Senior VP, Study Start-Up, ICON Clinical Research Services
There is an increasing demand from sponsors for technology and data-driven solutions to improve site selection, study start-up and patient recruitment.
With the explosion of data and improvements in analytical techniques, including emerging technologies that incorporate machine learning and artificial intelligence (AI), sponsors are also demanding greater transparency about how these processes are carried out. This article examines how effective these approaches have been and what the potential opportunities are going forward.
Data Driven Site Selection and Supporting Accelerated Start-up
Growth in available clinical trial investigators has declined over the past several years according to a recent study published by Tufts, making it especially important to have mechanisms in place to identify investigators and their affiliated institutions that have high enrolment potential.
The challenge facing sponsors and CROs is to develop tools that support site-selection and integrate multiple internal and external sources of site and investigator information, along with survey capabilities, to help select the right sites. The data sources involved have a diverse set of information types, ranging from site experience to start-up and enrolment performance, which are all factored into enrolment projections for a given study.
Delays in study start-up has been an industry issue for a long time now and there is a growing demand for outsourced technologies that could streamline these activities. Site identification and selection, based on the increasing availability of data, is a key area of demand. In response, several industry consortia have been formed to aggregate data and make it available for site selection decision making.
As the landscape evolves, it makes sense to adapt a strategy of using leading-edge tools to leverage the best of what is available in the marketplace for optimum results. Available systems can be used to target rate limiters in the start-up process, and their success is measured by a reduction in cycle times, without compromising quality.
With this combined strategy, you are likely to see a decrease in cycle time with increased transparency of the site selection process as well as from the enhanced tracking capabilities and improved visibility these technology and data-driven approaches provide. Furthermore, acceleration in regulatory collection as well as contracts/budgets negotiation, may contribute to overall faster start-up timelines.
Managing and Tracking Documents and Budget Negotiations
In regulatory document submission and contract and budget negotiations, it is advisable to capitalise on a central site activation management system, which should be used both for standardised and central tracking, as well as to share and exchange draft and final documents with key stakeholders globally.
The system can be used to track baseline, planned and actual dates for regulatory and ethics agency submissions/approvals. Furthermore, the system permits approved documents be directly exported from the final start-up package directly into the electronic trial master file (eTMF) for final filing.
Aligning Innovation with Processes
Part of the process of introducing new technology is to ensure that it is integrated into the workflow to improve efficiency, along with ensuring global compliance. The approach taken depends on how disruptive the technology is going to be. In some cases, you can just update existing procedures while others require the introduction of a new process. Regardless it is important to ensure that the process is fully aligned and complementary to the technology.
Site activation tools may manage various types of information from CTMS systems (including, but not limited to, investigator and organisation name, contact details, site number, pre-study visit date, site initiation visit date) and from the eTMF (e.g. document nomenclature).
The Promise of Evolving New Technologies
Improving the use of data analytics and technology would allow for an increased ability to re-use site information on multiple studies and reduce the time between site selection and initiation. In addition, it could support increased engagement and partnering with sites with known patient populations. Another great opportunity is in the promise of AI and machine learning.
With these technologies, we would be able to ask open-ended questions and develop greater insights from sites and patients about what it will take to successfully deliver a study. These insights can then be incorporated into the organisation’s operational strategy, creating the infrastructure for using data analytics and technology to improve site selection and study start-up processes.