AI-powered Target Discovery
Identify New Drug Targets And Promising Drug Repurposing Candidates Quickly, Easily and with high Confidence:
- Accelerate your AI in clinical research at least 10x. Easily and quickly mine relevant scientific information and explore new relationships across vast connected data sources;
- Enrich your knowledge with an AI-powered therapeutic target database, automatically extracted from scientific publications, patents and study materials;
- Utilize your scientific research advanced algorithms to analyze large and complex network relationships between biomedical entities effectively;
- Embrace data-driven decision-making in target assessment and prioritization;
- Promote innovation by using a digital discovery platform that adapts to your research and business needs in both new drug target discovery and repurposing of existing drugs;
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Industry leaders trust us
Accelerate AI in clinical research 10 times
Discover previously unknown connections between targets and diseases, quickly generate and assess new ideas to guide drug research and development.
Leverage highly interlinked information across various data sources to boost drug development and drug repurposing
Identify biomedical concepts and relationships in both unstructured and structured data to speed up novel therapies
About Ontotext’s Target Discovery
The challenge of drug discovery
Discovering the next breakthrough drug candidate is a daunting task, involving sifting through vast amounts of biomedical information scattered across different databases and research publications. This process can be time-consuming and difficult to mine, gather and analyze.
Centralizing biomedical knowledge
Ontotext’s Target Discovery solves this by combining all the knowledge about biomedical entities, such as genes, proteins and compounds, into a centralized Knowledge Graph. The system democratizes data access to AI in biomedical engineering through powerful search tools, presents it in a user-friendly manner, and provides transparent analytics to aid data-driven decision-making.
AI-powered preclinical insights
Using AI for preclinical research provides fast and easy access to facts generally hidden in millions of scientific publications and patents and predictions about novel relations between genes and diseases. The process of selecting the right candidate is further enhanced by comprehensive data provenance and confidence metrics for AI-driven drug discovery.
How it works
The building blocks of Ontotext’s AI-powered target discovery solution include:
LinkedLifeData Inventory
Leverage pre-configured data sources from Ontotext LinkedLifeData inventory that covers concepts such as genes, proteins, drugs, pathways, clinical trials, scientific literature, patents, etc.
Knowledge graph enrichment via NLP
Automatic extraction of relationships from leading scientific databases, such as Pubmed and Google Patents, to provide a comprehensive understanding of the concepts that are crucial for your research and decision making. Our AI tools provide accurate, reliable, and up-to-date information about millions of biomedical facts.
Data exploration that is easy to use and does not require technical expertise
- Design and customization that prioritizes the needs and preferences of the user;
- Providing transparent results to a wide range of access points;
- Includes metadata with detailed information about the origin and credibility of each result, and allows for customizable ranking options.
Powerful and configurable analytics
- Unlock the potential of AI to predict new targets for your research. Utilize our advanced tools that use knowledge of genes, proteins, and diseases to identify new therapeutic targets with precision and efficiency;
- Maximize the potential of your data with our ranking and clustering algorithms;
- Unlock the full potential of your custom machine learning algorithms by integrating them seamlessly into our platform. Our flexible architecture allows you to plug in your own algorithms to extract even deeper insights from your data;
Who is Ontotext’s Target Discovery for?
Scientists and Researchers
Typically, it’s challenging to find relevant information in the vast amount of scientific publications and make sense of both public and internally produced data. Target Discovery helps minimize difficulty in deciding what assays to prioritize based on all available information.
Pharma companies
Organize and semantically connect your disparate data to reveal hidden relationships and unlock deeper insights.
Research
Organize and semantically connect your disparate data to reveal hidden relationships and unlock deeper insights.
Related posts
Accelerating End-to-end Knowledge Graph Solutions with Ontotext’s LinkedLifeData Inventory: The Case of Target Discovery
LLD Inventory forms the semantic foundation for Ontotext’s Target Discovery solution.
Oxford Drug Discovery Institute Accelerated Alzheimer’s Breakthroughs by Harnessing Ontotext’s Target Discovery
Ontotext’s Target Discovery solution helped Oxford Drug Discovery Institute accelerate target analysis and decision-making
Breaking Barriers: Streamlining Target Prioritization for Swift Scientific Insights
Join this webinar to hear from a satisfied partner who achieved a remarkable 500% increase in insight discovery speed, streamlined research timelines from months to days, and enhanced innovation potential.