PITTCON® 2007
Chicago, IL, USA
February 26–March 1, 2007
Booth #: 1055 - See map for location of booth
View ACD/Labs Poster Schedule
ACD/Labs' Talk Schedule |
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| SUNDAY, FEBRUARY 25, 2007 |
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| Title: | n-Dimensional MAP Chromatography: Virtual Resolution of Components Based on Orthogonal Chromatographic Methods |
| Authors: | Mike McBrien, Andrey Vazhentsev, Alexey Galin, Vitaly Lashin (ACD/Labs) |
| Session Title: | LC-MS in Environmental, High-Throughput and Other Applications |
| Time: | 3:15 PM |
| Location: | Room 504BC |
| Abstract #: | 170-7 |
| Abstract: | The primary benefit of the many forms of two-dimensional chromatography has been the ability to utilize multiple selectivities independently, resulting in a resolving power unattainable in one-dimensional separations. Applications of chromatography with greater dimensionality than two have rarely been reported, for many reasons, including theoretical and practical issues.
Recently, chemometric techniques for chromatographic peak matching across multiple chromatographic runs have created the opportunity to exploit complementary retention mechanisms using conventional instrumentation. Hyphenated detection techniques (i.e., LC/UV/MS) have been shown to be effective in tracking chromatographic peaks in the same sample across different chromatograms when used in conjunction with chemometric techniques such as Mutual Automated Peak matching (MAP). When these chromatograms have been collected under orthogonal chromatographic conditions, 2 components that co-elute under one system have an excellent chance of being at least partially resolved from each under the second system. The components, in fact, can show zero resolution in any of the individual runs and still be "virtually resolved", provided that in at least one experiment, coelution with the exact same component does not occur. Obviously the chance of this coelution occurring decreases considerably with each additional experiment, provided that the new experiment can be expected to display markedly different chromatographic behavior. The number of "dimensions" that can be applied to the problem is limited only by the sample size, and the number of orthogonal condition sets that can be designed.
The benefits of this approach, called n-Dimensional MAP Chromatography (NDMC), over conventional multidimensional chromatography are clear—standard instrumentation can be used, and the data collected is considerably smaller than for conventional multidimensional chromatography, while still containing spectral information for each component. This paper will discuss the application of three- and six-dimensional NDMC to various complex samples, discussing practical limitations to the approach in general, as well as to the extraction of spectral and quantitative data.
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| MONDAY, FEBRUARY 26, 2007 |
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| Title: | IR and Raman Databases for the Analysis of Polymers |
| Authors: | Michael Boruta (ACD/Labs), John M. Chalmers (VS Consulting) |
| Session Title: | Spectroscopic Techniques for Polymer Characterization |
| Time: | 1:30 PM |
| Location: | Room 405A |
| Abstract #: | 630-1 |
| Abstract: | Both commercially available databases and user created databases can be a valuable tool to assist in the analysis and identification of polymers. The creation and use of these databases including such features as the resolution of the data, the technique used to acquire the spectra, the quality of the spectra and any meta data associated with the spectra can have an impact on the quality of the information derived. This paper will examine some of the potential problems and solutions available when using these databases to aid in the analysis of polymers. |
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| Title: | IR and Raman Spectrum: Structure Correlation in the Analysis and Identification of Polymers |
| Authors: | John M. Chalmers (VS Consulting), Michael Boruta (ACD/Labs) |
| Session Title: | Spectroscopic Techniques for Polymer Characterization |
| Time: | 1:50 PM |
| Location: | Room 405A |
| Abstract #: | 630-2 |
| Abstract: | Spectrum - structure correlations can provide information on the general class of a material being analyzed as well as some of the finer details used to distinguish similarities within a class. Sources of knowledge for these correlations will be discussed along with some example cases. |
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| TUESDAY, FEBRUARY 27, 2007 |
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| Title: | The Impact of LC/MS Componentization in the Low Level Extraction of Impurities and Related Compounds |
| Authors: | Mark Bayliss (ACD/Labs) |
| Session Title: | Identification of Impurities Using Liquid Chromatography Hyphenated with Tandem Mass Spectrometry - Organized Contributed Session |
| Time: | 9:30 AM |
| Location: | Room 405A |
| Abstract #: | 950-4 |
| Abstract: | "Why is it that as analysts we still invest huge numbers of hours into the extraction of potential impurities from LC/MS and fragment related data by having to perform manual data work-up? Is this not a perfect situation for software to provide a solution?"
