Two Planning Mistakes That Quietly Sink Clinical Programs
By John Oncea, Chief Editor, Clinical Tech Leader
Ask Natasa Rajicic, ScD, what separates clinical development programs that succeed from ones that struggle, and she won’t point to a piece of technology. In 25 years spanning Pfizer, Cytel, and her own consulting practice, she’s watched programs derail for reasons that have nothing to do with what software they bought and everything to do with decisions made, or skipped, before the first patient ever enrolled.
Two of those decisions came up repeatedly in our conversation. One is a single planning document that most programs either have or don’t. The other is a shortcut that’s tempting enough that experienced teams still take it, even though Rajicic calls it “low-hanging fruit” in the most damning sense of that phrase.
The Document She Asks For First
Every time Rajicic starts working with a new client, she asks the same question before anything else: do you have a target patient profile? “I always firstly think of target patient profile,” she said, “which is elements of the future product, how it will be differentiated and placed on the market.” Not just placed on the market, either. How it will actually be used in the clinic, how patients will take it, and what will differentiate it from existing therapies.
The absence of that document is, in her experience, the clearest early predictor of a program that will wander. “If that is a starting point,” she said, “the whole development program is much more on track and easier to develop.” Without it, teams generate data as they go, but without a fixed sense of what they’re actually trying to prove. “Data can take you in different directions and you kind of meander and follow and maybe lose track,” she told me. The target patient profile can be updated as a program matures, but its absence at the outset is what she watches for first.
The second piece of that same planning failure is who’s in the room when the profile and the early protocol take shape. Rajicic sees a recurring pattern, especially at smaller companies: a two-person core team of a clinical development lead and a clinical operations lead, deciding on their own when to pull in other functions. “That doesn’t always work,” she said, “because you don’t always know what input you need.”
Regulatory, CMC, biostatistics, and clinical pharmacology all shape decisions made at this stage, whether or not they’re consulted. Her advice isn’t complicated: bring in people with different expertise early, not because every input will change the plan, but because you can’t know in advance which input will matter. “It’s not knowing what you don’t know,” as she put it twice, in two different parts of our conversation.
The Rush Nobody Wants To Admit To
The second mistake is more specific and, in Rajicic’s telling, more expensive. It’s rushing dose selection and population definition into Phase 3 without having clearly answered either question first. “A lot of times what I see is, and it’s almost like a low-hanging fruit, but it still happens,” she said. “It’s rushing through the dose selection, population definitions, and then rushing with that into Phase 3 without those questions clearly understood.”
Phase 3 is supposed to be confirmatory: you find something in earlier phases, then confirm it at scale. But Rajicic has repeatedly seen programs enter Phase 3 without a clear sense of what response to expect from the chosen dose, sometimes because the dose hasn’t been used in quite that way before, or because the population differs meaningfully from what was studied earlier. “You start seeing that maybe the dose hasn’t even been used before, or the population is too different from what was studied before, that you can’t expect a similar result,” she said. “There are so many balls in the air here that you shouldn’t be that way.”
The financial stakes escalate sharply at this transition. “We are talking millions versus billions,” she said, comparing earlier phases to Phase 3. Some sponsors skip a proper Phase 2 dose-ranging study entirely and move straight from Phase 1 to Phase 3. When that happens under time or funding pressure, Rajicic’s description of the result is blunt: “Rush through that site initiation and first patient in, celebrate that, have a press release, and then hope for the best.”
What Reduces The Risk
Rajicic pointed to two concrete mitigations. The first is planning for adaptive designs deliberately, in advance, rather than treating them as an improvisation once a trial is already underway. “You can then possibly control some of those risks with adaptive designs if you’re aware of that, if you have a plan,” she said. Adaptive elements only help if they’re built into the protocol with foresight, not bolted on after a program has already committed to an underpowered dose assumption.
The second is a function she believes is systematically underused at exactly the point where it matters most: clinical pharmacology, at the transition from Phase 1 or Phase 2 into the recommended Phase 2 or Phase 3 dose. “People are overlooking possibilities of clinical pharmacology that can step in and answer some questions: how well did we choose this dose? Is it reliable? What is the dose-response relationship? What are the expected responses for certain populations?” That’s a specific, actionable checkpoint for any clinical technology leader reviewing a program’s readiness to advance.
How To Tell If Your Program Already Has This Problem
Neither mistake announces itself early. Rajicic described the dose-selection gap in particular as something that “creeps up” rather than arriving as an obvious red flag. “It’s not so black and white,” she said. “It’s not like you come in and say it’s immediately obvious.”
It typically surfaces once a team starts seriously planning Phase 3 and realizes the assumptions underneath the chosen dose were never fully tested. By then, the cost of correcting course has grown substantially. The same is true of a missing target patient profile: a program can run for a year or more generating data before anyone notices the underlying strategic question was never answered, only that data kept accumulating without a clear destination.
The Common Thread
Both mistakes trace back to the same root cause: decisions made without enough cross-functional expertise, at a stage when the cost of being wrong is still relatively cheap to fix. A missing target patient profile and a rushed dose-response answer look like different problems on paper. In Rajicic’s experience, they’re the same problem wearing two different disguises: teams that didn’t bring in enough of the right people, early enough, to catch what they didn’t know they were missing.