Understanding the Journey from Preclinical to Post-Market—And the Disasters Along the Way
By the end of this module, you'll be able to:
Drugs don't just magically appear on pharmacy shelves; they go through a gauntlet of testing. And often drugs fail. Sometimes spectacularly, in full public view. Your job as a sales rep is to know where your drug has been, what it survived, and what could still go wrong.
Drugs endure an arduous developmental path. Screening hundreds of thousands of compounds may yield a few hundred potential candidates. Only a few of these potential candidates become "lead compounds" toward research and development (R&D) within a company's clinical pipeline. Each step of preclinical and clinical development is strictly regulated by a country's government agency, which in the US is the FDA (Food and Drug Administration), part of the Department of Health & Human Services (HHS).
Manufacturers must document ALL aspects of a drug's preclinical and clinical development for regulatory scrutiny. That means MOUNTAINS of paperwork. If you think YOUR job has bureaucracy, imagine being the scientists and the regulatory affairs professionals!
clinical trials get exponentially more expensive as a therapeutic "candidate" moves through the trial phases. Depending on the disease, the number of patients* may be significantly fewer (for example, in a rare or orphan disease) than the generalized "number" in the table below.
| Phase | Number of Patients* | Typical Cost | What Can Go Wrong |
|---|---|---|---|
| Phase I | 20-100 | $1-5 million | Severe adverse events, dosing disasters |
| Phase II | 100-500 | $10-50 million | No efficacy signal, wrong endpoints |
| Phase III | 1,000-5,000+ | $100-500 million | Fails to beat placebo/competitor |
| Phase IV | Thousands | $50-200 million | Real-world safety issues emerge |
Think of clinical development as a series of gates. Each phase is designed to answer a specific question:
⚠️ The average cost to bring ONE drug to market costs ~$2.6 BILLION. 90% of drugs that enter Phase I will NEVER make it to approval. At EVERY phase of drug development, things can — and DO — go catastrophically wrong.
Preclinical studies involve cell or animal models to identify potential drugs.
Goal: Evaluate the safety and therapeutic profiles of a potential drug in a controlled and contrived environment.
What works in mice doesn't always work in humans. In fact, about ~90% of drugs that pass preclinical testing FAIL in human trials:
Since ~90% of drugs that pass preclinical testing FAIL in humans, since animal models don't perfectly predict human response, and since preclinical studies test safety and mechanism in cells and animals BEFORE human trials... Preclinical data discussions tend to fall under medical affairs' communication domains.
⚠️ Marketed drugs may show preclinical data in new (translation: off-label) applications that the physician community hears about. Thus, when/if doctors ask about preclinical data, be ready to share your company's medical affairs (medical science liaison) contact.
Phase I trials may be called introductory, pilot, feasibility, or prototype studies.
Primary Goal: Test the safety of a drug in a small group of human subjects (typically 20-100 people) and identify:
Phase I trials are sometimes referred to as "dose finding" or "dose escalation" studies because their primary goal is to assess the maximum tolerated dose (MTD) of a therapeutic.
Other parameters in the safety profile of a prospective treatment include:
A dose escalation usually begins with a small group of patients, called a cohort, who receive a starting dose of the therapeutic.
Depending on the side-effect profiles experienced by the first cohort, successive cohorts will receive increasing doses of the drug until the clinical investigator determines that the therapy's side effects have become unacceptable.
This dose-limiting toxicity (DLT) marks the highest dose used before the unacceptable side effect appears. Once the MTD and DLTs have been established, the therapeutic enters Phase II trials, which involve larger sample sizes and patients with conditions for which the therapy would be indicated.
Important Note: Dosages used in subsequent trials are usually LESS than the MTD determined in the Phase I trial. Additionally, side-effect profiles observed in Phase I studies provide clues to how side effects may be effectively managed in later clinical studies.
Most Phase I studies involve human subjects who are healthy volunteers. Some Phase I studies involve patients with a pre-existing condition for which no alternative treatments may exist. Phase I studies are prominent in oncology, where novel therapeutics are tested in cancer patients whose conditions are refractory (resistant) to available treatments.
Ethical Considerations: Clinical investigators view Phase I trials as ethically complex based on the risk-benefit ratio. Phase I clinical trials have a favorable risk-benefit ratio for cancer patients, who often have advanced cancer and have exhausted available treatment options. However, the use of healthy volunteers in non-oncology Phase I trials raises different ethical concerns.
Cancer patients (with compromised liver/kidney function) can get the same dose as what a healthy human subject (volunteer) appears to tolerate in Phase I. However, due to compromised organ function(s) from disease or prior medications/treatments, cancer patients are unable to metabolize / clear out the drug as quickly. Drug then accumulates in the cancer patients' organ(s). Result? Unexpected toxicity in Phase II. This is why most oncology Phase I trials now use actual cancer patients instead of healthy volunteers—even though it's riskier for those patients.
⚠️ Healthy volunteers metabolize drugs differently than sick patients. Clinical study patients can also metabolize drugs differently than "real world" patients. This is why Real World Evidence (RWE) matters.
