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An Industry Matures at the Point Where Variability Stops Being Acceptable

Gene therapy is arriving at the transition aviation and semiconductors made before it, where the question shifts from whether something can work to whether it can work repeatedly.

By Alicia Moreno· September 11, 2026· 3 min read
An Industry Matures at the Point Where Variability Stops Being Acceptable
Photo Courtesy: Getty Images · source

Every breakthrough industry tells a better story about itself than the work deserves. The outside world sees the bold idea, the discovery, the technology that appears to change what is possible. That version is clean and easy to follow.

Kristofer Mussar, chief operating officer of VectorBuilder and managing director of its German arm, argues that the version doing the actual work is far less appealing. Breakthroughs become industries only when they can be repeated.

A promising idea has to behave consistently outside the environment where it was first proven. It has to be manufactured, tested, reviewed, financed, regulated and trusted. Creativity is not the deciding factor. Discipline is.

Why that lands badly in innovative organisations

Discipline sounds restrictive, as though process exists to slow people down, and in innovation-led companies it is frequently heard that way.

Mussar's counter is that disciplined engineering is what lets innovation move faster without losing control of the risk. The moment an emerging industry matures is not when it generates more ideas. It is when it reduces unnecessary variability.

The cost of skipping that step is specific. Without standards, teams cannot compare results across programmes. Investors cannot judge whether progress is repeatable. Regulators are asked to evaluate systems that may not behave the same way at different stages.

An organisation in that position is not learning. It is performing individual acts of problem-solving and calling the sequence progress.

The question has to shift from can this work to can this work reliably, safely and repeatedly

What it looks like in gene delivery

Early progress in gene therapy depends on specialised scientific insight and programme-specific problem-solving. The science is difficult and the pressure to show movement is real.

As the field moves from experimental promise towards clinical and commercial application, the standard changes. A vector that works once is not enough. A process that depends on exceptional conditions is not enough. A design that performs well in one context while creating uncertainty later is not enough.

The detail that makes this concrete is how small the decisions are. In gene delivery, minor differences in vector design influence expression, manufacturability, stability and regulatory review. Choices that look purely technical at the design stage determine whether a programme advances cleanly or carries risk forward into later development.

Mussar's company has given the response a name, Good Vector Practice, meaning vector design that prioritises reproducibility, manufacturability, safety and regulatory readiness from the outset. He is upfront that the label matters less than the habit behind it.

Standards do not replace judgment

The objection to standardisation is that it substitutes procedure for thinking, and Mussar addresses it directly.

Standards do not remove scientific judgment. They make it more useful, by giving teams a common basis for decisions, making trade-offs visible, and allowing what was learned on one programme to inform the next.

The alternative is the trap. If every vector is treated as a custom exception, the field cannot accumulate learning at all. If each programme solves the same avoidable problem in a slightly different way, everything gets slower and more expensive while appearing busy.

The part that is not about biotech

The wider lesson is the one worth extracting, because it applies well outside laboratories.

Aviation, semiconductors, pharmaceuticals and advanced manufacturing all run on disciplined systems nobody sees. Their progress comes from controlling the critical variables, reproducing outcomes, and improving from a stable base rather than from a fresh start each time.

Industries mature at the point where variability becomes unacceptable. In an early market, flexibility is treated as an advantage: teams move quickly and solve problems as they appear. That works until the volume arrives.

Then the same flexibility that made a company fast becomes the reason it cannot scale, and the organisations that recognised the switch early are the ones still standing.