real chromatograms.     

High-speed peak matching algorithm for retention time alignment of gas chromatographic data for chemometric analysis

A rapid retention time alignment algorithm was developed as a preprocessing utility to be used prior to chemometric analysis of large datasets of diesel fuel profiles obtained using gas chromatography (GC). Retention time variation from chromatogram-to-chromatogram has been a significant impediment against the use of chemometric techniques in the analysis of chromatographic data due to the inability of current chemometric techniques to correctly model information that shifts from variable to variable within a dataset. The alignment algorithm developed is shown to increase the efficacy of pattern recognition methods applied to diesel fuel chromatograms by retaining chemical selectivity while reducing chromatogram-to-chromatogram retention time variations and to do so on a time scale that makes analysis of large sets of chromatographic data practical. Two sets of diesel fuel gas chromatograms were studied using the novel alignment algorithm followed by principal component analysis (PCA). In the first study, retention times for corresponding chromatographic peaks in 60 chromatograms varied by as much as 300 ms between chromatograms before alignment. In the second study of 42 chromatograms, the retention time shifting exhibited was on the order of 10 s between corresponding chromatographic peaks, and required a coarse retention time correction prior to alignment with the algorithm. In both cases, an increase in retention time precision afforded by the algorithm was clearly visible in plots of overlaid chromatograms before and then after applying the retention time alignment algorithm. Using the alignment algorithm, the standard deviation for corresponding peak retention times following alignment was 17 ms throughout a given chromatogram, corresponding to a relative standard deviation of 0.003% at an average retention time of 8 min. This level of retention time precision is a 5-fold improvement over the retention time precision initially provided by a state-of-the-art GC instrument equipped with electronic pressure control and was critical to the performance of the chemometric analysis. This increase in retention time precision does not come at the expense of chemical selectivity, since the PCA results suggest that essentially all of the chemical selectivity is preserved. Cluster resolution between dissimilar groups of diesel fuel chromatograms in a two-dimensional scores space generated with PCA is shown to substantially increase after alignment. The alignment method is robust against missing or extra peaks relative to a target chromatogram used in the alignment, and operates at high speed, requiring roughly 1 s of computation time per GC chromatogram.     

Preparative high-performance liquid chromatographic separation and isolation of bacitracin components and their relationship to microbiological activity.

Bacitracin, a polypeptide antibiotic, is one of the most commonly used antibiotics in the world. The approved method of analysis for bacitracin is microbial. To correlate the microbiological method with a high-performance liquid chromatographic (HPLC) method, bacitracin was chromatographed using HPLC with ultraviolet detection and a YMC basic column. Adequate separation of the isomers was obtained to scale up this procedure to preparative HPLC using a Prep HPLC system and a 250 x 21 mm YMC basic column. The various fractions were separated, isolated and examined for microbial activity. The individual fractions could be precipitated by adding zinc or methylene disalicylic acid and lowering the pH. The crude fractions were recycled to ensure chromatographic purity. The chromatograms can accurately predict (in minutes) the microbiologically determined potency which usually takes 16-24 h to develop. The chromatographic procedure also provides information on the amounts of isomers and degradation products present in the sample, whereas the microbiological assay only provides activities or potencies of the antibiotic. The reported HPLC method also possesses some advantages over some other published HPLC methods in terms of accuracy and time of analysis.     

Quality control and discrimination of pericarpium citri reticulatae and pericarpium citri reticulatae viride based on high-performance liquid chromatographic fingerprints and multivariate statistical analysis

High-performance liquid chromatographic (HPLC) fingerprints of Pericarpium Citri Reticulatae (PCR) and Pericarpium Citri Reticulatae Viride (PCRV) were firstly measured for deliberately collected 39 authentic samples and 21 commercial samples. Both correlation coefficients of similarity for chromatograms and absolute peak areas of characteristic compounds were calculated for quantitative expression of the HPLC fingerprints. After principal component analysis (PCA) successfully distinguished the ‘mixed peels’ samples from authentic samples, partial least squares-linear discrimination analysis (PLS-LDA) was then effectively applied to class separation between authentic PCR and PCRV. Furthermore, the unequivocally determined compounds, hesperidin, nobiletin and tangeretin, were screened out by loadings plots of PCA and PLS-LDA. The results indicated that they could be used as chemical markers for discrimination among different groups of samples. The proposed method shows an efficient strategy for quality control of PCR and PCRV, which cannot only distinguish the ‘mixed peels’ but also discriminate authentic PCR and PCRV. This method has potential perspective for quality control of traditional Chinese medicine (TCM).     

