Clinical trials are designed to answer one question: Is the drug safe and effective?
What they are not designed to answer is what happens when the drug enters a world that looks nothing like the one it was tested in. Different patients. Different circumstances. Different barriers. The trial was a success. That doesn’t always mean the patient gets better.
Consider what that looks like in practice.
A woman in her mid-forties is diagnosed with breast cancer. Her oncologist identifies a drug that was recently approved by the FDA and has compelling data. She qualifies. He prescribes it. On paper, she is exactly the kind of patient this drug was designed for.
But she never got the drug.
Not because the drug failed. Because she lives 90 minutes from the nearest infusion clinic, can’t afford to miss work every two weeks, and after multiple prior authorization appeals and mounting delays, treatment still hadn’t been approved. Eventually, the window for timely intervention began to close.
In the trial that proved this drug worked, she didn’t exist. Participants were recruited from academic medical centers in major metros. They had reliable transportation, kept scheduled appointments, and received the drug at no cost. The variables that define her life — distance, cost, time, and an insurance system that quietly bets on her giving up — were never part of the equation.
The trial answered its question. Is the drug safe and effective? Yes.
But that was never the only question that mattered. The one that actually determines whether a treatment succeeds in the real world is harder and far less convenient to answer: will this drug work — for this patient, in this clinic, in this town, with these insurance hurdles, these comorbidities, this healthcare provider who’s still waiting to see how their colleagues’ patients do first?
Those are different questions. And for too long, pharma has treated the first answer as a sufficient substitute for the second.
It isn’t.
The Controlled World vs. The Real One
Before a drug reaches a single patient outside a research setting, it has to prove it can do what it claims — safely, consistently, and under conditions rigorous enough to satisfy one of the world’s most demanding regulatory bodies. That process has produced some of the most meaningful medical advances of the last half-century. The innovation happening right now in oncology and immunology alone is extraordinary.
But here’s what a clinical trial is not designed to do: reflect the world most patients actually live in.
By necessity, trials are controlled environments. Participants are carefully selected. Dosing is monitored. Appointments are kept. The drug is free. Most trials are conducted at academic medical centers in major metropolitan areas. And that means the patient population participating in the trial tends to be healthier, better resourced, and more closely managed than the broader population who will eventually be prescribed the same drug.
That’s not a criticism. It’s a design feature. Control is what makes the science valid.
The challenge comes after the trial is completed, when that carefully controlled data meets the unpredictable reality of everyday life.
Once a drug launches, it moves into the hands of community healthcare providers who may see only a handful of patients with a given condition each year, in clinics stretched too thin to provide the same level of monitoring as a trial site. It reaches patients in rural areas who can’t make every scheduled appointment, patients managing four other conditions, and patients whose insurance company will make them fight for every refill. In the real world, there is no compensation for participation, no transportation stipend, and no research coordinator to ensure every dose is taken on schedule.
What remains is something no trial can replicate: real life.
Clinical trial data tells you what a drug can do. Real-world evidence tells you what it actually does. And while that gap has always existed, the conversation about what to do with it is, surprisingly, still in its early stages.
The science answered its question. Now comes the harder one.
The Variables Nobody Tested
The gap between clinical trial data and real-world outcomes runs deeper than patient compliance. Adherence is shaped by dozens of contributing factors, including cost, access, education, support systems, and the complexity of the treatment itself. No single variable can explain it, and no single solution can fix it.
There is no single variable that explains the gap. There are dozens. And they interact with each other in ways that no trial protocol was ever designed to anticipate.
Start with access — and not just the insurance conversation the industry defaults to, though that matters enormously. Access is made up of many layers, and any one of them can be the reason a patient never starts a treatment or doesn’t stay on it.
But before access even enters the picture, there’s a more foundational problem: who was in the trial to begin with?
Clinical trials have historically underrepresented women, older adults, and minority populations, in particular African Americans, Latinos, and other communities of color. In indications that aren’t gender-specific, female patients are often enrolled at rates that don’t reflect their share of the actual patient population. Older women are frequently excluded due to age cutoffs or comorbidity criteria. And minority populations, who often bear a disproportionate burden of chronic and serious disease, remain underrepresented in the data. The result is a clinical dataset that reflects a narrower slice of humanity than the population the drug will actually be prescribed to.
Geography compounds this further. Clinical trials are often conducted at academic medical centers concentrated in major metropolitan areas. Patients who live two hours from the nearest infusion clinic or who can’t get a blood draw every two weeks were not included in that trial. Geography, however, is only one factor.
