R&D informatics
Develop custom algorithms and apply machine learning to create an integrated and harmonized source of data. Elsevier can help with:
Data integration and harmonization
Workflow solutions
Text-mining applications
Cheminformatics
Professional Services
Professional Services: Domain and data science expertise to tackle complex challenges
You need trusted partners to tackle complex data challenges and improve innovation outcomes. Elsevier Professional Services is an agile team of consultants that supports bespoke data integration and applied analytics. Go further, faster with Elsevier.
Risk analysis
Develop custom reports to answer key R&D and safety questions. Elsevier can help answer questions such as:
Which studies have been conducted for similar compounds and what were the findings?
What adverse events might occur based on molecular structure and class?
What are the most predictive preclinical species for understanding human toxicity?
What is the potential risk of litigation based on drug failure?
Target analysis
Accelerate early discovery activities through access to critical disease or target overview information to prioritize research focus areas. Elsevier can help you answer key research questions, such as:
Which diseases might this target treat?
What are the potential adverse events and drug interactions?
Are there known molecules likely to be test molecules?
What new target may exist to treat a specific disease with less side effects?
How does each target score based on pathway activation, gene expression, and an overall literature analysis?
Pathway analysis
Develop a more thorough understanding of the chemical risk of a compound based on the analysis of biological pathways in the human body and underlying molecular mechanisms that can cause diseases. Our team can help answer questions such as:
What are the key cells to target for a particular disease?
Which proteins are relevant in my disease of interest?
What are the biomarkers on the path to toxicity?
Which molecular mechanisms are linked to disease outcomes?
Drug repurposing decisions
Access detailed custom reports and predictive analytics to support critical drug repurposing decisions. These solutions include:
Text mining for possible drug indications in the scientific literature
Prediction of new drug indications based on drug target biology and efficacy of other drugs in the same class
Scoring mechanism to identify most promising repurposing candidates
Disease-centric repurposing includes pathway analysis to identify:
Signaling affected in a disease
Compounds targeting proteins in the disease pathway
Known drugs to inhibit proteins
Connected, configurable solutions to innovate in R&D
Advance your R&D with Elsevier's Professional Services and a portfolio of solutions to support and optimize innovation outcomes. Navigate your R&D journey with confidence, supported by:
Trusted content from peer-reviewed scientific literature to regulatory data
Innovative technology that prepares data for machine consumption
Expertise to capture scientific knowledge in computational formats
Information integrity is essential to your progress. Discover trusted data and tools that transform complexity into scientific insight. Let's shape progress together.
Core capabilities we apply to drive customer success
Semantic technologies
Semantic technologies
Model, annotate and enrich data into rich, machine-readable and contextualized data using semantic analytics software.
Data integration and harmonization
Data integration and harmonization
Integrate and harmonize data in multiple formats with proprietary and industry-standard ontologies and taxonomies.
Workflow solutions
Workflow solutions
Extract and query data to develop custom repositories or dashboards and new, integrated points of access.
Custom reporting
Custom reporting
Create custom reports and analytics based on Elsevier data, customer data and externally published information.
Predictive analytics and machine learning
Predictive analytics and machine learning
Develop custom algorithms and apply industry-leading algorithms and machine learning techniques.