HPLC Fingerprint with Multi-components Analysis for Quality Consistency Evaluation of Traditional Chinese Medicine Si-Mo-Tang Oral Liquid Preparation

Si-Mo-Tang(SMT) oral liquid preparation, a traditional Chinese medicine, was prepared from four crude herbal drugs, Fructus Aurantii Submaturus, Radix Aucklandiae, Semen Arecae and Radix Linderae Aggregatae. A combinative method using HPLC fingerprint and quantitative analysis was developed and validated for quality consistency evaluation of SMT. Individual HPLC chromatograms were evaluated against the mean chromatogram generated via a similarity evaluation computer program. Data from chromatographic fingerprints were also processed with principal component analysis(PCA) and hierarchical cluster analysis(HCA). Additionally, six components (naringin, isonaringin, hesperidin, neohesperidin, norisoboldine and potassium sorbate) in SMT were simultaneously determined to interpret the quality consistency. For fingerprint analysis, 20 peaks were selected as the characteristic peaks to evaluate the similarities of 26 SMT collected from different manufacturers. Among the 20 characteristic peaks, 10 peaks were assigned to be naringin, hesperidin, neohesperidin, isonaringin, neoeriocitrin, tangeretin, nobiletin, norisoboldine, 5-(ethoxymethyl)furan-2-carbaldehyde and potassium sorbate, respectively. The results of similarity analysis, PCA and HCA, indicate that the samples from different manufacturers were consistent with each other in composition. The results from the quantitative data show that the contents of six compounds were significantly different in SMT oral liquid preparations from different manufacturers. The combinative method of chromatographic fingerprint with quantitative analysis developed here offered an efficient way for the quality consistency evaluation of the traditional Chinese medicine SMT.     

高效液相色谱-离子阱-飞行时间质谱法鉴定碱性嫩黄中的杂质及高效液相色谱法制备碱性嫩黄标准物质

该文建立了一种高效液相色谱-离子阱-飞行时间质谱（HPLC-IT-TOF-MS）分析非法食品添加剂碱性嫩黄样品中杂质成分的方法。对碱性嫩黄样品中的杂质进行多级质谱分析,根据各碎片离子的精确质量数推测出该杂质的具体组成,确定这个杂质为4-（亚氨基（4-（甲基氨基）苯基）甲基）-N,N-二甲基苯胺盐酸盐,从而推断出碱性嫩黄的合成方法及杂质的可能来源。同时建立了制备碱性嫩黄标准物质的方法,分别选用了粒径为10μm和5μm的制备液相色谱柱进行两次制备高效液相色谱分离纯化,进样量分别为1 mL和500μL,最终采用分析型高效液相色谱峰面积归一化法得到纯度为99.52%的碱性嫩黄标准物质。扣除0.34%水分含量,0.13%灰分含量,采用质量平衡法确定制备的物质最终纯度为99.05%,并通过UV、IR、LC-MS和NMR四大谱图进行化学结构的确认。该方法简单、高效,可拓展应用于其他非法食品添加剂标准物质的制备。     

Applications of HPLC-MS in compound Ilex pubescens extract study

In this paper, high performance liquid chromatography (HPLC) along with mass spectrometry (MS) and HPLC along with a diode array detector (DAD) was used to study the compound Ilex pubescens extract. Two ionization techniques: electro spray ionization (ESI) and atmospheric pressure chemical ionization (APCI) were used in this work. The liquid chromatograms obtained by DAD, total ion chromatograms (TIC) from positive-and negative-ion ESI-MS and the positive-and negative-ion APCI-MS were compared. The liquid chromatograms obtained by TIC from ESI-MS provided more information on chromatographic peaks than those obtained by DAD or TIC from APCI-MS. It is suggested that the fingerprints of the compound Ilex pubescens extract should be provided by the liquid chromatograms obtained by DAD together with TIC from the negative-ion ESI-MS. The molecular weights of the nine main components in an HPLC-DAD chromatogram were determined by the corresponding positive-and negative-ion ESI and the positive-and negative-ion APCI mass spectra information. In the liquid chromatogram obtained by TIC from the negative-ion ESI-MS, the molecular weights of 23 main components were determined based on the corresponding positive-and negative-ion ESI mass spectra information.     

