AAV at Launch: The Hidden Work of Scaling, Supplying, and Proving Sameness

Captured live at Advanced Therapies Europe 2025, this session distills how to model demand, harden supply chains, align EU and US expectations, and stage scale for late-stage and commercial AAV launches.

Session summary with Philip Wills, CCO, Catalent; Bastiaan Leewis, SVP Manufacturing Science and Technology, MeiraGTx; and Bernd Schmidt, Chief Technical Officer, Sensorion.

TL;DR
In a hurry? Here are the essentials at a glance:

• Start with supply, not steel. Model country-by-country access, hospital overage, and where to place stock. Expect backup vial requests to double perceived output needs.

• Demand is not flat. Many inherited indications create an early peak, then settle toward incidence. Decide now whether you will buffer with stock, validate multiple scales, or both.

• EU vs US needs diverge in practice. Plan for EU QP release, local testing, and compendial differences. Potency often sails through; classic assays like mycoplasma trigger more debate.

• Do not over-or undershoot scale. Push commercial forecasting early so your validation scale fits launch, not a guess.

• Dual source with intent. Launching with two sites adds approval risk. Many teams add the second site post-approval when revenue supports it.

• Comparability is a sampling problem first. Bank process intermediates and DS from early runs so you can bridge methods and standards later.

• AI is useful, but targeted. Today it helps with clinical selection and mechanistic modeling; use digital twins to limit robustness burden and to justify what you do and do not test.

Model demand and supply early

Hospitals, payers, and ministries will shape your inventory more than your reactor size. Rare disease launches often need local backup vials, cold-chain staging, and just-in-time replacement plans. Build that overage into both COGS and capacity.

Do not assume steady state. Many inherited indications spike at launch, then narrow to newborn incidence. Decide whether you will validate multiple scales for the peak or build stock and run down. Both have regulatory and cash impacts.

Choose where to make and test, on purpose

Manufacturing site location is more than tax and tariffs. Talent access, university links, and clinical network proximity all matter. In the EU, a QP will release your lots, and many teams still need some EU testing even if they make in the US.

Tariffs in the mid-teens may be absorbable in total COGS. If they climb, re-run the model. Keep commercial options open for fill-finish close to market.

Harmonize analytics, expect compendial surprises

Potency often gets a fair hearing when the scientific rationale is clear. The unexpected friction comes from classic compendial methods where countries differ on controls and replicates.

Identify country-specific twists early. Where possible, pick methods and acceptance criteria that will survive across regions, then document the scientific bridge.

Scale that fits validation and launch

Lock a validation scale that matches your first 12 to 24 months of commercial demand, not an optimistic midpoint. Push commercial teams for real forecasts so you do not validate at 50 L when you need 500 L, or the reverse.

Dual sourcing and second sites

Two launch sites can slow you down if one misses. Many teams validate a single site for approval, then bring a second site online post-launch to add resilience and regional flexibility.

If you must dual source for volume, budget the extra comparability and align your filings so one site’s stumble does not stall the program.

Make-or-buy, and the real overhead line

In-house can remove real bottlenecks. Teams have internalized plasmids and QC when third-party queues stretched to 18 months. The tipping point is pipeline width and utilization, since overhead often outweighs unit COGS until capacity fills.

What to want from a CDMO

Treat the selection as a partnership test, not a pricing exercise. Look for pockets of excellence that match your phase, low staff turnover, line of sight to commercial, and honest program governance when things go wrong.

You may pair a manufacturing specialist with a separate distribution expert. Few providers excel equally at both.

Comparability by design

Comparability fails without banked material. From your earliest GLP and clinical runs, archive process intermediates and drug substance in volumes that support future bridges across sites, methods, and reference standards.

Document mechanism-based justifications and use them consistently across regions.

AI, digital twins, and what is ready now

AI is not a catch-all for CMC. Today, teams see value in digital twins and mechanistic models to focus robustness studies and defend design spaces. On the clinical side, AI helps with patient identification and secondary endpoints.

Adopt targeted tools rather than broad promises. Use them to justify the testing you run, and the testing you do not.

Geopolitics, China, and risk

China’s capabilities are real, timelines can be fast, and trial models have been flexible. The political risk is also real. If you consider China, many teams limit scope to Asian supply within a broader global strategy and maintain non-Chinese options.

Final word

Commercial AAV lives or dies on details that do not fit on a bioreactor slide. Model demand honestly, design supply with overage, harmonize the analytics that regulators actually question, and stage your second site when it helps rather than hurts. Archive early samples so you can prove sameness later. Do this well and AAV moves from a pivotal dataset to reliable patient access.

Keep the momentum: join the community at Advanced Therapies Week 2026 in San Diego, February 9 to 12, 2026.

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