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Articles & Third-Party References

Recent journal articles and third-party references about ACD/Labs from the last year

Informatics for QbD
Dec 12, 2017
A. Anderson
Chemistry & Industry
Andrew Anderson looks at some of the challenges that can be addressed with informatics solutions.
A. Anderson. (2017). Informatics for QBD. Chemistry & Industry, 81: 34–35

Automated Comparative Metabolite Profiling of Large LC-ESIMS Data Sets in an ACD/MS Workbook Suite Add-in, and Data Clustering on a New Open-Source Web Platform FreeClust
Dec 05, 2017
A. Božičević, M. Dobrzyński, H. de Bie, F. Gafner, E. Garo, M. Hamburger
Analytical Chemistry
The technological development of LC-MS instrumentation has led to significant improvements of performance and sensitivity, enabling high-throughput analysis of complex samples, such as plant extracts. Most software suites allow preprocessing of LC-MS chromatograms to obtain comprehensive information on single constituents. However, more advanced processing needs, such as the systematic and unbiased comparative metabolite profiling of large numbers of complex LC-MS chromatograms remains a challenge. Currently, users have to rely on different tools to perform such data analyses. We developed a two-step protocol comprising a comparative metabolite profiling tool integrated in ACD/MS Workbook Suite, and a web platform developed in R language designed for clustering and visualization of chromatographic data. Initially, all relevant chromatographic and spectroscopic data (retention time, molecular ions with the respective ion abundance, and sample names) are automatically extracted and assembled in an Excel spreadsheet. The file is then loaded into an online web application that includes various statistical algorithms and provides the user with tools to compare and visualize the results in intuitive 2D heatmaps. We applied this workflow to LC-ESIMS profiles obtained from 69 honey samples. Within few hours of calculation with a standard PC, honey samples were preprocessed and organized in clusters based on their metabolite profile similarities, thereby highlighting the common metabolite patterns and distributions among samples. Implementation in the ACD/Laboratories software package enables ulterior integration of other analytical data, and in silico prediction tools for modern drug discovery.
(2017). Anal Chem. 89(23): 12682–12689

Achieve QbD by Managing Impurity Data
Nov 15, 2017
A. Anderson, G.A. McGibbon, S. Bhal
Genetic Engineering & Biotechnology News
This article will discuss how QbD requirements impact risk assessment, process assessment, material assessment, documentation, and traceability, and how these functions can be addressed using informatics software. One of the challenges in applying QbD principles in process development is establishing an acceptable Quality Target Product Profile (QTPP).
(2017). Genetic Engineering & Biotechnology News. 37(20)

Outsourcing Pharma: Quality-by-design: How to mitigate risk in drug development
Nov 13, 2017
M. Fassbender
Joe DiMartino, solution manager, Luminata, at ACD/Labs speaks to at AAPS 2017 in San Diego, CA, about the evolving regulatory landscape and how companies can leverage QbD to help mitigate risk in drug development.
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Qualitative screening for new psychoactive substances in wastewater collected during a city festival using liquid chromatography coupled to high-resolution mass spectrometry
Oct 01, 2017
A. Causanilles, J. Kinyua, C. Ruttkies, A.L.N. van Nuijs, E. Emke, A. Covaci, P. de Voogt
The inclusion of new psychoactive substances (NPS) in the wastewater-based epidemiology approach presents challenges, such as the reduced number of users that translates into low concentrations of residues and the limited pharmacokinetics information available, which renders the choice of target biomarker difficult. The sampling during special social settings, the analysis with improved analytical techniques, and data processing with specific workflow to narrow the search, are required approaches for a successful monitoring. This work presents the application of a qualitative screening technique to wastewater samples collected during a city festival, where likely users of recreational substances gather and consequently higher residual concentrations of used NPS are expected. The analysis was performed using liquid chromatography coupled to high-resolution mass spectrometry. Data were processed using an algorithm that involves the extraction of accurate masses (calculated based on molecular formula) of expected m/z from an in-house database containing about 2,000 entries, including NPS and transformation products. We positively identified eight NPS belonging to the classes of synthetic cathinones, phenethylamines and opioids. In addition, the presence of benzodiazepine analogues, classical drugs and other licit substances with potential for abuse was confirmed. The screening workflow based on a database search was useful in the identification of NPS biomarkers in wastewater. The findings highlight the specific classical drugs and low NPS use in the Netherlands. Additionally, meta-chlorophenylpiperazine (mCPP), 2,5-dimethoxy-4-bromophenethylamine (2C-B), and 4-fluoroamphetamine (FA) were identified in wastewater for the first time.
Chemosphere, 184: 1186–93

Applying QbD in Process Development
Sep 01, 2017
A. Anderson, G.A. McGibbon, S.K. Bhal
Over the past few years, global regulatory authorities have been raising the expectation of incorporating quality by design (QbD) into pharmaceutical development. While QbD offers many important long-term benefits, these expectations are having a dramatic impact on product development groups and their supporting corporate informatics infrastructure. This article discusses how QbD requirements for risk assessment, process assessment, material assessment, documentation, and traceability can be addressed with informatics, using development of an impurity control strategy as an example.
Pharmaceutical Technology, 2017(4):s28-s30, s34

Targeted Dereplication of Microbial Natural Products by High-Resolution MS and Predicted LC Retention Time
Apr 26, 2017
J. Chervin, M. Stierhof, M.H. Tong, D. Peace, K. Østnes Hansen, D.S. Urgast, J.H. Andersen, Y. Yu, R. Ebel, K. Kyeremeh, V. Paget, G. Cimpan, A. Van Wyk, H. Deng, M. Jaspars, and J.N. Tabudravu
Journal of Natural Products
A new strategy for the identification of known compounds in Streptomyces extracts that can be applied in the discovery of natural products is presented. The strategy incorporates screening a database of 5555 natural products including 5098 structures from Streptomyces sp., using a high-throughput LCMS data processing algorithm that utilizes HRMS data and predicted LC retention times (tR) as filters for rapid identification of known compounds in the natural product extract. The database, named StrepDB, contains for each compound the structure, molecular formula, molecular mass, and predicted LC retention time. All identified compounds are annotated and color coded for easier visualization. It is an indirect approach to quickly assess masses (which are not annotated) that may potentially lead to the discovery of new or novel structures. In addition, a spectral database named MbcDB was generated using the ACD/Spectrus DB Platform. MbcDB contains 665 natural products, each with structure, experimental HRESIMS, MS/MS, UV, and NMR spectra. StrepDB was used to screen a mutant Streptomyces albus extract, which led to the identification and isolation of two new compounds, legonmaleimides A and B, the structures of which were elucidated with the aid of MbcDB and spectroscopic techniques. The structures were confirmed by computer-assisted structure elucidation (CASE) methods using ACD/Structure Elucidator Suite. The developed methodology suggests a pipeline approach to the dereplication of extracts and discovery of novel natural products.
J. Nat. Prod., 2017, 80 (5): 1370-1377

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