辽东楤木叶中皂苷Congmuyenoside B(2)的分离与鉴定

本研究实现了对辽东楤木叶中Congmuyenoside B(2)的分离与鉴定。研究中采用大孔吸附树脂提取法和硅胶柱层析法对其分离,应用HPLC色谱法和薄层色谱法对纯度进行分析,利用电喷雾多级串联质谱结合核磁共振和红外光谱对该化合物的结构进行分析鉴定。本提取分离法操作简便,提高了分离化合物的纯度。HPLC色谱法灵敏度高,结果准确、减少了质谱及其它色谱中的杂质峰对化合物鉴定的干扰,结构准确,可靠。     

icoshift: An effective tool for the alignment of chromatographic data

The Interval Correlation Optimised Shifting algorithm (icoshift) has recently been introduced for the alignment of nuclear magnetic resonance spectra. The method is based on an insertion/deletion model to shift intervals of spectra/chromatograms and relies on an efficient Fast Fourier Transform based computation core that allows the alignment of large data sets in a few seconds on a standard personal computer. The potential of this programme for the alignment of chromatographic data is outlined with focus on the model used for the correction function. The efficacy of the algorithm is demonstrated on a chromatographic data set with 45 chromatograms of 64,000 data points. Computation time is significantly reduced compared to the Correlation Optimised Warping (COW) algorithm, which is widely used for the alignment of chromatographic signals. Moreover, icoshift proved to perform better than COW in terms of quality of the alignment (viz. of simplicity and peak factor), but without the need for computationally expensive optimisations of the warping meta-parameters required by COW. Principal component analysis (PCA) is used to show how a significant reduction on data complexity was achieved, improving the ability to highlight chemical differences amongst the samples.     

Evaluation of Seven Chromatographic Response Functions on Simulated and Experimentally Obtained Chromatograms in Hydrophilic Interaction Liquid Chromatography System

This paper investigates the ability of seven chromatographic response functions to measure the quality of chromatograms obtained in hydrophilic interaction liquid chromatography (HILIC). First, the functions were tested on a set of simulated chromatograms and differences in their mathematical design were discussed. Second, the functions were evaluated on the experimentally obtained chromatograms in HILIC analysis of model mixture consisted of beta agonists and antagonists. The ranking of chromatograms obtained by different functions was significantly different, implying that the accuracy of the optimization procedure is strongly dependent on the function that was selected as an output. Investigation of potential drawbacks of each function was conducted and general recommendations concerning the use of chromatographic response functions in optimization strategies are proposed.     

Authentication of cassia seeds on the basis of two-wavelength HPLC fingerprinting with the use of chemometrics

<正>High performance liquid chromatographic(HPLC) fingerprints of Cassia seed,a traditional Chinese medicine(TCM),were developed by means of the chromatograms at two wavelengths of 238 and 282 nm.Then,the two data sets were combined into one matrix.The application of principal component analysis(PCA) for this data matrix showed that the samples were clustered into four groups in accordance with the plant sources and preparation procedures.Furthermore,partial least squares(PLS),back propagation artificial neural network(BP-ANN),and radial basis function artificial neural network(RBF-ANN) were effectively applied to predict the category of the four different samples in the test set.     

Quantitative impurity profiling by principal component analysis of high-performance liquid chromatography-diode array detection data

Related organic impurities generally have approximately similar molar absorption coefficients (epsilon) due to their structural similarities. On the assumption that all peaks in an impurity profiling chromatogram have approximately the same maximum molar absorption coefficients (epsilon(max)) and the chromatogram contains one major peak and several much smaller ones, all of which are completely separated, integration of the summed score vectors from the principal component analysis (PCA) decomposition of high-performance liquid chromatography-diode array detection (HPLC-DAD) data will give areas that are quantitatively proportional to the actual content of the compounds. Due to the sequential nature of PCA, the first principal component (PC) will primarily be related to the main compound and all peaks showing a similar spectrum, while the second PC will be related to the impurities with a spectrum different from the main peak. Summing the two score vectors thus makes it possible to take account of different spectra in the score chromatogram, which make the method proposed give better quantitative estimates of the impurities than any single wavelength chromatogram. Multivariate curve resolution alternating least squares (MCR-ALS) is used for comparison. The results are presented for two examples of simulated HPLC-DAD data as well as for three examples of real HPLC-DAD data from impurity profiling. The results show that integration of the score chromatograms can handle differences in the unknown epsilon(max) of the peaks and take account of the different spectra of the impurity peaks, giving quantitative estimates of the content of the impurities that closely correspond to the reference values. The results obtained are also better than integration with the best possible separate wavelength. The method could be a straightforward approach to impurity profiling in order to obtain a good estimate of the content or relative response factors of small chromatographic impurity peaks without knowledge of their molar absorption coefficients and without any precalibration.     