Phase II trials assess the efficacy of the drug in a given indication. Phase II studies are often expansions of Phase I trials (scale-up in more patients, typically 100-500). In some cases, drugs have been approved based on results of Phase II studies alone—especially in rare diseases where large Phase III trials aren't feasible.
The "scientific robustness" (Level of Evidence) of experimental design and timeliness of completion of Phase II trials are important, especially:
National guidelines shape prescribing decisions by accounting for treatment goals and therapeutic clinical data in a disease state. These same treatment goals or clinical outcomes are considered during clinical study design to most accurately detect the therapeutic effect(s) of a drug.
Example of a Phase II Fail: REGEN-001 (BC 007) for Long COVID
The Phase II trial for REGEN-001 (BC 007) by Berlin Cures, an immunology drug previously promising for heart failure, failed to improve symptoms in patients with chronic Long COVID in 2025.
Key Failure Concept: Inappropriate Endpoints and Patient Selection. The trial struggled due to a too diverse patient group and inappropriate trial endpoints, highlighting the complexity and differences in post-viral syndromes.
Example of a Phase II Success: MM120 (LSD for Anxiety)
MindMed's Phase II trial for MM120 (LSD) for Generalized Anxiety Disorder (GAD) was a major SUCCESS. The positive results earned significant media buzz and potential FDA fast-track designation, demonstrating a clear efficacy signal that justifies a large Phase III trial.
Remember: Phase II tests efficacy — "Will this drug work?" (not just "Is it safe?") 70% of Phase II trials fail because the wrong endpoints or patient population were selected, or the drug candidate showed no efficacy signal. Drugs for rare diseases may get approved on Phase II alone, but confirmatory trials are usually required, and because of the small sample size, important safety signals may not emerge until later or with more patients.
⚠️ Phase II can be a GAME-CHANGER when the trial is well-designed, the endpoint is clear, and the effect size is large. This is why rigorous Phase II data matters.
Phase III trials are the make-or-break stage, often called comparative or head-to-head trials. ThePrimary goal of Phase III studies is to confirm the drug's efficacy by comparing against a competitor or placebo, and to fully assess the safety profile in a large, diverse patient group. Trials are typically randomized, multi-center, and involve a large number of patients (1,000 to 5,000+).
Phase III studies are extremely costly (typically $100–$500 million) and can take a long time to complete recruitment, collect and analyze data, and share/publish results. Approximately 50% of Phase III trials fail, often because the promising Phase II data was misleading or the trial design was flawed.
Example of a Phase III Fail: Relyvrio (ALS) — The Accelerated Approval Trap
Relyvrio (for ALS) received FDA Accelerated Approval based on small Phase II data (CENTAUR study) but subsequently failed its confirmatory Phase III trial (PHOENIX) in 2024, leading to its market withdrawal.
This disaster underscored a risk and ethical dilemma of the accelerated approval pathway. Should the FDA approve drugs based on weak Phase II data to give patients a potential treatment option where few or none exists, or wait for rigorous Phase III data to ensure the drugs actually WORK? Patients receiving accelerated approval study drugs trade the promise of a potential treatment that makes a difference in their disease against the real possibility that the study drugs may not work for them, and they may have lost precious time to the experimental drugs.
Phase III is the "make or break" trial that is large (1,000-5,000+ patients), expensive ($100-500M), and confirmatory. ~50% of Phase III trials fail because Phase II data was misleading or trial design was flawed. Accelerated approvals are risky — if confirmatory Phase III fails, the drug may get pulled from the market if alternative study designs or inappropriate or not (financially) feasible, and company programs (and people) who support that pipeline drug may lose their jobs. Comparative trials matter — doctors want to know how your drug stacks up against competitors or standard of care.
If your drug was granted accelerated approval, be transparent. Acknowledge the pathway's risk while confidently stating you're running (or have completed) the required confirmatory Phase III trial to support the earlier data.
Phase IV trials, or Post-Marketing Studies, are conducted after the drug has been approved and is on the market. These studies are designed to gather additional safety and efficacy data, often mandated by the FDA. Companies also use Phase IV to differentiate their drug from competitors and potentially support future label expansions.
A crucial distinction exists between these controlled studies and general surveillance: Post-marketing Phase IV studies are experimental, whereas patient registries (a source of RWE) are observational.
In 2025, Real-World Evidence (RWE) has become a major focus, representing data collected from non-trial sources like electronic health or medical records (EHRs or EMRs), insurance claims databases, and wearable devices. RWE is critical because controlled clinical trials typically use very strict inclusion criteria, failing to represent the messy, real-world patient population.
The FDA increasingly accepts RWE to support post-market safety surveillance, new indication approvals, and changes to drug labeling. This is particularly important for identifying rare adverse events that only surface when a drug is used by thousands of patients. Safety issues not observed in trials can emerge with widespread use, leading to major consequences, including drug withdrawals, highlighting the necessity of rigorous Phase IV monitoring and RWE tracking.
