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Imad Haidar Ahmad and colleagues at Merck present multifactorial peak crossover (MPC)—a new technique to quickly isolate peaks of interest. Using computer-assisted chromatographic modelling, the separation landscape is mapped and conditions that change peak-elution orders are found. Peaks of interest can be quickly shifted to convenient areas of the chromatogram, dramatically reducing the time spent...

The first efforts for the development of methods for Computer-Assisted Structure Elucidation (CASE) were published more than 50 years ago. CASE expert systems based on one-dimensional (1D) and two-dimensional (2D) Nuclear Magnetic Resonance (NMR) data have matured considerably by now. The structures of a great number of complex natural products have been elucidated and/or revised using...

E&L contains large amount of analytical datasets and chemical information of all impurities associated to each study. Luminata’s ability to be configurable allows it to handle each step within the extractable and leachable process, to store all meta data for each compound found in the study with its corresponding data.

To use network pharmacology and molecular docking technology in predicting the main active ingredients and targets of Qushi Huayu Decoction treatment in Nonalcoholic Fatty Liver Disease and explore the potential mechanisms of its multi-component-multi-target-multi-pathway. Materials and Methods. The main chemical components of QHD were searched using traditional Chinese medicine system pharmacology technology platform and PubChem...

In LC Method Development I to III, we covered the key points of method development: figuring out the project purpose, choosing parameters for screening, and optimizing. How do you assemble all these components into one workflow and manage them efficiently? This webinar puts it all together by showing you how to manage your projects from...

This document provides an overview of the ACD/pKa Classic prediction model and a review of improvements in prediction accuracy including highlights of collaborative projects using proprietary customer data, with excellent results.

This webinar on ACD/MS Fragmenter will show you how to predict mass fragments based on chemical structure and match the prediction to your spectrum. Join us to learn more about how MS Fragmenter can support your spectral interpretation.