Peak alignment and robust principal component analysis of gas chromatograms of fatty acid methyl esters and volatiles

Gas chromatograms of fatty acid methyl esters and of volatile lipid oxidation products from fish lipid extracts are analyzed by multivariate data analysis [principal component analysis (PCA)]. Peak alignment is necessary in order to include all sampled points of the chromatograms in the data set. The ability of robust algorithms to deal with outlier problems, including both sample-wise and element-wise outliers, and the advantages and drawbacks of two robust PCA methods, robust PCA (ROBPCA) and robust singular value decomposition when analysing these GC data were investigated. The results show that the usage of ROPCA is advantageous, compared with traditional PCA, when analysing the entire profile of chromatographic data in cases of sub-optimally aligned data. It also demonstrates how choosing the most robust PCA (sample or element-wise) depends on the type of outliers present in the data set.     

Determination of the purity of phenoxymethylpenicillin by micellar electrokinetic chromatography and reversed phase liquid chromatography on a monolithic silica column

A micellar electrokinetic chromatographic and a fast reversed‐phase liquid chromatographic method have been developed for determination of the purity of phenoxymethylpenicillin. The optimized running buffer composition was 40 mM phosphate–borate–125 mM SDS–3.5% (v/v) methanol. The HPLC method employed a monolithic silica C18 column and a mobile phase composed of phosphate buffer, pH 3.5, and ACN, the flow‐rate being 3.5 mL/min. Both methods were successfully validated. Linearity, intermediate precision, limits of quantitation, accuracy, and a good correlation of the HPLC and MEKC results were demonstrated. Both methods proved to be fast and reliable and sufficiently sensitive. A combination of the two methods can be very useful in impurity profiling.     

多面体低聚八硝基苯基硅倍半氧烷纯度分析

使用高效液相色谱-电喷雾四级杆飞行时间质谱(HPLC-ESI-Q-TOF MS)联用技术对八硝基苯基硅倍半氧烷(ONPS)纯度进行分析, 从而判定ONPS产物峰及杂质峰的位置, 根据ONPS峰和杂质峰的面积比计算ONPS的纯度. 通过改变HPLC的洗脱梯度和测试时间, 将ONPS产物中的杂质峰完全分开, 测得硝基苯基硅倍半氧烷(NPS)质量分数为97.55%, 其中ONPS的纯度约为92.42%, 产物中含有九硝基八苯基硅倍半氧烷(9-NPS)约5.13%, 其它杂质含量约为2.45%. 通过对ONPS高效液相色谱图峰形和同分异构体极性情况分析, 进一步证明ONPS分子中硝基取代发生于对位和间位. 使用超高效液相色谱(UPLC)对ONPS进行分析, 以更高的分离效率验证了HPLC的结果. 该方法可作为ONPS纯度的分析方法.     

Determination of the purity of ampicillin by micellar electrokinetic chromatography and reversed phase liquid chromatography on a monolithic silica column

A micellar electrokinetic chromatographic (MEKC) method and a fast reversed-phase liquid chromatographic one have been developed for determining the purity of ampicillin. MEKC separation of ampicillin and its related substances was performed with the use of an untreated fused-silica capillary and 40 mM phosphate-borate buffer, pH 7.5 containing 75 mM SDS. The HPLC method employed a monolithic silica C18 column and a mobile phase composed of phosphate buffer, pH 5.2 and ACN, the flow rate being 4.0 mL/min. Both methods were successfully validated. Linearity, relative response factors, limits of quantitation, intermediate precision, and accuracy were evaluated. The methods proved to be fast, reliable, and sufficiently sensitive and, accordingly, well-suited for control of purity of ampicillin substance, injections, and capsules. A combination of both methods can be very useful in the confirmation of impurity profiles.     

A simple method for automated pretreatment of usable chromatographic profiles in pattern-recognition procedures: application to HPAEC-PAD chromatograms of honeys

In this article a simple method for automated pretreatment of chromatograms is presented. The resulting data matrix can be used as input for multivariate statistical analysis. Application of this method to high-performance anion-exchange chromatography-pulsed amperometric detection (HPAEC-PAD) chromatograms of honeys before canonical discriminant analysis results in very good performance in the data reduction with regard to the preservation of the original information content of the data. This pretreatment of the chromatogram allows for the use of all the peaks corresponding to the sugars present in the sample. This results in a high-quality discrimination between honeys of various types. A versatile program has been developed to apply this method. This serves as a starting point for software suited for food characterization and adulteration detection by semi-automatic pattern recognition applied to chromatographic analysis.