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ACD/Labs Blog

From new instruments and software to the rise of the digital lab, the landscape of analytical chemistry data is constantly evolving. To stay on top of trends, we launch a comprehensive survey every few years focused on analytical chemistry data and its management. Here's what we learned.

1H NMR is the go-to technique to help identify or confirm the structure of organic compounds. A solution-state proton spectrum is relatively fast to acquire and a lot of information about the structure of a compound can be deduced from it. With centuries of combined experience in NMR data interpretation, we thought we’d share the basics of analyzing solution-phase 1H NMR spectra in this blog.

UPDATED Oct. 21st, 2021: We have found that a number of common misconceptions exist about validated environments. Many arise because previous deployments of software accompanied the installation of new hardware, or have involved informatics systems that are the source of data and reports submitted directly to regulatory authorities. Here we clear up some of the grey areas that seem to have become industry myths.

The pharmaceutical industry has renewed its interest in HTE these last few years. Leaders see it as a way to get medicines to patients faster, but they’re also attracted by the sheer quantity of data generated in parallel experiments. How and where should HTE be set up for maximum success? Read this blog for questions that should be considered.

Most of us who’ve worked in chemistry know about logP. The partition coefficient makes it into Lipinski’s rule of five and most post-secondary educations. But when it comes to logP, we mean one exact chemical structure. If a compound ionizes, it’s not the same structure. And since most compounds investigated in pharmaceutical and pharmacological research contain ionizable sites, it’s not logP we should be concerned about, but logD.

Andrew Anderson, VP of Innovation & Informatics Strategy, recently spoke with Scientific Computing World about some of the challenges associated with data standardization and how the value of data can be realized. Here’s an overview of what he covered...