09:00 – 12:00 | Workshop A
Navigating Novel Ophthalmic Endpoint Development & Regulatory Validation to Accelerate Disease Therapeutic Approvals
Synopsis
Novel endpoint development and validation are major challenges in ophthalmic gene therapy, with regulatory acceptance crucial for approval. Traditional vision measures often fall short in rare, slow-progressing diseases, while patient-reported outcomes add variability. Join us in this workshop to identify effective endpoints and regulatory strategies to increase regulatory approval.
Key Discussion Points:
- Navigating FDA’s RDEA pilot program and building compelling cases for novel endpoint acceptance through strategic regulatory engagement
- Implementing long-term secondary endpoint collection strategies in early-phase studies to establish pivotal trial readiness over 3-4-year timelines
- Eliminating confounding variables in vision testing by distinguishing true visual function from alertness, fatigue, and other behavioral factors that can compromise trial validity
- Advancing objective biomarkers and AI-driven assessment methods to subjective endpoints
12:00 pm LUNCH BREAK & NETWORKING
01:00 – 04:00 | Workshop B
Engineering Advanced Capsid Technologies to Overcome Ocular Barriers & Enhance Scalability
Synopsis
Current vectors face the restriction of the blood-retinal-barriers when injecting into the eye. Therefore, the advancement of AI and large data provides efficient and creative way to pass through this boundary. This workshop examines engineered capsids using highthroughput multiplexing and machine learning approaches to achieve effective delivery at lower doses with reduced inflammatory responses.
Key Discussion Points:
- Harnessing high-throughput multiplexing and machine learning to engineer nextgeneration AAV capsids for intravitreal gene therapy delivery
- Developing engineered capsids that penetrate the inner limiting membrane barrier to enable effective intravitreal delivery
- Implementing high-throughput screening platforms that evaluate capsid variants simultaneously to accelerate discovery beyond traditional approaches
- Integrating machine learning algorithms with capsid performance data to generate vectors achieving therapeutic efficacy at reduced doses