Optimization of capillary zone electrophoresis for charge heterogeneity testing of biopharmaceuticals using enhanced method development principles

CZE is a well‐established technique for charge heterogeneity testing of biopharmaceuticals. It is based on the differences between the ratios of net charge and hydrodynamic radius. In an extensive intercompany study, it was recently shown that CZE is very robust and can be easily implemented in labs that did not perform it before. However, individual characteristics of some examined proteins resulted in suboptimal resolution. Therefore, enhanced method development principles were applied here to investigate possibilities for further method optimization. For this purpose, a high number of different method parameters was evaluated with the aim to improve CZE separation. For the relevant parameters, design of experiments (DoE) models were generated and optimized in several ways for different sets of responses like resolution, peak width and number of peaks. In spite of product specific DoE optimization it was found that the resulting combination of optimized parameters did result in significant improvement of separation for 13 out of 16 different antibodies and other molecule formats. These results clearly demonstrate generic applicability of the optimized CZE method. Adaptation to individual molecular properties may sometimes still be required in order to achieve optimal separation but the set screws discussed in this study [mainly pH, identity of the polymer additive (HPC versus HPMC) and the concentrations of additives like acetonitrile, butanolamine and TETA] are expected to significantly reduce the effort for specific optimization.     

Considerations on contactless conductivity detection in capillary electrophoresis

Nearly all analyses by capillary electrophoresis (CE) are performed using optical detection, utilizing either absorbance or (laser-induced) fluorescence. Though adequate for many analytical problems, in a large number of cases, e.g., involving non-UV-absorbing compounds, these optical detection methods fall short. Indirect optical detection can then still provide an acceptable means of detection, however, with a strongly reduced sensitivity. During the past few years, contactless conductivity detection (CCD) has been presented as a valuable extension to optical detection techniques. It has been demonstrated that with CCD detection limits comparable, or even superior, to (indirect) optical detection can be obtained. Additionally, construction of the CCD around the CE capillary is straightforward and robust operation is easily obtained. Unfortunately, in the literature a large variety of designs and operating conditions for CCD were described. In this contribution, several important parameters of CCD are identified and their influence on, e.g., detectability and peak shape is described. An optimized setup based on a well-defined detection cell with three detection electrodes is presented. Additionally, simple and commercially available read-out electronics are described. The performance of the CCD-CE system was demonstrated for the analysis of peptides. Detection limits at the microM level were obtained in combination with good peak shapes and an overall good performance and stability.     

Benchmark Evaluation of Protein–Protein Interaction Prediction Algorithms

Protein–protein interactions (PPIs) perform various functions and regulate processes throughout cells. Knowledge of the full network of PPIs is vital to biomedical research, but most of the PPIs are still unknown. As it is infeasible to discover all of them experimentally due to technical and resource limitations, computational prediction of PPIs is essential and accurately assessing the performance of algorithms is required before further application or translation. However, many published methods compose their evaluation datasets incorrectly, using a higher proportion of positive class data than occuring naturally, leading to exaggerated performance. We re-implemented various published algorithms and evaluated them on datasets with realistic data compositions and found that their performance is overstated in original publications; with several methods outperformed by our control models built on ‘illogical’ and random number features. We conclude that these methods are influenced by an over-characterization of some proteins in the literature and due to scale-free nature of PPI network and that they fail when tested on all possible protein pairs. Additionally, we found that sequence-only-based algorithms performed worse than those that employ functional and expression features. We present a benchmark evaluation of many published algorithms for PPI prediction. The source code of our implementations and the benchmark datasets created here are made available in open source.     

