Knowledge hub

AI in drug discovery

Abstract network visualization representing AI-driven integration of biological data and knowledge graphs for target identification in drug discovery.
Blog

Target Identification: From Poor Data to Quality Predictions

Abstract data streams representing data sourcing in pharmaceutical research and AI drug discovery
What Are Common Data Sourcing Patterns in Pharmaceutical Research (part 3)
Abstract visualization of binary data representing AI model training in drug discovery
What Type Of Data Do You Need For AI Drug Discovery (part 2)
Data quality management in AI-powered drug discovery and pharmaceutical research
Why Data Quality Matters in AI-powered Drug Discovery (part 1)
Scientist working with AI-driven drug discovery data in a biopharma laboratory
A practical 2026 roadmap for adopting AI in biopharma R&D
AI-powered bioinformatics platform visualizing biological data and model insights in a laboratory setting
The invisible bridge: How UX design can support AI success in bioinformatics?
Good AI practice is no longer optional in Drug Discovery – EMA and FDA set the direction
AI in biotech evolving from experimental models to regulated, production-ready drug discovery systems
AI in Biotech: Lessons from 2025 and the Trends Shaping Drug Discovery in 2026
Stage view from the SBI² 2025 conference in Boston, showing the event banner and audience.
News

SBI² 2025 Recap: From Cells to Systems – Imaging, AI, and the Future of Phenotypic Discovery

Scientist working in a laboratory environment, symbolizing biotech innovation and AI-driven drug discovery.
New publication: Biologically relevant models and AI increase scalability in CRC drug screening
Scientist analyzing high-content cell images on a computer screen – visualizing AI-driven phenotypic profiling in drug discovery.
The Future of Drug Discovery: Integrating Phenotypic Data with Omics and AI
a biopharma lab
What’s trending in European Biopharma? A look ahead