Research from the Tufts Center for the Study of Drug Development (CSDD) indicates that starting clinical trials from site identification through to activation, that is the ability of the investigative site to enroll the first subject in the study, is highly inefficient with cycle times that have not budged in over two decades.
The study startup (SSU) phase of a trial has been receiving renewed focus from Pharmaceutical companies under intense pressure to reduce timelines and abate the rising costs of drug development. The globalization of clinical studies has added an additional layer of complexity as differing regulations, limited infrastructures, and cultural differences weigh heavily on study sponsors. These factors, highlight the growing importance of technology solutions in stemming the tide.
The continual reliance on spreadsheets, multiple databases, and unsecured e-mail without audit trail is hardly adequate to manage SSU activities such as country selection, pre-study visits, site selection and activation, regulatory document submissions, contract and budget execution, and enrolling the first subject. Overseeing these activities from dozens or even hundreds of sites involves tracking and storing country-specific documents, ensuring that the most recent versions are being used, and identifying bottlenecks as the startup process unfolds.
From a management perspective, the high degree of complexity results in valuable time being wasted trying to find data buried in documents along with subsequent analyses that are not readily available. In this environment, a multitude of status meetings to understand the results and key metrics driving startup performance is routine. Using these archaic processes to manage activation of a site (which has been estimated at $20,000 to $30,000 per site, followed by the cost of maintaining a site, which is approximated at $1,500 per month) can increase risk and result in knock-on costs, due to poor site selection and under-enrollment. Though these costs are widely known, inefficiencies in startup continue to be largely overlooked, even as attempts are being made to taper the average 6.7 years clinical developmental cycle.
To tackle the multitude of SSU issues in a way that gains traction with clinical trial stakeholders, a collaborative approach has been deemed essential. One of the earliest efforts was undertaken by the Clinical Trial Transformation Initiative (CTTI), a public-private partnership representing academic institutions, biopharmaceutical sponsors, government liaisons, contract research organizations (CROs), and IRBs. As a starting point, some of these entities participated in a retrospective research project, providing data from 2009 for all Phase III studies in SSU mode across all therapeutic areas. The collected data served two purposes: to use a collaborative approach establishing the current level of SSU efficiency in the US; and to create effective approaches for improving it, including the development of standard terms and time points to be used as benchmarks. The main conclusion of the research was that many stakeholders in the clinical trial process fail to routinely collect standardized measures of SSU cycle times, a practice that is common in many other industries. Metrics, though necessary, are not sufficient for driving down SSU costs and eliminating bottlenecks.
According to Tenley Koepnick, Senior Director of Clinical Operations at Transcatheter Heart Valves, the importance of embracing teamwork is key to mitigating issues that hinder SSU and derail timelines. Koepnick explains that teams should focus on:
- Proper planning and preparation
- Better protocol management to avoid amendments
- Smart site selection
- Strategic global considerations
Taken together, the need for metrics and streamlined collaboration underscores why the time is right for cloud-based SSU technology. Purpose-built SSU solutions are the missing component in the eClinical stack of electronic tools that are being widely adopted for more efficient study conduct, poised to follow the growing adoption of other cloud-based solutions such as clinical trial management systems (CTMS), electronic data capture (EDC), the electronic trial master file (eTMF) and eSource. Patients can't wait, nor should they have too because of the unwillingness of an industry to use existing technology to automate a cumbersome and error prone manual process for starting trials. Vital data collected in real-time during startup provides immediate status of how a study is unfolding. By ensuring global access and an independent platform for collaboration, the use of this technology can bring measurable change at the inception of a trial, adoption of which will shorten clinical trial cycle times, reduce study costs, and, most importantly, speed delivery of new therapies to patients.
Article published in CenterWatch, October 2017