Key Agenda Sessions Recommended For You
These featured sessions offer a snapshot preview of the insights you can expect at the 4th Donor Selection & Cell Source Summit. Download the Full Event Guide to unlock the complete agenda, view detailed session descriptions, and explore our speaker faculty.
Strengthening Donor Material Logistics
Panel Discussion: Strengthening Vendor Partnerships to Secure Reliable Material Supply & Quality Standards
Conference Day 1
- Building strategic relationships with blood banks, apheresis centers and cord blood banks to ensure consistent material availability and quality alignment
- Establishing clear communication of donor requirements, testing specifications and delivery expectations with external partners to prevent misalignment
- Auditing supplier capabilities, quality systems and regulatory compliance to qualify vendors that can support long-term commercial needs
Speakers:
Developing Fit-for-Purpose Donor Selection Strategies
Ensuring Consistent Donor Material Characterization to Strengthen Clinical-Stage Cell Therapy Development
Conference Day 2
- Standardizing donor screening criteria to reduce variability and improve starting material consistency across clinical manufacturing campaigns
- Implementing robust donor characterization assays to strengthen comparability between batches and support reliable clinical outcomes
- Establishing fit-for-purpose quality control frameworks to identify variability early and maintain product consistency throughout development
Speakers:
Advancing Predictive Donor Characterization & Scalable Screening Assays
Integrating Bioinformatics & Data-Driven Approaches to Accelerate Donor Stratification & Enhance Selection Accuracy
Conference Day 1
- Utilizing artificial intelligence and machine learning to analyze donor datasets and identify patterns that predict manufacturing success and therapy efficacy
- Building algorithms that force-rank donor variables and enable rapid decision-making when selecting between multiple candidate sources
- Establishing correlations between laboratory characterization results and clinical outcomes to validate predictive models and refine selection frameworks
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