How do 1 in 16 cell and gene therapies fail, not because of the biology, but because of the supply chain?


In this episode of Out of the Lab, host Nico sits down with Mehran, a seasoned Cell & Gene Therapy supply chain consultant, to dissect why operational resilience must be engineered into your product long before tech transfer ever takes place.


From CDMO selection gaps to un-addressable spend and non-standard Bill of Materials (BOM) choices, Mehran exposes the hidden operational traps that trigger FDA Complete Response Letters (CRLs) and derail launches.


In this episode, we cover:

  • Who Owns Resilience? Why supply chain expertise must intersect with early CMC and process development.

  • The CDMO Bottleneck: Unpacking why 40% of manufacturing-related FDA hurdles stem from partner selection and process optimization gaps.

  • Addressable vs. Non-Addressable Spend: Why 42% of materials get locked in filings and how to optimize raw material selection up front.

  • Real-World Harmonization: Lessons from J&J’s Carvykti pipeline on managing apheresis variability and standardizing network supply.

  • The Future of Orchestration: How AI and predictive analytics are transforming patient slotting, scheduling, and apheresis quality.


Timestamps & Chapters:

  • 00:00 – Introduction: Supply chain resilience in Cell & Gene Therapy

  • 02:03 – Who owns resilience? Bridging CMC, process development, and supply chain

  • 04:57 – CDMO partner selection & commercial readiness

  • 06:21 – The cost of failure: CRLs, manufacturing quality, and CDMO gaps

  • 08:05 – Process ownership vs. CDMO lock-in: Lessons from J&J and apheresis

  • 12:21 – Addressable vs. non-addressable spend in biomanufacturing

  • 16:38 – The 50 mL Syringe Example: Why process engineers need supply chain optics

  • 20:15 – Geopolitical risk, tariffs, and global facility harmonization

  • 24:18 – Built-in network resilience: Lessons from radiopharmaceuticals

  • 28:20 – Logistics, cold-chain, and patient orchestration in Europe vs. US

  • 34:34 – The role of data, AI, and predictive analytics in apheresis quality

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