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Elsevier
論文を投稿する
Press release

Elsevier introduces authoritative scientific Datasets to fuel innovation and business-critical decisions in life sciences, chemicals and other research-intensive industries

New York | 2023年11月8日

Elsevier’s Datasets help accelerate digital transformation at scale in a variety of applications, including generative AI and predictive modeling

Elsevier, a global leader in scientific information and data analytics, has announced a new offering of enriched and authoritative scientific Datasets to power data applications that solve R&D challenges. Elsevier’s Datasets enable researchers, data scientists and practice leaders to answer R&D questions with greater speed and precision across many industries, including life sciences, energy, chemicals and materials, and technology. Use cases span a variety of data science and analytical projects including identifying disease targets using natural language processing, predicting molecule efficacy and toxicity using neural networks, predictive modeling, Key Opinion Leader (KOL) analysis and more.

“R&D-intensive businesses are excited by the possibilities of generative AI, predictive modeling and other areas at the vanguard of data science,” commented Gino Ussi, President of Corporate Markets, Elsevier. “However, to deliver high-quality analytics and well-trained AI models, data scientists must still devote much of their time to sourcing quality data. This is laborious due to the volume and range of research literature and comes with risk if the data is not from a trusted, validated source. Elsevier’s Datasets address this challenge, drawing on our expertise in curating peer-reviewed science for more than 140 years and partnering with the research community.”

Pharma, chemicals, energy, applied materials and technology companies can extract scientific insights by integrating data from Elsevier into private, secure computational ecosystems, including custom applications and third-party tools. Application-ready Datasets for chemistry, biology and 22 other disciplines come from a variety of sources, including:

  • 19 million full-text articles from peer-reviewed journals

  • 17 million author profiles

  • 1.8 billion cited references

  • 333 million chemical substances and reactions

  • 86 million bioactivities and biomedical records

  • 35 million chemical patents

Elsevier’s Datasets accelerate discovery and innovation in multiple domains. Leaders in pharmaceuticals, chemicals, technology and other industries are licensing Elsevier data for a variety of use cases. For example, in drug discovery, Datasets are used for target selection and discovery, confirming or identifying lead candidates, and in performing protein-ligand binding QSAR modeling. Pharmaceutical companies can also benefit from applying Datasets to pharmacovigilance, clinical trial design and to inform market access strategy. In materials science and materials informatics, Datasets support selecting the right material for a given application or product design based on property prediction and analysis of relevant datasets. Spanning all disciplines, Datasets enable KOL identification and rising star selection; predictive modeling (e.g., material property predictions or drug-drug interactions); training sets; knowledge graph creation; enterprise, federated and/or semantic search; business intelligence dashboards; and algorithm and neural network training.

Datasets are delivered flexibly via APIs or flat files. Elsevier has a team of domain and data science experts who can support customers’ data projects, and ontology management, text analytics and semantic search tools to help find, manage and share data.

“Elsevier’s Datasets provide data from the world’s largest source of scientific information to embed within R&D and business workflows. Research teams can also benefit from the expert support of the Professional Services team of data scientists, bioinformaticists, ontologists and domain specialists to help them scale and accelerate their data-led projects,” commented Mark Sheehan, Vice President of Data Science, Life Sciences. “This translates into faster, safer innovation for business from data insights and predictions based on the most authoritative Datasets and underlying expertise.”

Learn more about Elsevier’s Datasets.

エルゼビアについて

エルゼビアは情報分析を専門としたグローバル企業として、研究者や医療専門家の方々を支援し、社会にとっての利益最大化に向けて、科学や医療の進展を支えています。これは、信頼できるエビデンスによるコンテンツと高度なAI対応によるデジタル技術に基づく革新的なソリューションにより、知見の集積や重要な意思決定を支援することで実現されています。

エルゼビアは、全世界で9,700人の従業員(うち技術者2,300人以上)を抱え、140年以上にわたって、研究者、図書館員、アカデミックリーダー、資金提供者、政府、研究開発集約型企業、医師、看護師、将来の医療専門家、教育者など研究・医療分野におけるパートナーの重要な活動を支援してきました。エルゼビアが刊行する3,000誌以上の科学ジャーナルと代表的な参考書には、The Lancet 新しいタブ/ウィンドウで開くCell Press 新しいタブ/ウィンドウで開くおよびGray’s Anatomyなどをはじめとする、各分野を代表する主要なタイトルが含まれています。 エルゼビア・ファンデーション 新しいタブ/ウィンドウで開くとの活動を通し、私たちがサービスを提供する地域社会と連携して、開発途上国を含む世界中の医学、研究、医療分野における、インクルージョン&ダイバーシティ(I&D)の改善に努めています。

エルゼビアは、専門家および企業向けの情報分析および意思決定ツールのグローバルプロバイダーであるRELX Group 新しいタブ/ウィンドウで開くの一事業を担っています。エルゼビアの事業内容、デジタルソリューション、コンテンツなどの詳細については、www.elsevier.comをご覧ください。

連絡先

Headshot of Terri Mueller

TM

Terri Mueller

VP, Global Communications

Elsevier

+1 908 323-9180

E-mail Terri Mueller