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By reading this brochure, you will learn:
  • The limitations of relying just on PubMed for knowledge reviews and what insights will be missed
  • How advanced data curation connects together causal insights from multiple sources and uncovers cause-and-effect relationships not previously described in the literature
  • What return-on-investment can be delivered by leveraging advanced data curation technology
  • What others in the biopharma industry have to say about advanced data curation
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Please kindly fill out the form below and a member of our team will be touching base with you shortly.

By submitting this form, you submit your information to Biorelate, who may use it to communicate with you regarding your request via the form and their other services. You may unsubscribe from these communications at any time by clicking the Unsubscribe button at the bottom of our marketing emails or contacting us at info@biorelate.com.

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Daniel Jamieson awarded The Princess Royal Silver Medal

July 9, 2024
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5 min read
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Biorelate Downloads

Downloads

Discover new insights and updates for data science in biopharma.

Exploring Roflumilast's Potential in Non-Cystic Fibrosis Bronchiectasis

Mapping disease signaling: a case study of roflumilast's potential in non-cystic fibrosis bronchiectasis

Galactic API Datasheet

Discover Galactic API, a Galactic AI™ solution

Galactic Data Datasheet

Discover Galactic Data, direct access to the most comprehensive knowledge graph in biopharma

Galactic Web Datasheet

Discover Galactic Web, a Galactic AI™ solution featuring an advanced web interface

Introduction to Galactic AI™ for Target Selection

How Galactic AI™ enhances Target Selection

Galactic AI™ Introduction Brochure

An introduction to what, why and how of advanced data curation by Biorelate

Return-on-investment (ROI) using advanced cause-and-effect data curation

Going beyond standard search tools to tap into the power of advanced auto-curation of biomedical literature

Parkinson's Disease Case Study: Indication Expansion, Target Expansion, and Understanding Mechanism of Action

Galactic AI™ enables a deeper understanding of protein targets for Parkinson's Disease

Cause-and-Effect Data for Metformin and Kidney Cancer

An example of capturing richer data on the relationship between a drug (metformin) and disease (kidney cancer) to enhance knowledge reviews.

Using contextual cause-and-effect data and a disease knowledge graph to explore lung cancer

Explore how a novel lung cancer knowledge graph is created for better target identification

Drug Repurposing for chronic pain diseases

Identifying drug repurposing opportunities in chronic pain diseases

Safety & Toxicity Knowledge Review for Apconix

AI knowledge curation required to support safety and toxicity reporting for drug targets

Enhancing Drug Development Success Through Strategic Focus on Mechanism of Action and Explainability

Revealing novel insights in the case studies of roflumilast in non-cystic fibrosis bronchiectasis and the exploration of LCN2 in the context of obesity

Using Cause-and-Effect Knowledge Graphs to find Genetic Drivers for ALS

Case study example of using Cause-and-Effect Knowledge Graphs to find Genetic Drivers for ALS

Target selection for e-therapeutics: fibrotic diseases

Identifying potential fibrotic disease drug targets to support phenotypic screening

Indication Selection for Mid-sized pharma

Biorelate helped a mid-sized pharma who developed a combination product for two drug targets and wanted to identify the highest likely clinically relevant disease.

Galactic AI™ represents a quantum leap in the field of biomedical literature search and curation

By leveraging the power of Galactic AI™, researchers can accelerate the pace of discovery and innovation in the biomedical field, leading to breakthroughs in understanding, preventing, and treating diseases.

Request demoLearn more