Experimental designs for modeling retention patterns and separation efficiency in analysis of fatty acid methyl esters by gas chromatography-mass spectrometry

The retention behavior of components analyzed by chromatography varies with instrumental settings. Being able to predict how changes in these settings alter the elution pattern is useful, both with regards to component identification, as well as with regards to optimization of the chromatographic system. In this work, it is shown how experimental designs can be used for this purpose. Different experimental designs for response surface modeling of the separation of fatty acid methyl esters (FAME) as function of chromatographic conditions in GC have been evaluated. Full factorial, central composite, Doehlert and Box-Behnken designs were applied. A mixture of 38 FAMEs was separated on a polar cyanopropyl substituted polysilphenylene-siloxane phase capillary column. The temperature gradient, the start temperature of the gradient, and the carrier gas velocity were varied in the experiments. The modeled responses, as functions of chromatographic conditions, were retention time, retention indices, peak widths, separation efficiency and resolution between selected peak pairs. The designs that allowed inclusion of quadratic terms among the predictors performed significantly better than factorial design. Box-Behnken design provided the best results for prediction of retention, but the differences between the central composite, Doehlert and Box-Behnken designs were small. Retention indices could be modeled with much better accuracy than retention times. However, because the errors of predicted tR of closely eluting peaks were highly correlated, models of resolution (Rs) that were based on retention time had errors in the same range as corresponding models based on ECL.     

The Isoinversion Principle—a General Model of Chemical Selectivity

A large number of successful methods for chirality transfer, using either stoichiometric or catalytic chiral auxiliaries, are in use today. However, there is a lack of practical and dynamic selectivity models, i.e. models which take into account the entire reaction sequence, and which allow simple and reliable assessment, optimization and prediction of selectivity in asymmetric syntheses. The models that are available are either too strongly biased to the steric requirement of the particular molecules reacting, but do not go beyond classical considerations of static facial differentiation, or they take a demanding, theoretical approach, which because of its inherent limitations and the great theoretical effort required has not yet found its way into the practical world of the synthetic chemist. The “Isoinversion Principle”, developed on the basis of Eyring's theory, closes this gap. With its aid, the synthetic chemist can determine the characteristic isoinversion temperature T_i for the reaction type of interest from a few temperature-dependent measurements of selectivity parameters. T_i then affords information on interesting questions such as optimization etc. The advantage of this method is that it is useful not only for stereoselectivity, but for any kind of process where selectivity in general (regio-,chemo-, etc) is generated at two or more stages of a reaction sequence, regardless of whether these reactions involve the ground state or a diabatic photoprocess. The present review will demonstrate that this generation of selectivity at two or more stages of a reaction sequence occurs more commonly than is generally thought.     

Optimization of Mobile Phase Composition in Liquid Chromatography—A Survey of Most Commonly Used Chemometric Procedures

Abstract

Chemometrics offers techniques to reduce the number of experiments necessary for obtaining reliable predictions about the optimum conditions for liquid chromatographic separations. This article describes the different chemometric procedures that are currently used for mobile phase optimization. These procedures can be divided in three stages: the selection of the optimization criteria, the choise of the experimental set-up (design) and the evaluation and interpretation of the results. The optimization criteria usually involve resolution (either expressed as α, Rs or P), often analysis time and sometimes column length. The experimental set-up can be either sequential (e.g. simplex algorithm) or simultaneous (e.g. factorial designs). Data can be evaluated either graphically or by mathematical methods. The applicability of the different methods in general and for specific problems is discussed, using examples from the literature.     

Randomization tests to identify significant effects in experimental designs for robustness testing

The screening designs applied in robustness tests are usually fractional factorial or Plackett-Burman designs. Different methods to identify significant factor effects estimated from experimental designs for robustness testing are described. In this paper, the use of randomization tests as a statistical interpretation method is examined and compared with both graphical (half-normal probability plot) and statistical methods, such as the estimation of error based on a priori considered negligible effects and the algorithm of Dong. It was found that all statistical methods usually gave similar results, i.e. the same effects are found to be significant. However, sometimes randomization tests indicate either less or more significant factor effects compared to the other methods, regardless the design size. Both randomization tests and the algorithm of Dong become unreliable when about 50% of the examined factors are significant. In such situation, it is advisable to perform an experimental design from which enough negligible effects can be estimated. The graphical interpretation method did not always succeed in indicating the correct number of significant effects.     

