Related presentations, posters, and scientific talks from this event have been posted here for your reference. Please click the associated link to download.
|A New Universal Mass Spectrometry Data Analysis Software Suite||Graham A. McGibbon et al||View Presentation|
|ACD/Spectrus DB Release Completes ACD/Labs' Next Generation Cheminformatics Platform||ACD/Labs||ACD/Spectrus DB Release Completes ACD/Labs' Next Generation Cheminformatics Platform - March 2013|
|ACD/Spectrus: Breathing Life into your Analytical Data||Ryan Sasaki||View Presentation|
|Good Practices in Spectral Databasing and Knowledge Management||Michael Boruta||View Presentation|
Booth # 1516
Title: ACD/Spectrus: Breathing Life into your Analytical Data
Speaker: Ryan Sasaki
Date: Monday, March 18, 2013
Time: 2:00–3:00 PM
Location: Room 103B
Title: Good Practices in Spectral Databasing and Knowledge Management
Authors: Michael Boruta
Session: 460—Molecular Spectroscopy Advances (Half Session)
Abstract Number: 460–4
Date: Monday, Mar. 18, 2013
Time: 9:00 AM Abstract: View Abstract
For the past several years there has been a growing acknowledgement by senior management of the value of sharing existing chemical and spectroscopic knowledge across an organization. This acknowledgement along with in increasing number of software tools available to accomplish some form of knowledge sharing has led a growing number of organizations considering how they might implement a solution. Generally this consideration takes the form of looking at the available software products and how they might fit within an organization.
While selection of the appropriate software is an important step in the process of creating a corporate knowledgebase, there are a number of other considerations which can be just as important if not more important than the actual software products. These issues range from what corporate data gets saved, to how to motivate individuals to use or contribute to the knowledge management system. Based on several decades of experience creating databases and helping others initiate their database strategies, this talk will look at a number of key issues which should be considered prior to starting a project and how they can impact the development and use of an in-house knowledge management system.
Title: Avoiding Bosutinib: A Case of What Could Have Been?
Authors: Ryan Sasaki, Graham A. McGibbon, Patrick D. Wheeler, and Philip E. Keyes
Session: 480—Pharmaceutical: Other Analytical Methods
Abstract Number: 480–7
Date: Monday, Mar. 18, 2013
Time: 10:15 AM Abstract: View Abstract
In high pace, minimal operating cost environments, everyday decisions and conclusions are made based on a limited number of datapoints. Our review of a recent high-profile error raises questions about the validity and accuracy of routine analytical data interpretation and to what degree automated and computerized routines can help avoid catastrophic mistakes.
The story of Bosutinib, a third generation tyrosine kinase inhibitor, has been highly publicized based on the widespread commercial shipment of an imposter compound1,2. This example prompts questioning as to what analytical chemistry technologies could have been used to proactively expose the imposter early in the research process.
In this study we have obtained the commercial NMR data for the authentic and imposter bosutinib compounds and have tested the applicability of computer assisted structure verification and elucidation routines. This study reveals instances where automated software routines could have been used to clearly expose the presence of the imposter compound and validated the identity of the true compound.
1. Halford, B., Bosutinib Buyer Beware, Chemical Engineering and News, May 11, 2012. http://cen.acs.org/articles/90/web/2012/05/Bosutinib-Buyer-Beware.html
2. Richards, S., Bogus Isomer Vendors Identified, The Scientist, May 25, 2012. http://the-scientist.com/2012/05/25/bogus-isomer-vendors-identified/
Title: A New Universal Mass Spectrometry Data Analysis Software Suite
Authors: Graham A. McGibbon, Alexey Aminov, Vitaly Lashin, Andrei Vazhentsev
Session: 810—New Instrumentation/Software with Mass Spectrometry
Abstract Number: 810–3
Date: Monday, Mar. 18, 2013
Time: 2:40 PM Abstract: View Abstract
Software is a crucial aspect of mass spectrometry data processing, interpretation, information storage and reporting. Key uses of hyphenated mass spectrometry data are sample comparisons and structure characterizations. Software tools are vital for finding components using mass, or molecular formula or even chemical structures and for interpreting fragmentation. Handling data irrespective of its hardware origin offers value considering the existing variety of mass spectrometry instruments. Analyses often benefit from insights derived via techniques like NMR or optical spectroscopies.
Accordingly, we describe a newly developed software package that handles data from various mass spectrometry instruments, including other chromatographic detectors. It handles structures and has features facilitating small molecule anlyses and characterizations and can handle NMR and IR spectroscopy data.
A pre-commercial release version of a new mass spectrometry software suite was capable of handling files from a variety of instrument vendors and hardware technologies. Several processing functions were triggered simply by data import and the introduction of molecular structures. Familiar tools performed operations on chromatographic traces including zooming, peak detection and generating average spectra from LC/UV, LC/MS and GC/MS data. The interface made innovative uses of color coding and a Table of Components to accommodate molecular structure, formula, monoisotopic mass and/or simply a name. Retention time and peak areas were automatically added when a component was manually assigned to a chromatographic peak. Algorithms also extracted ion chromatograms for a mass, formula or structure. The software improved ease-of-use for some known component finding algorithms. For high resolution accurate mass spectral data additional features could confirm or predict molecular formulae or ion fragmentation.