Articles & News

Dr. Andrew “Dru” Namanja, Principal Research Scientist at AbbVie, will explore the potency ranking methods involving both qualitative single-point ligand concentration (Q Score) and quantitative binding affinity (KD), and how the combined utility can be used successfully to drive a Fragment-Based Drug Discovery (FBDD) campaign

The screening and selection of the best chromatographic methods play a pivotal role in the synthetic chemistry pipeline as it allows the obtention of high-purity materials for downstream uses. In this application note, we delve into the essential factors and consideration involved in evaluating chromatographic methods through a scoring approach.

 

Reaction optimization is crucial for achieving efficient syntheses of final products or intermediates. While different approaches can reduce the number of trial reactions, effectively handling and analyzing LCMS data to quantify components remains a significant challenge…

We've released Mbook 3.1.1, which brings a set of improvements. We have fine-tuned the user experience by addressing typical issues and adding a few enhancements. So, get ready to enjoy a smoother and more refined software experience with this latest update.

We’re introducing Mnova 14.3.3, a recent release that brings a touch of freshness to the table. Just a couple of months after our previous version, this […]

Gavin Shear (Mestrelab) describes expert tools to the desktop user, with game changing enhancements in peak picking, spectral display, and spectral substraction using Mnova MSChrom.

No automation exists in a vacuum. Inputs and outputs to the process (or rather the ease with which these connections can be achieved) can make or break the overall automation. There is no point having a wonderful automation processing 10,000 samples if all the results then need to be transcribed manually into a corporate database!

Experts working with chemistry – from small molecules right up to macromolecules and from pure compounds through to complex mixtures – know that the analytical data acquired by the instruments is empty and meaningless without analysis and interpretation.

Agreeing in principle that there are benefits to data automation is one thing, yet in practice, changing standard processes to implement such automations can be a much more complicated decision to make, especially when lacking the internal expertise to take care of such changes.