Advanced data analytics, improved demographic targeting, and patient engagement initiatives should be top-of-mind for sponsors looking to improve clinical trial efficiency in the coming year.
As we enter into the new year, clinical trials continue to struggle with costly delays and inefficiency, particularly when it comes to recruitment. In fact, 90% of clinical trials struggle to hit enrollment targets, and 27% of U.S. trial sites fail to enroll a single qualified patient. Such delays can have devastating effects — in fact, each additional day can cost sponsors up to $37,000 in out-of-pocket expenses.
As such, measures must be taken to improve the efficiency and efficacy of recruitment campaigns. Fortunately, new advances in data analytics, digital ad targeting, and performance tracking have opened the door for improved patient screening, enrollment, and retention. Here are a few areas we expect will have a big impact in 2017 and beyond.
Digital Demographic Targeting
Big data and advanced analytics technologies have enabled clinical trial recruiters to target potential participants more efficiently than ever before. In a recent article in Applied Clinical Trials Online, Antidote’s Tom Krohn noted that new algorithmic targeting technology is boosting the qualification rate of recruited patients by way of simplified educational resources and segmented patient engagement outreach campaigns.
“You can maximize enrollment and minimize screen failures by doing good matching, prescreening, and follow-up. I see lots of various types of digital companies that do advertisements that lead patients to sites which results in a lot of of false-positive screen failures...The quality from our perspective is pre-screening quality: pre-screen patients as much as possible through algorithms.”
For example, the Michael J. Fox Foundation has seen great success from targeted Facebook ad campaigns. Using the social media network’s advanced demographic targeting tools, the foundation was able to reduce the enrollment cost from $800 to $35 per patient. This drop in cost can be attributed to effective targeting, which in this instance was centered around Ashkenazi Jews, who are at a higher risk of developing Parkinson’s.
These enhanced targeting capabilities aren’t limited to social media, either — with search ad platforms like Google Adwords, recruiters can utilize keyword targeting to identify those prospective patients who have reached the transactional stage of their path to treatment and are therefore more likely to convert.
Performance Tracking and Predictive Modeling
Internal trial data analytics have also had a considerable impact on performance monitoring, yielding improvements in recruitment and retention across the board. For instance, analytical benchmarking solution Clinical SCORE identified an association between eClinical software issues and clinical trials that don’t meet enrollment targets. Because improper training leads to software issues down the line, the resultant attitude of disengagement can harm relationships between trial operators and participants. Therefore, trial operators will want to ensure that all site coordinators are well-versed in the relevant eClinical software in order to maximize trial enrollment outcomes.
Similarly, Pfizer leveraged aggregate data to create models which predict study quality risk and its impact on GCP. For example, one of its models compares the protection of subject well-being against key clinical trial quality metrics — if a correlation is found, it can serve as an effective early warning system for quality control. Pfizer has also built models that analyze deviation from protocol and protocol amendments to find relationships between protocol adherence and study quality and improve quality risk planning.
Patient Centricity On the Rise
In order to improve recruitment and retention, many sponsors are attempting to gain a better understanding of trial participant preferences and tendencies, as well as including them in the trial design process. Recruiters have launched initiatives to quantify the participant’s perspective in order to reduce patient burden and optimize trial design to improve outcomes and cost efficiency.
For example, many sponsors are engaging with patients directly via panels in order to gain a better understanding of the target participant demographic, establish inclusion and exclusion criteria, and “clinically meaningful” outcomes for patients. This kind of insight is vital, as the patient perspective on what is a clinically meaningful outcome for a trial can differ from that of a physician, which in turn can have a direct impact on a trial’s ability to recruit qualified participants.
For example, in a comparative assessment on clinical outcomes for an anticoagulants in atrial fibrillation trial, patients saw avoiding “disabling stroke” as a clinically meaningful outcome, whereas the physicians responded that avoiding “death” was the clinically meaningful outcome. Clearly, there’s a disconnect between participant and physician expectations — if the industry hopes to improve recruitment, enrollment, and retention, patients should be treated as “colleagues” throughout the design and approval process.
What’s clear is that in 2017, patients will become more empowered than ever before. In order to improve trial enrollment and efficiency, sponsors will need to make embracing technological innovation and patient centricity a top priority — or risk falling behind the curve.