Plate number requirements for establishing method suitability

Establishing the suitability of an analytical system has become a routine requirement in the testing of modern pharmaceuticals. Acceptable parameters that illustrate the system is performing as intended and in an equivalent manner to the original validation are often set at the time of method validation and transferred with the method to the production laboratory. For chromatographic methods, these parameters include--but are not limited to--resolution, tailing, and plate number specifications. Transferring methods is often a seamless transition from research to quality control. However, far too often the quality group receives arguably "overzealous" and strict requirements for the method. More specifically, chromatographic methods get issued with plate number specifications that far exceed the minimum number required to achieve sufficient resolution of the analytes. Presented here is a discussion of the setting of realistic plate number specifications that still maintain the minimum resolution of the chromatographic critical pair.     

毛细管电泳序列分析技术用于在线酶分析研究进展

毛细管电泳技术具有操作简单、样品消耗量少、分离效率高和分析速度快等优势,不仅是一种高效的分离分析技术,而且已经发展成为在线酶分析和酶抑制研究的强有力工具。酶反应全程的实时在线监测,可以实现酶反应动力学过程的高时间分辨精确检测,以更准确地获得反应机制和反应速率常数,有助于更好地了解酶反应机制,从而更全面深入地认识酶在生物代谢中的功能。此外,准确、快速的在线酶抑制剂高通量筛选方法的发展,对加快酶抑制类药物的研发以及疾病的临床诊断亦具有重要意义。电泳媒介微分析法（EMMA）和固定化酶微反应器（IMER）是毛细管电泳酶分析技术中常用的在线分析方法。这两种在线酶分析法的进样方式通常为流体动力学进样和电动进样,无法实现酶反应过程中的无干扰序列进样分析。近年来,基于快速序列进样的毛细管电泳序列分析技术已经发展成为在线酶分析的另一种强有力手段,以实现高时间分辨和高通量的酶分析在线检测。该文从快速序列进样的角度,综述了近年来毛细管电泳序列分析技术在线酶分析的研究进展,并着重介绍了各种序列进样方法及其在酶反应和酶抑制反应中的应用,包括光快门进样、流动门进样、毛细管对接的二维扩散进样、流动注射进样、液滴微流控进样等。     

Comparison of several curve resolution methods for drug impurity profiling using high-performance liquid chromatography with diode array detection

The performance of five curve resolution methods was compared systematically for the identification and quantification of impurities in drug impurity profiling. These methods are alternating least-squares (ALS) with either random or iterative key-set factor analysis (IKSFA) initialisation, iterative target transformation factor analysis (ITTFA), evolving factor analysis (EFA), and heuristic evolving latent projections (HELP). Real and simulated high-performance liquid chromatography diode array detection (HPLC-DAD) data were obtained for drug mixtures containing one main compound and two impurities. The elution order of the main compound and the impurities was varied. Furthermore, resolutions were varied from 0.56 to 3.36 and impurity levels from 30% down to 0.1%. For simulated data, ALS with IKSFA initialisation and HELP perform better than ITTFA and EFA, which perform better than ALS with random initialisation. ITTFA works better than EFA for almost completely separated data, while the opposite is true for moderately or strongly overlapping data. Only ALS with IKSFA initialisation and HELP were found to resolve the required 0.1% level for moderately overlapping data. For real data, comparison of the methods provides similar results. ITTFA performs clearly better than EFA. However, none of the curve resolution methods can identify or quantify impurities at the required 0.1% level. The results for real data are worse than for simulated data because of heteroscedasticity, nonlinearity, and the acquisition resolution of the A/D-converter.     