Ensuring coverage of all potential impurities both in terms of extraction and identification forms a complex interdependency between the need to determine both molecular weight and obtain sufficient fragmental information to be able to support structure identification.
The potential to perform extraction and determination of molecular weight, obtain fragment and neutral loss data in a single pass experiment using an increased level of source voltage offers significant opportunities for automation by software. A similar approach applied to metabolism data by Bateman et al., and impurities by Rourick et al, provides an insight that from an instrumental and concept approach, this mode of data acquisition can be useful in screening type environments. In extending this concept, our group wanted to consider the feasibility of automating the extraction and identification of potential impurities using a software approach to auto-componentization, fragment extraction and elucidation. In this presentation we discuss the challenges of auto-componentization of MS data that ensure the accurate detection of appropriate fragment ions to enable the extraction of closely eluting impurities. In particular we were particularly interested in the potential to perform data extraction and elucidation of potential impurities eluting within the elution space of the parent drug substance. We also discuss the co-detection of related fragments and auto-calculation of neutral losses that provide a powerful multi-dimensional screening method with potential for downstream software automation. |
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| Title: | 24-Hour Creation of Chromatographic Prediction Systems |
| Authors: | Mike McBrien, Vitaly Lashin, Alexey Galin, (ACD/Labs) and David S. Bell (Supelco/Sigma-Aldrich) |
| Session Title: | Method Development in Chromatography |
| Time: | 10:45 AM |
| Location: | Room 504A |
| Abstract #: | 1050-3 |
| Abstract: | For more than 20 years, there have been efforts to create a system to predict the elution of compounds based on their chemical structure. Chromatographic systems have become more robust, and computers have become faster, so that even gradient and mixed-mode retention systems can be modeled. These predictions of elution data for new compounds can be applied to the selection between generic methods for preparative scale work or purity estimation, starting points for method development, or even retention time-based confirmation of chemical structures. One of the requirements for the creation of a prediction system is the collection of elution data for a sufficient number and diversity of relevant compounds for each targeted chromatographic method. While the ideal approach is to collect this data during the normal course of experimentation in order to generate a knowledgebase without the need for extra measurements, this can become a barrier to the adoption of a system of prediction; for some laboratories, the collection of sufficient data can take months or longer.
With the recent development of chemometric tools for the extraction of peak data from LC/MS datasets, there is a new opportunity to perform efficient extraction of hundreds of sets of retention data in a limited number of chromatographic injections, and with practically no manual evaluation of data. The approach involves the injection of extremely complex samples that are then deconvolved using chemometrics. It is now possible to collect elution data for a very large number of compounds and build a prediction model for a set of orthogonal chromatographic methods in less than a single day of combined experimentation and computation, with practically no user involvement.
Practical application of this work will be discussed, as well as the design of compound training sets and performance of the resulting prediction algorithms. |
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| Title: | A New Deterministic Variable Selection Method for Multivariate Regression Analysis |
| Authors: | Michael Boruta, Michel Hachey (ACD/Labs) and A. Y. Bogomolov (European Molecular Biology Laboratory) |
| Session Title: | Chemometrics |
| Time: | 1:30 PM |
| Location: | Room 504A |
| Abstract #: | 1310-1 |
| Abstract: | A new approach for the pre-selection of wavelength, to be used in conjunction with Partial Least Squares (PLS) or other multivariate regression techniques, will be presented. In a first step, this variable selection method makes use of the purity function, originally suggested in the SIMPLe-to-use Interactive Self-modeling Mixture Analysis (SIMPLISMA) algorithm, to map out the regions of potentially influential variables. The selected intervals are then individually tested using multivariate regression technique modeling and prediction, and an optimal subset of variables is obtained. The algorithm is simple and intuitive and does not rely on iterative variable searches.