Access depends on whether a patient receives the correct diagnosis, whether the right treatment is selected for his specific situation, and whether the drug is actually available. Then there’s cost, which stops patients before they even start. Logistical impediments, such as blood work or frequent office visits, make it difficult to remain on the treatment over time. And then there’s administering the drug, which may require an injection, an infusion, or a regimen so demanding that patients quietly decide it isn’t worth it.
Doctors are working with data that was never generated with any of this in mind. This is precisely where market research in the pharmaceutical industry.
Then there’s the insurance system itself — a barrier so familiar it has almost stopped registering as a problem. In a trial, the drug is free. In the real world, a prior authorization denial doesn’t just delay treatment. It starts a clock. Every form that goes unanswered, every appeal that requires a follow-up call, every week the patient waits is another opportunity to give up.
The burden doesn’t fall on the patient alone. Physician offices are increasingly hiring staff specifically to manage insurance challenges. While this is a workable solution for large practices, the same cannot be said for small and mid-sized practices, where the person handling prior authorizations is also juggling a dozen other responsibilities. When those requests get deprioritized, not out of indifference but out of capacity, patients wait longer. Some stop waiting altogether.
And insurance companies, whether by design or consequence, are counting on some percentage of patients doing exactly that. Those who push through tend to have an advocate in their corner — a spouse who knows how to navigate the system, a caregiver who won’t take no for an answer. That is not most patients.
The drug interaction problem is quieter but just as consequential. A trial can test for known interactions — if a patient is likely to be on a beta blocker, researchers can account for that. What no trial can do is test for every combination of prescription medications, over-the-counter drugs, vitamins, and supplements that real-world patients bring to their treatment. A patient managing a sleep disorder who is also taking supplements their HCP recommended for a comorbid condition, and who is now asked to go off all of them to participate in a trial, is not representative of the patient who will actually be prescribed that drug when it launches. The interactions that emerge in the real world are not surprises. They are simply variables that were never part of the study.
Perhaps the most underappreciated gap, though, is patient education. In a trial, adherence is practically engineered. Coordinators follow up. Instructions are reinforced. The protocol ensures patients know exactly how and when to take their medication. That infrastructure does not exist in a community physician’s office, where an HCP may see dozens of patients a day and has only minutes to explain a new treatment.
The consequences can be significant. A stimulant prescribed for ADHD, for example, may require specific dietary pairing and precise timing tied to a patient’s circadian rhythm to deliver its full effect. Without that information, a patient who isn’t seeing results doesn’t conclude that the instructions were incomplete. She concludes the drug isn’t working. And she stops taking it.
That’s not a clinical failure. That’s a communication failure. And it won’t show up anywhere in the trial data.
Healthcare Providers Are Quietly Adjusting Their Expectations
Something happens in nearly every HCP’s office when a new drug launches. But it doesn’t appear in any clinical readout, any market analysis, or any post-launch tracking report. The healthcare provider reads the trial data, listens to the rep, and then quietly recalibrates.
The science is controlled, the methodology is rigorous, and physicians know exactly what they are looking at. What they have learned over years of practice is that trial outcomes will vary for their patients. Because they know their patients. And their patients don’t look like trial participants.
This quiet skepticism is one of the most consequential and least examined forces in pharmaceutical adoption. Healthcare providers aren’t rejecting new drugs. They’re hedging. They’re watching. They’re waiting for colleagues to run the real-world experiment before they commit their own patients to it. Depending on the drug, the indication, and the severity of potential side effects, the wait can stretch from a few months to a few years.
“HCPs trust the clinical data because it is controlled and the process is rigorous. And they are wary of what the actual outcomes will be for similar reasons,” says Jim Sharples, who co-leads KS&R’s Healthcare Industry Team and has spent decades studying prescriber behavior.
Physicians adapt. When they anticipate that adherence might be a problem, they find workarounds. These small, practical adjustments happen quietly at the practice level and rarely make it back to the brand team. But they are among the most useful pieces of intelligence a pharma company can have — a real-world signal that something in the original treatment model isn’t working as intended.
A healthcare provider’s first impression of a new drug is formed the moment trial results are presented to the medical community. Understanding what HCPs actually heard, what they assumed, and what biases they formed is some of the most valuable intelligence in pharmaceutical market research. By the time a brand team is reviewing prescribing patterns six months post-launch, those impressions have already hardened into habits.
