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AI in biotech evolving from experimental models to regulated, production-ready drug discovery systems
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AI in Biotech: Lessons from 2025 and the Trends Shaping Drug Discovery in 2026

Fluorescent Cell Painting image showing multiple cellular components used for morphological profiling in drug discovery.
The Applications of Morphological Profiling for Drug Discovery: The success stories
Leading with purpose: Łukasz Nowak on building strong teams and scalable operations
Leading with purpose: Łukasz Nowak on building strong teams and scalable operations
Data visualization representing AI-driven drug discovery using UK Biobank data
Lessons from the UK Biobank: Scaling AI Insights with Deep, Structured Data
AI with impact: CTO Michał Warchoł on building tech that matters
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
Adding Space to the Equation: How Spatial Context Enhances Drug Discovery
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Where Biology Meets Data: Key Takeaways from Festival of Biologics & BioTechX 2025
Abstract visualization of AI-driven analysis of patient data, representing precision medicine and responder identification.
Blog

Precision Trials: Using AI to Identify Responders

Portrait of Livia Legg, Chief Commercial Officer at Ardigen, featured in the 10 Years of Ardigen: Voices of Leadership interview series.
Built on Trust, Driven by Impact: How Ardigen’s CCO – Livia Legg Sees the Future of Partnerships in AI & Biotech
Microscopy image on computer screen with data charts – visualization of AI-ready phenotypic screening in drug discovery
From Phenotypic Screening to AI-Powered Insight: How to Generate Data to Get the Most from Ardigen phenAID
Illustration of Explainable AI in drug discovery, showing model interpretability and data transparency
Can You Trust Your Model? Why Explainability Matters in AI-Driven Drug Discovery
Learn how biotech can innovate faster and smarter. Discover how AI can benefit biologics’ discovery from protein design to in silico testing.
The AI-Biology Convergence: Designing the Next Generation of Biologics
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
banner that introduces blog post a key take aways from the Drug Discovery Conference
Data dreams and drug design: What we learned at Discovery and Development Europe 2025
Biologics 2.0 – From monoclonal antibodies to multispecific therapeutics