Introduction
In advanced therapies, there’s a growing expectation that process can solve everything. Standardize the inputs, control the steps, optimize the system—and the outcome should follow. But biology doesn’t always cooperate. As cell and gene therapies become more complex, the limits of that control are becoming harder to ignore, surfacing not as isolated issues but as persistent variability that cannot be engineered away.
For Therese Choquette, Chief Technical Officer at Tigen Pharma, that tension sits at the center of the field. Her experience—from early CAR-T development to commercialization—has shaped a perspective grounded less in ideal systems and more in how those systems behave in reality. “I was really happy to see a focus on analytics,” she said. “Usually it’s just process, process, process… analytics has been a little bit in the shadow.” Her point reflects a broader shift: as therapies evolve, the industry is being pushed to confront not just what it can control, but what it cannot.
Where Biology Challenges Process
At the core of Choquette’s thinking is a disconnect she sees playing out across development: the gap between what teams expect from their processes and what biology actually delivers. “Everyone expects that the potency assay is going to predict everything,” she explained. But in practice, outcomes are shaped by far more than a single measurement, and often by factors that sit outside tightly controlled systems.
One of the most underestimated variables is the starting material. “I think the biggest disconnect… is how much the starting material impacts manufacturing and product,” she said. “We can only control so much.” In cell and gene therapy, where products are living systems, variability is not an exception—it is inherent. Differences in patient material, cell phenotype, and biological response introduce variability that persists no matter how refined the process becomes.
“We cannot control phenotypes,” she noted, pointing to the biological complexity that continues to challenge even the most advanced manufacturing approaches. That reality reframes a core assumption in the field. Process can reduce variability, but it cannot eliminate it. And when expectations are built around that elimination, misalignment follows.
What We Underestimate in Analytics
If variability cannot be removed, then the challenge becomes understanding it. For Choquette, that responsibility falls squarely on analytics—not as a supporting function, but as the mechanism through which the product is actually defined. Yet the effort required to build that understanding is often underestimated.
“How much time and resources it takes to develop a good assay… that is very underestimated,” she said. In heterogeneous systems, even measurements that appear straightforward—cell counts, flow cytometry, potency readouts—require extensive validation across conditions, timepoints, and sources of variability. What seems simple on the surface quickly becomes complex when applied to real-world biology.
“Your product is only as good as your analytical method,” she emphasized. That statement reflects a broader shift across the field: analytics is no longer just confirming what has been built—it is determining how the product is understood, described, and ultimately trusted.
The System Has Changed
Choquette’s perspective reflects a larger transition across the life sciences ecosystem. As therapies become more advanced, the limits of control are becoming more visible—not just to developers, but to manufacturers, regulators, and patients relying on consistent outcomes from inherently variable systems. The field is moving away from a process-centric model toward a more integrated one, where biology, analytics, and manufacturing must be understood together rather than optimized in isolation.
In that environment, collaboration becomes less of an advantage and more of a requirement. “I like to help and collaborate and learn,” she said, emphasizing the need for shared progress in a space where complexity continues to outpace any single organization. At the same time, emerging technologies offer opportunities to simplify and strengthen how therapies are evaluated. “I think we can make QC so much easier and leaner with that new technology,” she noted.
The Bottom Line
Even as tools improve and processes become more refined, one truth remains: not everything in advanced therapies can be engineered away. Biology continues to define the boundaries of what is possible, introducing variability that must be understood rather than eliminated.
The companies that succeed will not be the ones that try to control everything.
They will be the ones that understand what they cannot.
