The Iqvia Institute released a report last month titled The Changing Landscape of Research and Development Innovation1. The report is a fascinating insight into the world of clinical research and provides evidence to support what many in the industry already know: there are still many challenges facing the successful translation of new therapy discovery into approved therapies.

A summary of Recruitment Challenges

It takes an average of 12.5 years for a drug to be approved for use, an increase of 6 months on the 2017 data1 and an increase of 26% since 2010. Instead of speeding up clinical research, it seems that despite all efforts (which have been considerable), we are slowing it down.

Successful and timely recruitment of patients is one of the most significant contributing factor in trials not meeting their timelines.  Despite the use of companies that specialise in trial recruitment, expensive and intricate marketing campaigns and better site selection, this factor tops the list of “biggest hurdle” in timely trial completion.

With the increased use of social media and information technology, patients have more information available to them than ever. An internet search will throw up hundreds of articles extolling the benefits of clinical research. Within a few minutes, anyone proficient in the use of a search engine can locate all clinical trials for a given disease available at practically any location in the world. So why is recruitment still a momentous barrier for clinical trials?

The number of clinical trials conducted under an IND (meaning that the trial is being used to support registration of the therapy under study) has increased 61% over the past five years. This may be one of the most significant contributors to the constant struggle for patients. More trials are competing for the same patient populations.

But is there really?

As an example, the ClinTrial Refer – Oncology WA App lists nearly all oncology studies currently open in Western Australia. It encompasses all clinical trial sites and all investigators. If the above statement is true – that more trials competing for the same patient populations – one would expect multiple trials listed for the same patient populations. In one sense, yes, there are multiple trials for Liver Cancer or Melanoma. However, further investigation reveals that the sub-populations that each trial targets very rarely overlaps.

Is this part of the problem? Are our trials becoming too specific? And if so, are the patient numbers required to provide a statistically significant result accurate?

What is going to Change?

The Iqvia Institute report offered what it thinks are the leading trends currently influencing clinical development of new therapies.  The report cited regulatory changes and changes in scientific advances as the two most prevalent factors driving change. These two factors will, for a multitude of reasons outlined in the report, enable investigators to reduce the numbers of patients needed to provide statistically significant results.

While the above is interesting, of note in the top eight trends driving change were direct-to-patient recruitment and pools of pre-screened patients. It seems that the industry is no longer relying on doctor referrals to find patients and finding ways to deliver trials directly to patients.

Experience at our site reflects this. 22.2% of clinical trial participants recruited at our site in the last 12 months have come from self-referral. This figure includes two referrals from outside physicians who documented in their referral letter that the patient requested to be referred for a clinical trial. Not only are we successful in informing patients of clinical trials, patients are actively engaging with the trials.

What does this mean for Patients?

While the above statistic is positive, there is another statistic that is not so positive. The number of patients refusing clinical trial involvement has increased at our site. Our conversion rate (the number of patients enrolled in a clinical trial/ the number of patients approached) is generally in the 80-99% range.  A trial opened this year had a conversion rate of 6.67%. This is a great deal lot of effort for a site to put in to get such a low number of patients.

In the above example, the reason for refusal was related to study design: the study had too many visits. Patients are not worried about safety or being a guinea pig. It was that, for them, the cost (their time) outweighed the perceived benefit.

Lessons Learnt

For a patient to consider enrolment into a trial, the benefits offered by the trial need to outweigh the effort and risk undertaken by the patient. Whether the benefits are tangible or intangible doesn’t matter – the patient needs to believe he or she will benefit from participation. Therefore it is important that people designing trials understand what patients want and how patients interact with the healthcare system.

Patient centricity and patient involvement in clinical trials is a popular topic at present. However, personal experience would dictate that we are still giving patients what we think they want not what they say they want. For this reason, I have compiled the following checklist for people designing clinical trials:

  • Talk to a patient and ask this question before you do anything else: “Is <<insert the problem we are trying to solve here>> actually a big problem for you”?
    • Real life examples: Do patient want to live longer if their quality of life is poor? Are frequent hospital visits a burden or do they provide social interaction for an isolated patient group?
  • Ask a patient what challenges do they see with the study?
    • Real life example: A patient pointed out that he would be unable to dispense his medication due to his disease affecting his dexterity. When I quizzed other patients on the trial, most admitted to having the same problem. It was something that we completely overlooked during trial design.
  • Have a patient read the information sheet form and provide feedback. The information sheet is supposed to be for the benefit of the patient after all.
  • Build up a picture of your ideal patient and what their life looks like outside of the trial. Understand how the demographics of the patient population translate into real life. To use marketing terminology, understand your target market.
    • Real life example: Patients in their 30-40s are likely to work and have small children. Patients in their 80s may not drive. Subjects under the age of 25 are generally not happy when told to fast for 8hrs, especially if there is no food available immediately afterwards.
  • Run through the patient visit in real time and understand the logistical challenges (and I mean actual run through the visit and not just in your office/head). Would you put your family member through it?
    • Real life example: Patient to fast for 6 hours, drive to the hospital, find parking, walk the equivalent of two blocks through the hospital to the clinic and then complete 20 pages of questionnaires because the protocol says it must be done before the blood test.
    • Patient complete 3 hours of cognitive or muscle strength testing which fails QC (because both the examiner and examinee were physically/mentally exhausted) so he had to do it again. And no, it couldn’t split these up over two days – it’s against protocol.
  • Make use of technology to reduce the burden of the trial.
    • Does the patient have to attend the clinic for that procedure? Can the doctor video call/telephone/email the patient? Can the procedure be completed by a remote nursing visit? Can the patient record whatever it is remotely?
    • Can the patient have access to a video tutorial on a complicated trial process so that they can watch it whenever they need to?
    • Embrace the use of eConsent


Despite considerable effort by the healthcare industry to speed up the drug approval process, it is still taking an average of 12.5 years. Patient recruitment remains one of the main challenges facing timely completion of clinical trials. Changes in healthcare practice and emerging technology are affecting how trials are conducted, reducing the number of patient hours required and marketing directly to patients.  Stringent inclusion/exclusion criteria and poor trial design are two facets contributing to patient recruitment issues. Patient involvement in trial design may help overcome these issues.


  1. Iqvia Institute for Human Data Science (2019) The Changing Landscape of Research and Development Innovation: Drivers of Change, and Evolution of Clinical Trial Productivity https://www.iqvia.com/institute/reports/the-changing-landscape-of-research-and-development Accessed 14 May 2019
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