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Galactic AI™ use cases

MoA &

Galactic AI™ meticulously identifies and organises critical cause-and-effect relationships within the data, uncovering previously unrecognised connections among drugs, targets, and diseases.


Galactic AI™ delivers profound insights into diseases’ biological mechanisms, increasing confidence in scientific rationale.

Researchers frequently struggle to grasp the intricate mechanisms linking drugs, targets, and diseases. Galactic AI™ leverages sophisticated analytics to seamlessly integrate information from scientific literature, empowering you to formulate the most well-supported hypotheses regarding mechanisms of action.

An extensive knowledge graph, tracing pathways from targets to diseases, all supported by evidence from scientific literature.

Galactic AI™'s directional cause-and-effect relationships enhance your understanding of how targets can be strategically utilised to combat diseases.

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Cause-and-effect paths example
Are you tapping into the most comprehensive data that reveals the intricate connections among drugs, targets, and diseases?

Galactic AI™ offers you a revolutionary perspective on target mechanisms, boosting your confidence throughout your drug discovery programme.

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Galactic AI Scheme
Data Quality
Access the most comprehensive, high-quality evidence on targets in your research field, curated automatically.

Galactic AI™ employs cutting-edge analytics to seamlessly integrate findings from scientific literature, empowering you to formulate the most well-substantiated hypotheses for drug mechanisms.

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Uncover the pharmacological effects of a drug through the lens of Galactic AI™

Navigate the most detailed knowledge graph with Galactic AI™ to trace evidence-based pathways from targets to diseases.

Galactic AI™ revolutionises your grasp of target mechanisms, enhancing confidence in your drug discovery endeavours.

40 Million +

Documents Processed

Galactic AI™ processes journals, patents, clinical trials and many more sources (and can process in-house text).

60 Million +

Cause-and-Effect Relationships

Relationships between concepts, such as cause-and-effect, are classified with directionality. All in context.

2.7 Billion +

Cause-and-Effect Interaction Mentions in Context

Explainability and greater flexibility to refine your data with more contextual data points.

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Customer testimonials

Our customers span globally recognised companies like Pfizer and AstraZeneca as well as innovative drug discovery biotechs.

“The contextual data from Biorelate is critical to our efforts to embed knowledge graphs into the drug discovery pipeline.”

Dr. Ben Sidders

Director, Oncology Informatics - AstraZeneca

“Biorelate has been a game changer. The cutting-edge platform can make novel connections between bioactive molecules and disease to help biologists find hidden insights.”

Christopher J Nicholson

Head of Biology - Pepper Bio

“Biorelate has managed to provide a user-friendly tool to Idorsia scientists to cope with the massive amount of biomedical literature and more efficiently discover relevant aspects for our projects to speed up processes.”

Peter Groenen

Head of Translational Biomarkers - Idorsia Pharmaceuticals

“Biorelate’s NLP-derived contextual interaction data, combined with ETX’s proprietary databases, enables e-therapeutics’ approach to the modelling of complex biology and the use of those models for target identification and deconvolution."

Dr. Jonny Wray

Chief Technology Officer - e-Therapeutics

"The collaboration between Biorelate has been extremely productive and we look forward to working together on future developments."

Professor Ruth Roberts

‍Co-Founder and Director- Apconix

Cause-and-effect paths example
Hidden links

New data insights
for mechanism hypotheses

Reveal undiscovered links between drugs, targets and diseases.


Discover and map pathways linking targets to specific diseases.

Indication and biomarker selection

Uncover and prioritise diseases mechanistically associated with your target, along with relevant pharmacodynamic biomarkers.

Better research decisions

Elucidate unexpected off-target effects to refine your drug discovery strategy.

Deeper understanding

Reveal new insights

Galactic AI™ is the most advanced data curation in biopharma, revealing new data insights for mechanism hypotheses

Galactic AI™ reveals new insights for understanding mechanism of action while also uncovering novel targets and biomarkers, and indication expansion opportunities

Galactic AI scheme

How Galactic AI™ works

Galactic AI™ is engineered to meticulously parse and process vast quantities of biomedical literature, extracting and curating valuable data from a multitude of textual sources.

Cause-and-effect paths example

The most advanced data curation in biopharma

Galactic Al™ gives you a new understanding of how targets work for greater confidence in your drug discovery programme.