Phase IV Post-marketing studies are conducted after FDA approval to gather more safety/efficacy data. RWE is critical for showing how the drug performs in real-world patients excluded from trials. Post-market failures are real, because real-world data reveal critical efficacy and safety signals that can be missed in controlled clinical study settings.
The clinical trial process has rapidly evolved, driven by the need for greater efficiency, flexibility, and patient centricity. Modern innovations aim to reduce time and cost while improving the quality and relevance of the data collected.
Adaptive designs allow for pre-specified modifications to the trial while it is underway, based on interim results. This enables researchers to drop ineffective doses (or arms) or shift seamlessly between phases, saving time and resources. Key examples include Basket Trials (testing one drug across multiple diseases with a shared biomarker) and Umbrella Trials (testing multiple drugs in one disease based on patient biomarkers).
Decentralized Trials (DCTs) allow patients to participate from home, utilizing technology like telemedicine, remote monitoring devices (wearables), and home nurse visits. The primary benefit is increasing patient diversity and recruitment speed, as participants no longer need to live near a major trial site.
Modern trials capture data beyond traditional lab values:
Digital Endpoints: These use technology, such as wearable devices (e.g., measuring activity in heart failure trials) or smartphone apps, to collect objective, continuous data instead of relying on periodic clinic visits or patient recall.
Patient-Reported Outcomes (PROs): PROs capture the patient's direct perspective on symptoms, quality of life, and treatment satisfaction. Regulatory bodies and payers increasingly require PROs because they provide evidence that a drug improves a patient's actual life, not just their lab metrics.
⚠️ If you don't understand clinical phases, you will lose credibility instantly with a physician. Your role is to be a confident, knowledgeable resource, not just a messenger.
You must be ready to detail your drug’s specific clinical path: the number of patients studied, the primary endpoints met, and any key setbacks or safety signals encountered. Knowledge of your drug's story from Phase I to Phase IV allows you to address physician skepticism with facts.
Anticipate the common failure points associated with each phase (e.g., poor safety in Phase I, lack of efficacy in Phase II, failure to beat the comparator in Phase III) and have a prepared, evidence-based response (see table below).
| Phase | What Can Go Wrong | How to Address It |
|---|---|---|
| Phase I | Severe adverse events, dosing disasters | "Our Phase I trial had rigorous safety monitoring with no serious AEs." |
| Phase II | No efficacy signal, wrong endpoints | "Phase II showed a 40% improvement, which was confirmed in our large Phase III study." |
| Phase III | Fails to beat placebo/competitor | "Our Phase III trial met ALL primary and secondary endpoints, demonstrating superiority." |
| Phase IV | Real-world safety issues emerge | "We've been on the market for 3 years with 100K patients—the safety profile remains excellent." |
Doctors respect transparency. Never use vague, superlative language like "100% safe". Instead, provide specific data: "In our Phase III trial, 65% of patients achieved remission, with the most common side effects being mild nausea in 10% of patients". If a doctor mentions a major industry disaster, acknowledge the lesson learned and immediately pivot to how your company's trial design specifically mitigated those risks.
Here are real-world scenarios reps face in the field. Use what you learned in this module to craft your responses.
Doctor says: "This looks promising, but it's only Phase II data with 150 patients. I'll wait for Phase III."
"That's a smart, evidence-based approach—Phase III is the confirmatory stage. You're right that Phase II is preliminary, but it proved a clear efficacy signal: our primary endpoint showed 42% complete remission vs. 18% with standard of care. We're now running a 1,500-patient Phase III trial with results expected in 6 months. Can I check back with you when those Phase III results are published?"
"But the Phase II data is really strong! 150 patients is enough."
(Defensive, disrespects the doctor's need for confirmatory data, and ignores the 50% Phase III failure rate)
Doctor says: "We all remember Relyvrio. Approved on Phase II data, then failed the large Phase III and got pulled. Why should I trust your Phase II results if you're going for accelerated approval?"
"That's exactly the right, ethical question to ask. Relyvrio taught the entire industry about the risk of the accelerated approval pathway. Our Phase II was significantly larger—350 patients vs. Relyvrio's 137. Our endpoint was more clinically meaningful and robustly validated. We respect the pathway's risk. Would it help if I showed you the comparative trial designs to explain how we mitigated the statistical issues faced by the PHOENIX study?"
"That was a totally different drug and disease, you can't compare them."
(Dismissive, fails to address the doctor's legitimate, concept-based skepticism about Phase II reliability for *any* accelerated drug)
Doctor says: "Your Phase III trial excluded patients over 75 and anyone with renal impairment. That's simply not my everyday patient population. I need real-world data."
"You're absolutely right. Clinical trials often use narrow criteria and don't reflect complex real-world patients. That's why our Phase IV commitment to Real-World Evidence (RWE) is so important. From our RWE database of 8,500 patients, 32% are over 75 and 41% have renal impairment. No new safety signals have emerged in these older or more complex patients. Would you like our medical affairs to share this new data when it's available?"
"Those are standard exclusion criteria for trials, and our drug is approved now."
(True but unhelpful—dismisses the RWE concept and the doctor's specific patient care concern)