ACD/Labs Releases 2025 Structure Elucidation & Verification Report

On February 6, ACD/Labs released its 2025 Structure Elucidation and Verification Report, discussing how informatics trends have shifted since 2022. The report, which was distilled from comments gathered from attendees at ACD/Labs’ annual virtual symposium in Q4 2024, featured presentations from organizations such as Bristol Myers Squibb (BMS), the U.S. Food and Drug Administration (FDA), Corteva Agriscience, Sutro Biopharma, and Shimadzu, among others (1).

Thin layer chromatography | Image Credit: © ggw - stock.adobe.com

As analytical chemists face increasing testing volumes, without expanded staffing capabilities, many are investigating automating sample handling, data processing, and prediction (AI/ML-based) model development. Workflow automation and high-throughput analyses have been implemented to address the increasing volume and complexity of analytical samples. There are a couple of areas that scientists are focused on automating. Hyphenated chromatography techniques, such as liquid chromatography–mass spectrometry (LC–MS) and liquid chromatography–ultraviolet mass spectrometry (LC–UV/MS), for example, remain a top priority. More than 70% of respondents selected these processes as having potential for automation. There has also been interest in automating mass spectrometry (MS) and optical data analyses. While 60% of these groups continue carrying out manual structure verification, automated verification by nuclear magnetic resonance (NMR) is reported to be an efficiency driver for both subject experts and synthetic/medicinal chemists in open-access laboratories.

Improving data quality and accuracy is vital because it ensures data can be properly used in machine learning and AI-powered structure elucidation. The report highlighted the importance of high-quality empirical data for analyzing, modeling, and predicting, which can optimize accuracy and efficiency, especially in novel chemical spaces. All-in-one software can streamline data analysis and management from different techniques, aiding knowledge transfer and minimizing the risk for human errors, such as in transcription.

The report also discussed the challenges of analyzing and verifying complex molecules, showing how tailored approaches are needed to ensure accurate high-throughput workflows. Emine Sager, an analytical scientist from Novartis, shared how her company’s ASV workflow first records a proton spectrum, which is analyzed using an in-house script to optimize subsequent ¹³C and 2D NMR experiments. All but 4% of the samples had experimental data applicable to their ASV system. The structure was accurately verified (true positive) or rejected (true negative) for 40% and 15% of samples respectively. While they acknowledged there was room for improvement, the ASV system proved sufficiently accurate and able to provide benefits without significant risk increases.

The report also highlighted the importance of combining different analytical methods to improve structure elucidation and verification. Kristof Cank, an analytical scientist with Sutro Biopharma, described how his team use various analytical methods, such as LC–MS, NMR and two-dimensional LC (2D-LC), for purity analysis, impurity identification, and structural elucidation of linkers, warheads, leads, and side products in their antibody-drug conjugate (ADC) development process. Richard Lewis, principal scientist of AstraZeneca, also believes in combining data for efficient and accurate structure verification.

“I think the future is likely to be a different mix of different approaches. So not just one bit of software, one bit of data, but putting lots of different software and data together to get an answer,” he said. (1).

References

(1) 2025 Structure Elucidation & Verification Report. ACD/Labs 2025. https://www.acdlabs.com/resource/advances-challenges-and-future-directions-in-structure-characterization/ (accessed 2025-2-7)

(2) Homepage. ACD/Labs 2025. https://www.acdlabs.com/ (accessed 2025-2-10)