What’s wrong with clinical trials?
New drugs must pass a series of clinical trials before they can be marketed and sold to the public. These trials are meant to prove that new treatments are safe and effective. It is widely known that clinical trials are extremely expensive — the cost of bringing a new drug to market today is estimated to be more than $2 billion.¹ What is less well known is that astronomical cost ranks a distant second to the biggest problem with clinical trials.
The biggest problem with clinical trials is they take too long. The longer a drug spends in development, the longer it takes for that drug to reach the market and benefit patients. Delays to clinical trials cost billions of dollars and affect millions of patients every year.
What’s holding up clinical trials? Regulatory red tape? Scientific rigor? Corporate bureaucracy? If we want to speed up clinical trials, it makes sense to begin with the biggest bottleneck.
Finding and enrolling patients is the most time consuming part of clinical trials. It is not unusual to see trials take years to enroll, and many trials never reach their enrollment goals. 86% of clinical trials fail to complete patient enrollment on time.² 19% of trials fail because they never enroll enough patients.³ To understand why patient recruitment is so difficult and time consuming, it is helpful to review how trial sponsors (e.g. BioPharma companies) go about it.
Trial sponsors don’t just need to recruit patients, they must also send those patients somewhere for treatment and examination. The front line work of clinical trials takes place at sites, which range in size from a single doctor’s office to a large medical center.
Before a trial can begin, the sponsor must identify, contract with, and activate whatever sites it feels are necessary to enroll and treat a sufficient number of patients. First, the sponsor engages with attractive sites that 1) reach a large number of patients that meet trial eligibility requirements, and 2) have the capacity to administer the trial protocol. Next, the sponsor and candidate sites negotiate a financial agreement compensating sites for their participation in the trial. Finally, contracted sites need to be activated. Activation involves everything from securing study approval from an Institutional Review Board to training site staff and providing required materials. On average, it takes 100 days to activate a single site.⁴
While sponsors are identifying and activating sites, they must also find suitable patients. Trial eligibility requirements have grown more strict as study protocols have increased in complexity.⁵ Stricter eligibility requirements reduce the number of potential patients a trial can enroll and increase the time and expense of screening patients. More complex screening discourages patients from enrolling while increasing the number of patients that must be screened in order to meet a trial’s enrollment goals.
Complex study protocols tend to impose a greater burden on participating patients and increase trial drop-out rates.⁶ The higher the drop-out rate, the more patients must be enrolled to say — with statistical certainty — that an observed effect is the result of the experimental treatment and not a result of chance.
Finally, because patients can only be enrolled in one trial at a time, they are a precious resource to trial sponsors. For many difficult to treat diseases, clinical trials must enroll large numbers of patients to achieve enough statistical power to confidently detect a modest effect on disease progression. Multiple treatment arms — a common feature in complex trial designs — further increase enrollment requirements.
Patient recruitment and enrollment present clinical trial sponsors with many challenges. Surprisingly, the most straightforward solution — reducing the number of patients needed for a given trial — has been largely overlooked.
In an upcoming series of posts, we will show how the patient recruitment needs for many trials can by dramatically reduced without increasing the chance of Type I and Type II experimental errors. Furthermore, we will demonstrate how smaller trials greatly reduce the time required to bring new treatments to market.
