New report reveals key trends in chemical structure elucidation and verification

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Mass spectrometry & spectroscopy


New report reveals key trends in chemical structure elucidation and verification


A new report on Structure Elucidation & Verification has been released, offering insights into shifting trends and strategies from leading R&D organisations. Compiled from the expertise of hundreds of researchers at ACD/Labs’ annual virtual symposium held in late 2024, the report outlines developments since 2022 and highlights how organisations are positioning themselves for success in 2025 and beyond.

Presentations from organisations such as Novartis, AstraZeneca, Bristol Myers Squibb (BMS), Medtronic, Sanofi, the US Food and Drug Administration (FDA), Corteva Agriscience, Sutro Biopharma, and Shimadzu explored challenges, goals, and the role of advanced spectroscopic technologies in enhancing productivity and efficiency.

With analytical teams facing increased demands without proportional growth in capacity or staffing, the report underscores a rise in sample handling automation, automated data processing, and the development of AI/ML-based predictive models. Stakeholders emphasised that any productivity gains must be balanced with maintaining high data integrity, quality, and result accuracy.

Workflow automation and high-throughput analysis are becoming standard across R&D sectors to manage growing sample volumes and complexity. Hyphenated chromatography techniques (LC/MS, LC/UV/MS) are a top automation priority, with over 70% of respondents indicating they either have automated or plan to automate this data type. Interest in automating NMR, MS, and optical data analyses has also grown. Notably, while 60% of respondents still rely on manual structure verification, automated structure verification by NMR (ASV) is increasingly recognised for boosting efficiency among NMR experts and chemists in open-access labs.

The focus on improving data quality and accuracy is pivotal, not only to enhance the benefits of automated workflows without increasing risk but also to ensure reliable data inputs for machine learning and AI-driven structure elucidation.

The report also explores the multi-technique approach many labs use for structure characterisation. Integrated software solutions that support entire workflows or centralise data in one interface reduce transcription errors, enhance confidence, and empower analysts.

“We dedicate a significant amount of time to structure elucidation and verification, but no other conference or meeting focuses solely on this area,” said a symposium attendee and past speaker from a leading pharmaceutical company. “It’s invigorating to exchange challenges and successes with industry peers and leave with new ideas to improve both efficiency and confidence in our work.”

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