Elsevier expands LeapSpace & sets up AI advisory board. Wed, 16th Sep 2026 (Today) Elsevier has expanded the content base of its AI research tool LeapSpace and set up an independent advisory board. The platform now draws on what Elsevier describes as the largest collection of peer-reviewed scientific material available to an AI research product. LeapSpace now uses more than 23 million full-text peer-reviewed articles and books, alongside 2.6 billion cited references from Scopus. Elsevier said that full-text corpus accounts for 56% of recent global research citations and 42% of research articles published since 2021. The update broadens the material available to researchers using the platform for tasks such as literature reviews, study design, manuscript drafting, and submission preparation. LeapSpace also includes Elsevier's own full-text journal articles and books, as well as more than 100 million scientific records from Scopus, covering content from more than 7,000 publishers. The latest expansion comes through licensing agreements with BMJ Group, JAMA Network, Rockefeller University Press, and the American Society of Civil Engineers. Elsevier has also added selected full-text material from existing partners including Emerald Publishing, IOP Publishing, and Sage Publishing, as well as content from more than 1,500 other scholarly publishers and societies. Elsevier is positioning the enlarged dataset as a way to distinguish LeapSpace from more general AI tools used in research. Its focus is on cross-publisher access and on using peer-reviewed source material rather than open-web content. Research trust The new advisory board is intended to address concerns about trust in AI tools within academia. Elsevier cited findings from its Researcher of the Future Report showing that 84% of researchers have used AI tools, while 22% said they trust them. According to Elsevier, the board will advise on the algorithms used to surface and assess content, oversee publisher-neutral discovery and ranking, and support transparency in AI-generated outputs. It will also provide guidance on the use of AI in academic and scientific research settings. The founding members are Chancellor's Professor Emeritus Jörg-Rüdiger Sack, who will chair the board; Professor Jodi Schneider; Professor Holger Hoos; Professor Fei Wu; and Dr. Mikiko Tanifuji. The group brings expertise from Carleton University, the University of Wisconsin-Madison, RWTH Aachen University, Leiden University, Zhejiang University, and the National Institute of Informatics. Elsevier has presented the board as an external layer of oversight at a time when academic publishers and technology companies face increasing scrutiny over how AI systems source, rank, and present research material. Questions around bias, transparency, and citation integrity have become more prominent as researchers experiment with generative AI for core parts of the research process. Elsevier also pointed to user feedback on the product, saying nine out of 10 LeapSpace users surveyed reported that the tool is either essential to completing literature reviews or makes a substantial contribution to them. Judy Verses, President, Academic and Government, Elsevier, outlined the company's view of the market. "Most AI tools give researchers answers. LeapSpace helps researchers achieve better outcomes across their whole workflow, while supporting their critical thinking, igniting their curiosity, and keeping them in control. LeapSpace is grounded in trusted science, transparent in how it works, and publisher-neutral by design. Breadth of content and rigor of governance, with independent assessment from leading experts at some of the world's top research institutions: that's what makes AI research-grade," she said. The expansion reflects a broader push by established academic information groups to embed AI tools into the daily work of universities, laboratories, and corporate research teams. That contest is increasingly centered on access to proprietary content and assurances that outputs can be traced back to credible source material. LeapSpace is sold to institutions and corporations. Elsevier said individual plans and free access are also available for academics and students. The tool is designed to help with complex tasks across the research workflow, from early literature review to preparing a paper or thesis. For publishers, the announcement also signals the growing importance of content licensing in the AI market. Rather than relying only on abstract-level databases, providers are seeking full-text agreements that give models and search tools access to the language, structure, and evidence contained in journal articles and books. Chancellor's Professor Emeritus Jörg-Rüdiger Sack described the board's purpose in those terms. "Trust in AI depends on more than how powerful the technology is. Researchers need confidence that the underlying content is selected fairly, that algorithms operate transparently, and that the same standards are applied consistently across publishers. The advisory board exists to provide independent oversight that helps ensure LeapSpace remains transparent, publisher-neutral, and grounded in trusted scientific evidence," he said.

