8:00 am Check-In & Coffee
Early-Stage Development
Workshop A: Solving Out of Specification (OOS) Issues in Early- Stage Cell Therapy Manufacturing
Synopsis
Out of Specification (OOS) results are a common and challenging issue in early-stage cell therapy manufacturing, where process variability can lead to delays and increased costs. This workshop will focus on identifying and addressing the root causes of OOS issues, as well as implementing proactive risk management strategies to ensure product consistency in the early phases of development.
- Root Cause Analysis of Early-Stage Process Failures: Methods for identifying key process variables that lead to OOS results, including cell viability and expansion issues
- Proactive Risk Management Strategies: Techniques for detecting and mitigating potential failure points early in process development to reduce the likelihood of OOS events
- Implementing Corrective Actions for OOS Consistency: Best practices for defining and executing corrective actions that ensure long-term process stability and consistency in early-phase manufacturing
Late-Stage Development
9:00 am Workshop B: Implementing Cutting-Edge Technology in Cell Therapy: Balancing Early Adoption & Phase-Appropriate Strategies
Synopsis
In the fast-evolving world of cell therapy, companies must decide when to implement cutting-edge technologies like AI, automation, and advanced analytics, all while maintaining speed and regulatory compliance. This workshop will explore how to strategically adopt new technologies, from early-phase development to clinical trials, and navigate the challenges of balancing innovation with the need for process standardization and GMP compliance.
- Deciding When to Implement New Technologies: Early vs. Later-Stage Adoption: Evaluating the risks and benefits of adopting cutting-edge technologies at different stages of development and scaling and balancing early-phase process flexibility with requirements for later-stage scalability
- Balancing Process Agility and Technology Integration: How to maintain operational flexibility and scale-up while integrating technologies like AI, automation, and advanced analytics without compromising on quality or compliance
- Successful Case Studies of Technology Implementation: Examining case studies where cutting-edge technologies were successfully implemented, and the lessons learned from overcoming regulatory and technical challenges
12:00 pm Lunch Break
1:00 pm Workshop C: Building a Robust Control Strategy in Early-Phase Development of Cell Therapies
Synopsis
In early-phase development, managing variability in starting materials, such as donor cells and raw materials, is crucial for ensuring consistent and reproducible cell therapy products. This session will explore strategies for establishing control measures that address these challenges and ensure clinical trial success.
- Establishing Protocols for Starting Material Variability: Developing strategies for sourcing both autologous and allogeneic cells to ensure consistent quality
- Early-Phase Analytical Strategies: Employing robust analytical methods to monitor product consistency throughout early development
- Ensuring Reproducibility Across Batches: Addressing challenges in material variability and ensuring a consistent product for clinical trials
1:00 pm Workshop D: Technology & Digitalization for Scalable, Reproducible & Data-Driven Cell Therapy Manufacturing
Synopsis
This workshop will explore the critical role of technology and digitalization in optimizing cell therapy manufacturing. The session will cover how scientific computing, AI, and automation are shaping scalable, reproducible, and data-driven processes to meet the growing demands of cell therapy production. Participants will also contribute to the development of a white paper summarizing key insights and strategies discussed during the workshop, providing a valuable resource for the wider industry.
- Leveraging Scientific Computing and Process Modeling to enhance scalability and reproducibility in cell therapy manufacturing
- AI and Machine Learning for predictive analytics, real-time decision-making, and optimizing production yields
- Automation and Digitalization to streamline operations, ensure quality control, and drive data-driven decision-making across the entire production process