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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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GenAI’s Real Potential in Biopharma: As a Cross-Function R&D Assistant

Daniel Jamieson
May 16, 2024
•
5 min read
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Biorelate Downloads

Downloads

Discover new insights and updates for data science in biopharma.

Target selection for e-therapeutics: fibrotic diseases

Identifying potential fibrotic disease drug targets to support phenotypic screening

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.

Drug Repurposing for chronic pain diseases

Identifying drug repurposing opportunities in chronic pain diseases

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

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

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

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

Safety & Toxicity Knowledge Review for Apconix

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

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

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.

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