LIMS & Lab Automation


It’s Not Too Late to Automate Your Structure Verifi cation Sarah Srokosz, ACD/Labs


Analytical Experiments are Carried Out to Answer, Essentially, One Question: What Is In My Sample?


There is nuance based on the work being done - lead optimisation in discovery, impurity control in process development, forced degradation studies, or manufacturing QA/QC. Results may be used to better understand a material, to understand a process, or to reveal its limitations - but the high-level question is still, ‘what is it?’ Every day, scientists collect vast quantities of NMR, LC/MS, FTIR, Raman spectroscopy, and a variety of spectroscopic and analytical techniques’ data to verify or elucidate the identity of chemical (or biochemical) structures and mixture components. Enhancing effi ciency in this pursuit thus offers signifi cant gains to individual scientists and their organisations.


Boosting Scientists Workfl ows Across Industries


ASV can benefi t a wide variety of fi elds in which structure verifi cation plays a signifi cant role. This includes the pharmaceutical industry from drug discovery, through to development, and even manufacturing QA/QC. It’s also valuable in analytical labs like CROs and environmental testing, as well as regulatory agencies, academic institutions, and patent offi ces.


At Novartis, Associate Director/Chemical Structure Investigation Group Lead, Dorina Kotoni reported that her team have implemented ACD/Labs ASV by NMR, for molecules smaller than 800 Daltons across research and development. In their workfl ow, analysts review the generated results which are then reported directly to the chemist, to a database, or to an ELN record, based on their needs.


She reports that the team has saved a signifi cant amount of time from their ‘ASV engine’ deployment. She estimates that for manual verifi cation an experienced analyst, on average, would spend 20 minutes on processing and interpreting NMR data per submission. When the ASV engine successfully delivers a structure confi rmation result, the analyst only spends a minute or two on review, which represents a 90% time savings. When minor manual corrections are necessary, the analyst may spend 5 minutes on the analysis - less than half the time required for manual analysis. Even when ASV does not generate a result or data processing is incomplete, it still saves the analyst time “because the peak picking is done”, Kotoni adds.


“After 2 years we are seeing 60–65% of successful automated verifi cations and the software is learning as we feed more data into it… Even failed verifi cations save the analysts time because they don’t have to process the datasets from scratch.”


Dorina Kotoni, Novartis


What is Automated Structure Verifi cation?


Automated structure verifi cation (ASV) generally refers to the process of using computational algorithms and software tools to assess the match between a proposed chemical structure and corresponding analytical data.


ASV software analyses experimental data, such as NMR spectra, and compares it with the proposed molecular structures. By applying various algorithms and rules, these tools can detect inconsistencies, errors, or ambiguities in the proposed structures. This verifi cation process saves scientists time in routine analyses, can help with throughput, and reduces the risk of human bias, as we analysts subconsciously try to fi t data to the expected structure.


Cut Down on Data Needed for Structure Determination


Structure determination requires the use of data from a variety of analytical techniques. The amount of data required also depends on how much structural information you have—is it a novel compound requiring elucidation or are you verifying the presence of an expected structure? The exact combination of techniques also depends on the type of compounds you anticipate are present.


We surveyed the audience of approximately 400 scientists from discovery and development who attended our Structure Elucidation & Verifi cation Symposium to learn more about what analytical techniques they’re using to identify chemical structures. We found the hierarchy of techniques to be high-resolution mass spectrometry (HRMS), followed by 1D 1H and /or 13C NMR, then more time-consuming 2D NMR, IR, and fi nally, other experiments such as LC/MS, UV/Vis, and Raman spectroscopy data.


In addition to time savings gained in data processing and analysis, ASV also presents the opportunity to save time and resources by cutting down on the number of experiments needed to confi dently verify a structure.


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