Everyone Wants Fast And Safe At The Same Time
When I sit with a team planning a new cell therapy program, someone always asks how fast we can get to the clinic. It’s the right question to ask. Patients with rare and neurodegenerative diseases don’t have years to wait for a perfect process. But there’s a trade-off buried in that question that almost nobody says out loud: every month you save on timeline, you usually pay for later, and often at a worse exchange rate.
I don’t say this to argue for slowness. I say it because pretending the trade-off doesn’t exist is how programs get into trouble two years in, not two months in.
What The Trade-Off Actually Looks Like
Early in a program, you have choices about how much you characterize your cell product before you move it forward. You can lock a process quickly with a reasonably good understanding of what’s happening inside the cells, or you can spend more time building a fuller picture of consistency, potency, and behavior across batches.
The fast path looks great on a slide. You hit your first-in-human date. Investors and boards like dates. But if the process wasn’t well understood, you often find out during scale-up or during a later regulatory review, and by then the fix costs more than the time you saved. I’ve watched programs redo work at a stage where redoing it means real delay, not the small kind.
The slow path has its own cost. If you over-characterize before you have any clinical signal, you can spend a year building precision for a product design that clinical data might tell you needs to change anyway. Precision on the wrong molecule is still wasted precision.
Neither path is free. That’s the trade-off. The job isn’t to eliminate it, it’s to decide, deliberately, which risk you’re willing to hold.
How I Decide Where To Sit On That Line
I ask a simple question before any other: which mistake is reversible, and which one isn’t?
If a manufacturing shortcut can be corrected later without touching the patient population or the mechanism, I’ll usually take the shortcut and move faster into early data. If the shortcut touches something that defines whether the therapy works at all, like the durability of the engineered cells or their behavior once shielded or delivered, I slow down there specifically, and only there.
That’s the part people miss. The trade-off isn’t a single dial you set once for the whole program. It’s a set of smaller decisions, and the right answer changes depending on what’s actually at stake in that piece of the work. Treating “speed versus rigor” as one company-wide setting is how teams end up either too cautious everywhere or reckless in the one place they couldn’t afford to be.
A Habit That Helps
Before locking any major process decision, I ask the team to write down, in one paragraph, what we’d have to unwind if this turns out to be wrong. Not a risk assessment with a five-point scale. Just plain language: here’s what breaks, here’s how far back we’d have to go.
If the answer is “we’d redo a small assay,” that tells you something. If the answer is “we’d need to reconsider the cell source,” that tells you something else entirely. Writing it down forces the conversation out of gut feeling and into something the whole team can weigh together.
What I Tell People Running These Programs
Don’t let anyone frame this as a choice between being careful and being fast, as if careful teams are slow and fast teams are careless. That framing hides the actual decision, which is about where you’re willing to accept rework later in exchange for data sooner now.
Rare disease and neurodegenerative disease patients are the reason this matters. A program that moves fast but has to restart at scale-up has, in effect, moved slower than one that took an extra quarter up front to understand its own process. Speed measured at the first milestone isn’t the same as speed measured at the patient’s bedside.
I’d rather be honest with a board about which risks we’re accepting than let a timeline slide look tidy on paper while it hides a decision nobody actually made on purpose.