New peak broadening parameter for the characterization of separation capability in capillary electrophoresis

The influence of separation conditions on peak broadening is usually estimated by the number of theoretical plates. Using the data available in literature and experimental data, it is shown that in pressure‐assisted capillary electrophoresis the plate number is not directly related to the separation capability of conditions used. The experiments at different electrolyte flow velocities demonstrate that a higher plate number (the best separation efficiency) can be obtained with a lower peak resolution. Since ions are separated by electrophoresis due to the difference in electrophoretic mobilities, the peak width in terms of electrophoretic mobility is suggested as a new peak broadening parameter describing the separation capability of the conditions used. The parameter can be calculated using the tailing factor and the temporal peak width at 5% of the peak height. A simple equation for the resolution calculation is derived using the parameter. The advantage of the peak width in terms of mobility over other parameters is shown. The new parameter is recommended to be used not only in pressure‐assisted capillary electrophoresis but also in general capillary electrophoresis when in a number of runs the virtual separative migration distance and separation capability of the conditions used change widely.     

Experimental designs and response surface modeling applied for the optimization of metal-cyanide complexes analysis by capillary electrophoresis

The development of capillary zone electrophoresis (CZE) methods for the determination of metal cyanide complexes in real samples showed some problems, such as the low detection signal of Au (CN)2- and the low resolution between Ni(II) and Fe(II) cyanides in gold processing solutions, and the lack of separation of Pt(CN)4(2-) and Pd(CN)4(2-) in the leachates from automobile catalytic converters. To optimize some analytical parameters, the present study thus focused on the application of experimental designs and multiregression models. The following factors were examined by a two-level factorial design: applied voltage, injection time, detection wavelength, buffer ion, ionic strength and buffer modifiers. For optimization of the CZE method, subsequent response-surface experiments with the important factors were made with the two kinds of leaching solutions. Optimal analytical conditions were obtained in each case, giving good detection signals and resolution for the components of the studied leachates.     

Controlled particle placement through convective and capillary assembly

A wide variety of methods are now available for the synthesis of colloidal particle having controlled shapes, structures, and dimensions. One of the main challenges in the development of devices that utilize micro- and nanoparticles is still particle placement and integration on surfaces. Required are engineering approaches to control the assembly of these building blocks at accurate positions and at high yield. Here, we investigate two complementary methods to create particle assemblies ranging from full layers to sparse arrays of single particles starting from colloidal suspensions of gold and polystyrene particles. Convective assembly was performed on hydrophilic substrates to create crystalline mono- or multilayers using the convective flow of nanoparticles induced by the evaporation of solvent at the three-phase contact line of a solution. On hydrophobic surfaces, capillary assembly was investigated to create sparse arrays and complex three-dimensional structures using capillary forces to trap and organize particles in the recessed regions of a template. In both methods, the hydrodynamic drag exerted on the particle in the suspension plays a key role in the assembly process. We demonstrate for the first time that the velocity and direction of particles in the suspension can be controlled to perform assembly or disassembly of particles. This is achieved by setting the temperature of the colloidal suspension above or below the dew point. The influence of other parameters, such as substrate velocity, wetting properties, and pattern geometry, is also investigated. For the particular case of capillary assembly, we propose a mechanism that takes into account the relative influences of these parameters on the motion of particles and that describes the influence of temperature on the assembly efficiency.     

Dynamic contact angles and hysteresis under electrowetting-on-dielectric

By designing and implementing a new experimental method, we have measured the dynamic advancing and receding contact angles and the resulting hysteresis of droplets under electrowetting-on-dielectric (EWOD). Measurements were obtained over wide ranges of applied EWOD voltages, or electrowetting numbers (0 ≤ Ew ≤ 0.9), and droplet sliding speeds, or capillary numbers (1.4 × 10(-5) ≤ Ca ≤ 6.9 × 10(-3)). If Ew or Ca is low, dynamic contact angle hysteresis is not affected much by the EWOD voltage or the sliding speed; that is, the hysteresis increases by less than 50% with a 2 order-of-magnitude increase in sliding speed when Ca < 10(-3). If both Ew and Ca are high, however, the hysteresis increases with either the EWOD voltage or the sliding speed. Stick-slip oscillations were observed at Ew > 0.4. Data are interpreted with simplified hydrodynamic (Cox-Voinov) and molecular-kinetic theory (MKT) models; the Cox-Voinov model captures the trend of the data, but it yields unreasonable fitting parameters. MKT fitting parameters associated with the advancing contact line are reasonable, but a lack of symmetry indicates that a more intricate model is required.     

