Knowledge hub

Knowledge hub

AI in Biotech

Webinar: Lab-in-the-Loop: reclaiming the 50% of scientific time lost to data
Webinars

Lab-in-the-Loop: reclaiming the 50% of scientific time lost to data

,
Blog cover for Ardigen publication on ARDisplay-I and MHC ligand identification in Molecular & Cellular Proteomics
New publication in MCP: Improving MHC ligand identification with machine learning and optimized isolation
Abstract network visualization representing AI-driven integration of biological data and knowledge graphs for target identification in drug discovery.
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?
Biotech AI data privacy in AI-driven biological and pharmaceutical research
Data Privacy Day 2026: Why Data Privacy Is Becoming a Technical Constraint in Biotech AI
News

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
From patient data to novel targets and biomarkers: UK Biobank use
Data visualization representing AI-driven drug discovery using UK Biobank data
Lessons from the UK Biobank: Scaling AI Insights with Deep, Structured Data
From research to impact: Ardigen’s technology behind the Polish Microbiome Map
Laboratory glassware with digital data visualization overlay, representing the use of public biological datasets for AI-driven drug discovery.
Leveraging Public Datasets for AI-Driven Discovery
AI transformation in clinical trials faces hurdles like data quality, bias, and scalability. Know the challenges and their corresponding sol
Challenges of AI in clinical trials and how to overcome them
,
New joint study: Computational identification of cross-reactive TCR epitopes with ARDitox
Adding Space to the Equation: How Spatial Context Enhances Drug Discovery