We solve data integration and applied analytics challenges across life sciences and engineering industries
With career backgrounds in data science, informatics, chemistry, pre-clinical research, and clinical development, the Elsevier Professional Services Group provides data integration and applied analytics as standalone services and via Elsevier’s Entellect platform. Our experts in scientific domains, industry-standard taxonomies, and custom content and data curation addresses complex data challenges in pharma biotech, life sciences, drug discovery, food and beverage, chemicals, energy, and other engineering and technology industries.
How we help our customers
Elsevier's Professional Services team integrates, harmonizes and analyzes data with predictive analytics and machine learning to accelerate discoveries, reduce risk, provide market intelligence, identify potential drug and patient safety signals, and much more. Check out these four key areas where our team can support your complex data challenges.
- Target-related custom reports
- Disease pathway analysis
- Scientific opportunity analysis
- Adverse event prediction
- Scientific risk management
- Integrated & harmonized source of chemistry data
- Drug repurposing custom reports
Capabilities & core services
The implementation of the Elsevier Text Mining solution to enable information discoverability across unstructured datasets through custom taxonomy mapping, natural language processing, and expertise in search construction.
Data integration & harmonization
The integration and harmonization of internal and external datasets, in both structured and unstructured formats, based on proprietary and industry-standard ontologies and taxonomies.
The extraction and querying of data to develop custom repositories or dashboards that serve existing workflows and/or make data available to researchers through a new, integrated point of access.
The development of custom reports and analytics based on large, integrated sets of Elsevier data solutions, customer data, and/or externally published information.
Predictive analytics & machine learning
The development of custom algorithms and/or the application of industry-leading algorithms and machine learning techniques to harmonized datasets to accelerate data-driven research.
Market insights & reports
Market insight: Melanoma report
In this report, we look at the current landscape of melanoma R&D, the biology and mechanisms of the disease, general knowledge gaps, therapeutics, and the new emerging topic of the microbiome melanoma association.
Case Study: Customized data sets for improved discovery
See how a pharmaceutical company was able to rely on a customized database created by the Professional Services team to help find reported mutations in cancer cells.
Elsevier Text Mining
Elsevier Text Mining enables the retrieval of highly specified information from unstructured content, providing more meaningful answers to complex research questions in less time.
The Hive: Real stories. Real science. Real time.
Biotech and pharma start-ups are using Elsevier's R&D solutions to solve for early-stage drug discovery and development. Check out real-world case studies and learn how early innovation starts with early access to research.
Pharma R&D Today blog:
Get a wide range of the latest insights and opinions on pharma-related topics with the Elsevier Pharma R&D blog.