Digitalization & AI-Enablement in R&D
Hear how R&D organizations are digitalizing workflows and preparing for AI. Industry experts share practical strategies for prioritizing data and workflows, and overcoming implementation challenges to improve efficiency and accelerate innovation.
June 3rd, 9:30 EST, Register Now5 Ways to Digitalize Your Research Lab and Accelerate Scientific Discovery
Discover how digitalizing your laboratory can make science simpler and more efficient. Learn how ELNs, LIMS, property prediction tools, and integrated analytical platforms can help you save time, reduce errors, and let chemists focus on meaningful experiments.
The future of chemical data analysis and management: Toward unified, standardised, and web-based analytical workflows
Explore how unified, standardized, and web-based workflows can help chemical R&D organizations unlock deeper insights from their analytical data by improving data access and collaboration, supporting scalable automation, and enabling AI-readiness.
ISO10993:18-2020—Simplifying the Chemical Characterization of Medical Device Materials
Chemical characterization of E&Ls in medical devices is integral to safeguarding the safety of medical products. The ISO10993-18:2020 guidelines provide comprehensive guidance to help address the fundamental questions “What substance(s) may be released from drug packaging or medical devices?” and “Will it cause harm to patients?”
Automated Structure Verification for High-Throughput Quality Control in R&D
Scientists at Syngenta and Amgen rely on Automated Structure Verification (ASV) to enable high-throughput NMR quality control workflows. Explore their process from optimizing dataset selection to reducing analysis time, improving data confidence, and accelerating decision-making with ASV.