Sr. CMC Consultant CMC & Regulatory Strategy for CGT, Rare Diseases, and Biologics Marina del Rey, California
Dive into the cutting-edge world of ADA-SCID gene therapy with this dynamic session, where you’ll explore a detailed comparison of two pivotal workflows transforming autologous manufacturing. Workflow 1, an 11-day lentiviral process with expansion, and Workflow 2, a 4-day gammaretroviral process without expansion, are compared in detail. Both workflows start with bone marrow harvest and CD34+ purification, followed by transduction with a self-inactivating lentiviral or gammaretroviral vector. Lot-release testing includes ADA enzyme activity (by ELISA), vector copy number (by ddPCR), and CD34+ viability (by cell counter). Predictive analytics link incoming material quality, in-process metrics (e.g., transduction efficiency), and clinical outcomes such as survival and immune reconstitution. Feedback from pharmacokinetic/pharmacodynamic data reduced manufacturing variability in Workflow 1 by 10–15%. Key learnings include poor CD34+ proliferation, myeloid cell suppression, and clinical failures such as engraftment loss and T-ALL. The study highlights how integrated analytics enhances process control, product understanding, and long-term safety in rare disease gene therapy.
Attendees will uncover practical solutions to key obstacles, including poor CD34+ proliferation, myeloid cell suppression, and clinical pitfalls like engraftment loss or the rare T-ALL risk tied to gammaretroviral vectors. You’ll learn how integrated analytics enhances process control, deepens product understanding, and ensures long-term safety for rare disease therapies. This data-driven strategy provides a roadmap for optimizing production, predicting out-of-specification events, and bolstering regulatory submissions. Expect to leave with innovative tools to elevate gene therapy manufacturing efficiency and reliability, making this session a must-attend for scientists, engineers, and regulators eager to shape the future of medicine. Don’t miss this opportunity to master analytics for groundbreaking therapeutic advancements!
Learning Objectives:
Upon completion, participants can explain how predictive analytics, using feedback from in-process metrics and clinical outcomes, optimizes ADA-SCID gene therapy manufacturing, predicts out-of-specification events, derives process and product understanding.
Upon completion, participants can compare the operational efficiency and safety profiles of lentiviral (Workflow 1) and gammaretroviral (Workflow 2) workflows in ADA-SCID gene therapy manufacturing, using data on cell yield, transduction efficiency, and clinical outcomes.
Upon completion, participants can identify critical manufacturing challenges (e.g., poor CD34+ proliferation, T-ALL risk) and propose analytical controls to enhance process robustness and support regulatory submissions for ADA-SCID therapies.