Planning for and conducting a clinical trial presents many challenges associated with study design, patient safety and outcome determination. With growing pressure from stakeholders to speed the process of drug development, and increasing demand from regulators to submit compelling data, it’s easy for clinical trial coordinators to lose sight of one of the most important aspects of the process: study startup.
Study startup – including site selection and site activation – has long been a costly and inefficient phase of the clinical trials process. Delays associated with integral steps in the initial stages of study startup – including contracts review and Institutional Review Boards (IRB) approvals – have extended the average activation time for sites to 3.2 months . Considering that a Phase III clinical trial could take up to 9 months to complete enrollment – nearly three times as long as the time spent on site selection – it’s no wonder these initial decisions have such a broad impact on the success or failure of the trial.
In particular, traditional site selection strategies have produced mixed results for the industry. The most recent statistics suggest that approximately half of all research sites in a multicenter trial fail to meet their enrollment targets, with 11 percent of them recruiting not a single participant .
Though 89 percent of studies eventually meet their enrollment goals, this delay in patient recruitment often leads to a significant increase in the time and money required to complete a clinical trial. In some cases, sponsor companies are required to nearly double their initial project timelines, and could end up absorbing a 20 percent increase – up to $2.25 million – in trial costs .
While some problems with patient recruitment and retention are the result of factors outside the control of clinical investigators – such as socioeconomic factors and regulatory-mandated protocol amendments – many of the problems associated with site performance can be solved by employing smart site selection practices.
Traditionally, site selection has been performed using a manual process that relies heavily on frequently-outdated data charting a site’s past performance in terms of participant recruitment. For some, initial site identification can even be reliant upon simplistic methods including word-of-mouth and internet searches.
What’s more, 70 percent of sites in any given multi-center trial have been used by the sponsor company before, with only 30 percent of the facilities newly recruited. While seasoned study teams may have developed strong relationships with specific research sites over the years, these sites may not always be the best choice for the disease being studied.
In an age of big data and fierce competition for top-performing research centers, some in the industry are urging study teams to take a data-driven approach to site selection. Instead of simply relying on past performance to predict site suitability, trial organizers should consider multiple variables – including patient population, treatment and procedural requirements, and outcomes measures – when performing site selection.
Perhaps the first step towards optimal site selection is managing expectations when it comes to site performance. Clinical trials management staff tend to assume that all study sites will recruit the optimal number of participants at the optimal time.
No matter what metrics are used to evaluate a site’s eligibility for the clinical trial, there will most likely be at least one site that fails to meet its recruitment target. By changing a sponsor’s expectations before sites are chosen, the potential for under-enrolling sites to derail the study is mitigated.
Investigators can also take advantage of dedicated study startup tools to apply a data-driven approach to clinical trial planning, and streamline the process of site selection. San Francisco-based clinical trials software developer, goBalto, have introduced a product known as goBalto Select, to help clinical trials professionals navigate the initial stages of clinical trials.
Select provides a purpose-built tool to combine and compare multiple performance variables, to identify the right sites with the best patient population for a given study protocol. By using a multi-faceted approach, Select helps reduce the number of under-enrolling or non-enrolling sites in any given study.
Without embracing the new data-driven approach to site selection, study sponsors are destined to face the same challenges associated with patient recruitment, study timelines and trial costs. Taking a proactive approach toward study startup and site selection could help improve patient recruitment and keep clinical trials expenses on-budget.
To learn more about optimizing site selection and goBalto Select, register for the upcoming webinar featuring clinical trials site management expert speaker, Ken Getz.
 KA Getz. Uncovering the drivers of R&D costs. Proprietary presentation 2015, citing data from the Tufts Center for the Study of Drug Development.
 Kaitlin, K.I., Editor. “89% of trials meet enrollment, but timelines slip, half of sites under-enroll.” Tufts Center for the Study of Drug Development Impact Report. 2013 Jan/Feb;15(1)
 “Unclogging the Patient Recruitment Bottleneck”, PharmaVoice, Feb. 2011