+tellic graph

+tellic graph is a patented biomedical knowledge graph platform developed by tellic, designed specifically for pharmaceutical and life sciences organisations. It leverages large language models (LLMs), natural language processing (NLP), and machine learning to create a single source of truth for biomedical concepts, enabling researchers and analysts to explore, validate, and generate drug discovery hypotheses faster and with greater confidence.

tellic addresses a core challenge facing biomedical professionals: legacy systems that produce incomplete taxonomies, fragmented document stores, and unclear mappings between biomedical concepts and relationships. Where conventional NLP solutions fail to keep pace with the rapid expansion of scientific literature, +tellic graph extracts cause-effect features from a broad range of text-format data sources — including research publications, grants, preprints, clinical trials, patents, and proprietary internal research — to deliver a comprehensive and continuously updated landscape of biomedical knowledge.

Core Capabilities

• Biomedical NLP: Machine learning pipelines purpose-built for biomedical text process unstructured data at Big Data scale, detecting scientific entities and relationships with PhD-level accuracy.
• Concept Search: Increases the number of relevant search results by up to 4X, dramatically reducing the time scientists spend searching across multiple data sources.
• Knowledge Graph: Constructs a data-driven knowledge graph from your organisation's data, enabling informed drug discovery decisions quickly and accurately.
• Ontology Linking: Links biomedical concepts into preferred ontologies using machine learning, with support for ever-evolving vernacular, ontologies, and identifiers.
• Relationship Surfacing: Surfaces relationships between biomedical entities to inform hypothesis generation and validation, including drug re-purposing and target prioritisation.

Platform Features

• Detects biomedical concepts in text data at Big Data scale, trained on thousands of PhD annotations that map all known synonyms to a single ontological concept.
• Provides a unified view of all relevant data that updates automatically as new research is published.
• Delivers a clear path for exploring concept relationships and pinpointing opportunities in drug discovery.
• Supports genomically-informed subgraphs, as demonstrated in a published customer case study leveraging a billion-edge knowledge graph for drug re-purposing and target prioritisation.
• Customised to organisational language, ensuring relevance to each pharma company's internal terminology and research focus.

Who It Is For

• Pharmaceutical and biotech companies seeking to accelerate drug R&D decision-making.
• Biomedical researchers and analysts overloaded by fragmented data sources and legacy search tools.
• Organisations looking to compress time-to-search and accelerate time-to-insight across internal and external biomedical data.

+tellic graph is an enterprise-scale solution covered by US Patent 12061870, developed by a multidisciplinary team with expertise spanning molecular biology, functional genomics, drug discovery, AI and machine learning, linguistics, and big data engineering. Founded in 2015, tellic pioneers a new category of biomedical language processing and knowledge discovery to help bring life-enhancing drugs to patients faster.