The solution to HCP skepticism has always been real-world evidence from clinical practice, showing what a drug does in the full complexity of human life. That evidence doesn’t exist at launch. It has to be built. And building it requires a strategy most brands haven’t put in place before the drug ever ships.
The “Why” Nobody’s Asking
Post-launch tracking in pharma is, by and large, a “what” exercise.
● How many healthcare providers are aware of the drug?
● How many have tried it?
● How many patients are still on it at 90 days?
These are useful numbers. They are, however, not useful explanations.
Knowing that 30% of patients discontinued in the first three months tells you something went wrong. It tells you nothing about what.
● Were the side effects worse than expected?
● Was the prior authorization process too burdensome?
● Did patients not understand how to take it correctly?
● Did their doctor never explain what to do if they missed a dose?
● Did the prescriber’s office switch to another comparable treatment because it was easier for staff to process?
The numbers don’t tell you why. And if no one is asking, the brand team won’t know “why” either. This is the “why” gap, and it’s where the most actionable intelligence in pharmaceutical market research lives.
Mary Curry, Vice President of the KS&R Healthcare Industry Team, has watched this pattern repeat across indications: “They’re asking what is happening. Not why it’s happening.”
The distinction sounds simple. The implications can be significant. Because the “why” is what tells you whether you have a messaging problem, an access problem, an education problem, or something deeper in the product experience itself. Without it, you’re pushing levers without knowing what they’re connected to.
The “why” also lives at the practice level in ways that aggregate data can’t capture. Some physician groups are dramatically more successful at onboarding patients to a specialty drug than others. How they set expectations. How they handle the prior authorization process. How they follow up. Identifying what those high-performing practices are doing differently, and understanding whether it can be replicated elsewhere, is exactly the kind of insight that moves the needle. But it requires someone to go looking for it.
Proactive Looks Like This
Most pharmaceutical brands begin developing their launch strategy 18 months or more in advance. Messaging gets refined. Access programs get designed. Sales teams get trained. It is an enormous operational undertaking.
What rarely gets built into that 18-month runway is a real-world evidence strategy. Not because anyone thinks it’s unimportant, but because the urgency of launch crowds it out. Post-launch monitoring gets treated as something to figure out later, after the drug is on the market, after the first data comes back.
That sequencing is backward.
By the time a brand team is reacting to a drop-off problem, a coverage gap, or a prescriber adoption curve that has flatlined, the window to get ahead of it is closing. The patients who gave up on the prior authorization process in month two didn’t wait for the brand team to develop a solution. The healthcare providers who tried the drug once, saw a suboptimal outcome, and went back to their existing standard of care, didn’t pause their prescribing habits while the data caught up.
The brands that close the gap between trial data and real-world outcomes don’t do it by responding faster. They do it by building the infrastructure to listen before there’s anything urgent to hear.
That means deciding before launch which patient populations are most at risk of falling through the cracks, and designing research to monitor them. It means tracking not just the patients who are on the drug, but the ones who couldn’t get it and the ones who left. Absence of data is often proof that no one was looking in the right places.
It also means treating the HCP relationship as an ongoing conversation rather than a launch event. The prescriber who adopted early and is seeing strong results knows something. The one who tried it twice and stopped knows something different. Both of those signals are valuable. Neither shows up in a standard tracking study.
Done well, this kind of proactive monitoring isn’t just a risk management tool. It’s a competitive one. Understanding why certain practices outperform, why specific patient segments fall short, and why adoption varies by region gives a brand team the ability to act before the market moves without them.
The Trial May Be Over. The Questions Still Remain.
Remember the patient from the beginning, the one who qualified for the drug, whose healthcare provider prescribed it. But who never filled the prescription because the real world got in the way before she ever had the chance.
The gap is between a remarkable clinical result and a patient sitting in a community clinic two hours from the nearest infusion center, navigating a prior authorization process.
A breakthrough that doesn’t reach the patient is a promising result in a file somewhere.
The clinical trial answered its question. But the real world asks different questions, and it will keep asking until someone decides the answer is worth finding.
The companies that close the gap are the ones that stay curious after launch. They invest in healthcare market research as a strategic imperative, not an afterthought. And they continue to ask why.
About KS&R
KS&R is a nationally recognized strategic consultancy and marketing research firm that provides clients with timely, fact-based insights and actionable solutions through industry-centered expertise. Specializing in Technology, Business Services, Telecom, Entertainment & Recreation, Healthcare, Retail & E-Commerce, and Transportation & Logistics verticals, KS&R empowers companies globally to make smarter business decisions. For more information, please visit www.ksrinc.com.
