Galactic AI™ use cases

Indication
Expansion

Galactic AI™'s knowledge graph reveals novel indications for your drug discovery programme.

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By reading this case study, you will discover:

Why leveraging cause-and-effect analysis is imperative for advancing drug target selection
How a robust proof of mechanism enhances the likelihood of drug discovery projects advancing from clinical development to market launch
Two detailed examples of applying groundbreaking Natural Language Processing-fueled technology to understanding complex biological mechanisms:

a. Investigating the application of roflumilast, a drug approved for treating chronic obstructive pulmonary disease (COPD), in treating Non-Cystic Fibrosis Bronchiectasis.

b. Examining the observed correlation between obesity and increased expression of the protein LCN2, a relationship currently lacking a direct cause-and-effect rationale.

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Galactic AI™ deepens your understanding of biology and establishes the causal connections between drugs and various disorders.

When researchers identify a therapeutic drug target for a condition, they often explore additional indications that could also benefit. This exploration is crucial for attracting further investment in their drug discovery efforts, demonstrating the wider market potential of their proprietary treatment. Galactic AI™ is an essential indication expansion resource; researchers uncover new indications by leveraging its unparalleled database of cause-and-effect relationships.

New opportunities

How much is restricted access to premier drug-disease data impacting your development pipeline?

Galactic AI™ offers groundbreaking insights, providing you with the most effective pathway to uncovering opportunities for indication expansion.

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Hypotheses

Gain access to invaluable new evidence for hypothesising novel indications for your drug.

Indication expansion can help broaden the impact of a new drug that has already been through the arduous R&D process for a disease. Richer data insights support new indication expansion opportunities.

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Evidence

Access the most comprehensive evidence for indication expansion, curated automatically.

Galactic AI™ harnesses cutting-edge technology to curate extensive cause-and-effect relationships derived from the biomedical literature. Request a demo to explore the transformative potential of this novel data for your research endeavours.

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Uncover new, directional relationships to support indication selection with Galactic AI™

Indication expansion can help broaden the impact of a new drug that has already been through the arduous R&D process.

Galactic AI™'s novel evidence gives you the best and most efficient understanding of indication expansion opportunities.

42 Million +

Documents Processed

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

65 Million +

Cause-and-Effect Relationships

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

3 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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Testimonials

Customer testimonials

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

“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

"Galactic Web can make compiling the right papers a lot quicker. And with Galactic Web, you can really tailor the search terms far beyond what you can do in PubMed."

María Victoria Ruiz Pérez

Senior Translational Cancer Scientist and Translational Guild Lead - Turbine

"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

Novel relationships

Novel cause-and-effect relationships

Galactic AI™ enables you to:

Identify

Identify diseases indirectly connected to a target from evidence in the literature.

Explore

Use the Galactic AI ™ knowledge graph for graph traversals to explore the disease landscape around a target.

Go further

Richer data insights support new indication expansion opportunities.

New insights

Deeper understanding

A deeper understanding of the landscape around targets fuels better hypotheses for indication expansion

Comprehensive cause-and-effect relationships reveal novel insights to point you in new directions for indication expansion

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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.