Elsevier and LG AI Research unlock more chemistry hidden in scientific images. Sep 15, 2026, 03:00 ET New chemistry-specific AI vision technology turns chemistry trapped in images into searchable evidence at scale in Reaxys, helping researchers make confident decisions faster SEOUL, South Korea and LONDON, Sept. 15, 2026 /PRNewswire/ - Elsevier and LG AI Research today announced that researchers can now identify chemistry that has often sat beyond the reach of search: the substances that appear only as images, drawings and reaction schemes in patents and scientific literature. Visual chemistry of this kind has long been difficult for both humans and machines to index at scale. Now, chemistry-specific AI vision technology developed by LG AI Research is being used within Elsevier's content extraction and curation processes for Reaxys, Elsevier's discovery chemistry solution. Substance information from images in patent and journal content is captured far more quickly, accurately, and at far greater scale than was previously possible. This work enhances Elsevier's leading content extraction and scientific curation of substances, reactions, bioactivities, biological targets and substance properties for Reaxys. Why it matters Much of the substance and reaction information chemists rely on is communicated through figures, drawings and reaction schemes rather than searchable text. When that chemistry isn't searchable, researchers can be left checking documents by hand to confirm whether a compound or reaction has already been described. Making that chemistry discoverable at scale is a specialist AI challenge. Chemical drawings encode meaning through bonds, atoms, stereochemistry and spatial relationships. A model that misreads a bond may identify the wrong compound; one that misses a structure gives chemists an incomplete picture. This matters most in areas such as novelty searching, competitive intelligence and synthesis planning, and in inorganic and organometallic chemistry, where complex structures are harder to extract and index. Built for chemical drawings The novel chemistry-specific AI vision technology from LG AI Research combines molecule detection, reaction-diagram parsing and optical chemical structure recognition (OCSR) in a single model. In the company's published benchmarking, it outperforms alternatives at extracting chemistry from a full document page, placing the technology at the forefront of innovation for reading chemistry across formats. Each extraction pipeline is validated against existing Reaxys benchmarks before it goes live, so accuracy is not traded for scale. The full pipeline has undergone a rigorous period of testing across Elsevier's data and workflow tools to ensure accuracy and quality before wider use. Mirit Eldor, Managing Director, Life Sciences, Elsevier, said: "Every hour a chemist spends deciphering figures or images to see what has already been made is an hour that could instead be spent on chemistry discovery. Our partnership with LG AI Research gives that time back, lifting more chemistry out of the image and into Reaxys - curated, searchable and ready to act on. A structure buried in a figure should be evidence rather than a dead end." Hwayoung Edward Lee, lead of the AI Biz Transformation Unit at LG AI Research, said: "Understanding scientific images requires AI engineered specifically for chemistry - where every bond and spatial layout holds critical meaning. We designed our AI vision model to decode these complex visual representations with human-expert precision. Through our integration with Elsevier, we are proving that advanced chemistry-specific AI can seamlessly convert raw visual data into structured knowledge for global researchers." Extending the partnership Reaction extraction is the next stage of the collaboration, extending image-based extraction beyond individual substances to broaden the reaction evidence available through Reaxys. Elsevier and LG AI Research are also exploring further customer challenges to tackle together, bringing together LG AI Research's specialist AI capabilities with Elsevier's chemistry content, scientific expertise and curation. About LG AI Research Established in December 2020, LG AI Research serves as the AI think tank for the LG Group. Its mission is to enhance AI capabilities by addressing business challenges, conducting cutting-edge AI research, and establishing and implementing ethical principles for AI technology. Leveraging EXAONE (Expert AI for Everyone), a proprietary large-scale AI model developed since 2021, the center has been driving innovation across various industries. Furthermore, by successfully passing the technological evaluation in the 'National AI Foundation Model Project' - an initiative launched to resolve dependency on global models - LG AI Research has firmly solidified its position as Korea's flagship AI company. About Elsevier Elsevier is a global leader in advanced information and decision support. For over a century, we have been helping advance science and healthcare to advance human progress. We support academic and corporate research communities, doctors, nurses, future healthcare professionals, and educators across 170 countries in their vital work. We help impact makers achieve better outcomes with research and clinical-grade solutions built on the world's leading evidence-based scientific and medical content, precision AI, and expert human assessment. We champion inclusion and sustainability, working with the communities that we serve. The Elsevier Foundation supports research and health partnerships around the world. Elsevier is part of RELX, a global provider of information-based analytics and decision tools for professional and business customers. For more information, visit www.elsevier.com and follow us on social media @elsevierconnect. SOURCE Elsevier Limited

Elsevier and LG AI Research have developed chemistry-specific AI vision technology that extracts chemical information from images in scientific literature and patents. The technology is now integrated into Elsevier's Reaxys chemistry discovery platform. Chemical substances and reactions are often depicted as drawings, figures, and reaction schemes rather than searchable text, making them difficult to index at scale. The new AI model combines molecule detection, reaction-diagram parsing, and optical chemical structure recognition to extract this visual chemistry more quickly and accurately than previous methods. LG AI Research's technology can interpret bonds, atoms, stereochemistry, and spatial relationships in chemical drawings. According to the company's published benchmarking, it outperforms alternatives at extracting chemistry from full document pages. The extraction pipeline has been validated against existing Reaxys benchmarks to maintain accuracy whilst increasing scale.