Spectroscopic techniques like NMR, IR, Raman, UV/Vis, CD, and mass spectrometry are powerful techniques for analyzing chemical samples. Identifying a molecular structure based on an experimental spectrum is usually done by comparing it to data from scientific literature or databases. Nevertheless, in a modern analytics lab, we often cope with novel, non-standard molecular structures, where assigning spectroscopic features becomes a challenge. Reference data might not be available, or the corresponding spectra are too complex and hard to analyze with typical approaches.
In our talk, we demonstrate how our quantum analytics lab can be used to deliver exactly what is needed: for a given compound, the most important spectroscopic features are predicted, based on robust and generally applicable quantum mechanical simulations. Our computations allow us to interpret and understand the experimental results, and to correlate them to their structural features.
Experience our quantum analytics lab in action, and see how it has helped our partners in pharma to address regulatory questions, deal with IP-related processes, and adhere to budget limits.
