Digitalization and AI Enablement Across Drug Discovery and Development
From analytical data management to automated structure verification, explore practical approaches to digitalization and AI in pharmaceutical R&D.
Digitalization and AI initiatives depend on accessible, reusable scientific data and workflows that support informed decision-making. Explore industry perspectives on the challenges of R&D digitalization alongside real-world examples of multi-technique analytical data processing and automated structure verification. These resources offer practical ideas for reducing manual work, improving data access, and building a stronger foundation for AI-enabled research and development.
R&D Digitalization Benchmark Report
Drawing on insights from more than 100 global organizations, this report examines the gap between AI ambitions and the data digitalization needed to support them. Explore digitalization maturity across R&D and why centralizing scientific data is important for future discovery and development.
DownloadDigitalization and AI-Enablement in R&D (webinar summary)
What does it take to move R&D digitalization and AI ambitions into practice? Read insights from digitalization leaders at Pfizer, AbbVie, Bristol Myers Squibb, and Revvity Signals on tackling data challenges, prioritizing high-value use cases, and building a foundation for AI-enabled research.
DownloadAutomated Verification of Small Molecule Structures at Sanofi
Discover how Sanofi is applying automated structure verification to reduce repetitive NMR analysis. This case study explores its LIMS-integrated workflow and how automated checks against reference or predicted spectra can help scientists spend less time on routine verification and more time on complex analytical challenges.
DownloadAccelerating Structure Verification Across Novartis
Discover how Novartis applies automated structure verification to open-access NMR workflows used by hundreds of chemists. The case study describes automated analysis and reporting, approaches to assessing accuracy, and how successful automated confirmation can reduce analysis time by up to 90%.
DownloadMulti-Technique, Vendor Neutral Analytical Data Handling for Chemists
Explore how a single, vendor-neutral application can support the processing, interpretation, and reporting of data from multiple analytical techniques and instrument formats, including NMR, chromatography, mass spectrometry, FT/IR, and Raman. The application note highlights how easier access to analytical data can support faster decisions.
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