Supersaturated designs: set-ups,data interpretation,and analytical applications

For screening purposes, two-level screening designs, such as fractional factorial (FF) and Plackett–Burman (PB) designs, are usually applied. These designs enable examination of, at most, N−1 factors in N experiments. However, when many factors need to be examined, the number of experiments still becomes unfeasibly large. Occasionally, in order to reduce time and costs, a given number of factors can be examined in fewer experiments than with the above screening designs, by using supersaturated designs. These designs examine more than N _SS−1 factors in N _SS experiments. In this review, different set-ups to construct supersaturated designs are explained and discussed, followed by several possible data interpretations of supersaturated design results. Finally, some analytical applications of supersaturated designs are given.     

Programed elution and peak profiles in electric field gradient focusing

Electric field gradient focusing (EFGF) methods have received increased attention in recent years, with potential applications demonstrated by several research groups. In order to move EFGF from the research stage to routine use in application areas, a more detailed understanding of practical aspects of device performance is required. Useful theoretical models for EFGF are available but have not been verified through systematic checks under a variety of conditions. In this paper, we compare modeled and experimental results for an EFGF device with the goal of optimizing the time sequence of voltages applied to the device for maximum resolution of analytes with close electrophoretic mobilities. Measured peak profiles depend strongly on the sequence of voltages applied to the device. We investigate the characteristic behavior of the elution profile under various voltage programs. Rapid voltage drops lead to fast elution of closely spaced protein peaks with narrow widths, whereas a carefully designed voltage program can be used to increase the separation between analytes and achieve higher resolution. Simulated and experimental results demonstrate that the behavior of analyte diffusion at an electric field singularity associated with the transition from the EFGF device to elution capillary can be used to separate analyte peaks which may not be resolved within the EFGF device itself, thereby increasing the achievable resolution of the EFGF technique.     

Global versus local QSPR models for persistent organic pollutants: balancing between predictivity and economy

Experimentally determined data on the key physicochemical parameters for halogenated congeners of persistent organic pollutants (POPs) are available only for a limited number of compounds. In the absence of experimental data, a range of computational methods can be applied to characterize those species for which experimental data is not available. One of the techniques widely used in this context is quantitative structure–property relationships (QSPR) approach. There are two ways to develop the QSPR models: using a more complex global model or fitting a simple local model that covers a specific class of chemically related compounds. The essence of the study was to investigate, if local models have significantly better explanatory and predictive ability than global models with wider applicability domains. Based on the obtained results, we concluded that whenever global models fulfill all quality recommendations by OECD, they would be applied in practice as more efficient ones in state of more time consuming procedure of modeling the particular groups of POPs one-by-one. On the contrary, local models are applicable to solve specific problems (i.e., related to only one group of POPs), when high-quality experimental data are available for a sufficient number of training and validation compounds.     

Determination of allergens in foods

Food allergy presents an emerging challenge to food safety and mandatory labelling of relevant food allergens is still in debate. To date there are only a few validated detection methods available for a limited number of food allergens. Immunological detection of food allergens can involve either human serum IgE or animal antibodies. Enzyme-linked immunosorbent assays are currently the method of choice to determine allergens in various food products. Polymerase chain reaction assays are promising tools for the future. Performance parameters of the methods such as sensitivity, specificity, limit of detection, recovery and reproducibility are reviewed in detail.     

毛细管电泳的手性拆分(文献综述)

根据最近文献,对毛细管电泳在手性拆分领域中的应用和发展进行了评述,包括各种操作模式和各类手性选择剂,进一步评述了手性拆分机理的研究,显示出毛细管电泳是手性拆分的一种高效、快速、简便的分离手段。