The method was tested on a set of infrared protein spectra in order to improve the quantitative determination of the fractions of two secondary structure elements, A-helices and B-strands (B-sheets) in the protein polypeptide chain. Comparable results to those obtained through interval PLS (iPLS), an exhaustive search-based algorithm, were achieved in this study. Our method was shown to be particularly beneficial in combination with variable weighting by their inverse standard deviation. The proposed method shows excellent agreement with prior experimental interpretation, and its design reduces wavelength selection instability due to noise.
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| WEDNESDAY, FEBRUARY 28, 2007 |
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| Title: | Automating the Development of Liquid Chromatographic Methods for Impurity and Stability Samples Using High Sensitivity, High Resolution LC/MS |
| Authors: | Michael Swartz, Michael D. Jones (Waters) and Mike McBrien (ACD/Labs) |
| Session Title: | LC-MS Pharmaceutical/Drug Discovery/Proteomics & Genomics |
| Time: | 8:50 AM |
| Location: | Room 501A |
| Abstract #: | 1650-2 |
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| Title: | Sample Stability, Composite Samples, and Chromatographic Method Development |
| Authors: | Mike McBrien (ACD/Labs), Rudy Sneyers, and Willy Jannsens (Johnson & Johnson) |
| Session Title: | Application of Liquid Chromatography and Tandem Mass Spectrometry in the Analysis of Active Pharmaceutical Ingredients |
| Time: | 10:05 AM |
| Location: | Room 501BC |
| Abstract #: | 1560-5 |
| Abstract: | A common problem in chromatography is the development of methods for analytes that span multiple physical samples. The samples might be related, such as forced degradation experiments conducted under different sets of conditions. Or, the samples might be related to known analytes that must be detected even when they are not present in every sample, along with any unknown analytes associated with the sample in question. While it might seem logical to physically mix samples and perform chromatography on the mixture, this approach has the disadvantage of impairing the detection of low-level components. In addition, this approach complicates the process of peak tracking for method modeling. In the ideal case, multiple injections are made for each set of conditions, each using one subsample (one of several samples containing at least some of the components for the overall system). However, this "composite sample" approach to method development has the drawback of requiring a large number of experiments, with resulting delays due to data interpretation and data collection. Traditionally there usually hasn't been enough time to rigorously examine these kinds of samples.
With the advent of faster chromatography and automated data extraction, it is now possible to apply the composite sample approach to chromatographic method development extremely efficiently. While there must be at least one datafile for each subsample under each set of conditions, method development project management and chemometric component extraction tools can streamline the data extraction process considerably.
The advantages of this approach will be illustrated with several examples, including the daunting case of the optimization of 6 chromatographic variables for forced-degradation samples containing a large number of components, spanning 6 subsamples. |
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| Title: | Grouping of High Throughput XRPD Spectra |
| Authors: | Michael Boruta, Michel Hachey (ACD/Labs) |
| Session Title: | Material Science |
| Time: | 1:50 PM |
| Location: | Room 502A |
| Abstract #: | 1980-2 |
| Abstract: | Grouping similar spectra is a key part of the analysis of high-throughput polymorph analysis. But even experienced scientists can find it difficult to identify unique patterns characteristic of a new solid form. This can be especially so in high-throughput screening, where the number of spectra generated can quickly cause data management and analysis bottlenecks. Indeed, the classification of new species patterns is especially complicated by the fact that wells can contain several species—unreacted API, residual liquids, solvates, hydrates, polymporphs—and give multicomponent spectra. What strategies can be used for classifying, ranking, and identifying the presence of one form or another in a sample well? The typical approach is to use an algorithm that compares a spectra to every other spectra providing a match quality number. In this talk, we will explore different classical comparison algorithms that can be used with x-ray powder diffraction screening. |
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