One-Day Agenda
Sessions
Partner Slots
Breaks & Admin
Opening Presentation
The 2030 Drug Discovery Laboratory: Where AI, Automation & Experimental Science Converge
- Examining how AI, laboratory automation and experimental science will reshape discovery workflows
- Integrating computational predictions with automated experimentation and real-world biological validation
- Exploring what the future drug discovery laboratory could look like and what capabilities will be needed by 2030
Keynote Presenation
Beyond Traditional Target Discovery: Unlocking Therapeutic Opportunities in Complex Biology
- Moving beyond conventional target identification to uncover opportunities in complex and poorly understood disease biology
- Integrating functional genomics, multi-omics and advanced biological models to strengthen target confidence
- Identifying new therapeutic opportunities where traditional approaches have struggle
Presentation 1
Designing Biology: Can Protein Engineering Create the Next Generation of Medicines?
- Using protein engineering to design molecules with improved specificity, stability and therapeutic properties
- Exploring engineered proteins, antibodies and other biologics for challenging disease targets
- Addressing the scientific and development challenges of translating engineered molecules into medicines
Deep Dive Session
The Biological Data Problem: Turning Massive Datasets into Actionable Drug Discovery Insights
- Integrating genomics, transcriptomics, proteomics and other biological datasets into meaningful discovery insights
- Overcoming challenges in data quality, interpretation, integration and reproducibility
- Translating complex biological data into actionable target and drug discovery decisions
Problem Solution Matrix
The Screening Challenge: Finding High-Quality Hits in an Era of High-Throughput Discovery
- Improving hit identification through high-throughput, high-content and phenotypic screening approaches
- Balancing screening scale with hit quality, biological relevance and reproducibility
- Accelerating the transition from initial hits to validated leads
Presentation 2
AI Beyond the Hype: What Can AI Actually Discover That Scientists Could Not?
- Exploring where AI and machine learning are delivering measurable value across drug discovery
- Moving from AI-generated predictions to experimentally validated biological and chemical insights
- Understanding the limitations of AI and where scientific expertise remains essential
Strategic Discussion
Expanding the Search Space: New Modalities for Previously Intractable Targets
- Exploring new therapeutic modalities for targets that have remained difficult or impossible to drug
- Matching modality, mechanism and delivery strategy to challenging target biology
- Evaluating the opportunities and limitations of emerging modalities in early discovery
Presentation 3
The Chemical Space Challenge: Discovering Novel Molecules Beyond Conventional Screening
- Exploring new approaches to access chemical space beyond traditional compound libraries
- Using computational design, fragment approaches and innovative chemistry to discover novel molecules
- Addressing challenges around novelty, potency, selectivity and developability
Panel Discussion
From Innovation to Impact: What Will It Take to Build the Drug Discovery Ecosystem of the Future?
- Breaking down the barriers between pharma, biotech, academia and technology companies to accelerate innovation
- Exploring how collaboration, partnerships and knowledge-sharing can turn promising scientific advances into real drug discovery outcomes
- Discussing what the next generation of drug discovery ecosystems needs to become faster, more connected and more productive