A recent industry survey by Inato revealed a striking disconnect: while 72% of research sites believe sponsors trust their feasibility data, only 13% of sponsors and CROs actually report such trust. At this year's SCOPE conference in Barcelona, Marcy Kravet, VP of Strategic Operations at Inato, moderated the panel "Increasing Trust & Transparency to Accelerate Site Selection and Startup" with Rosia Shah, Medical Lead at VCTC, and Tom Westgate, Director of Feasibility Strategy at PPD. The session explored strategies for fostering trust and transparency among sponsors, CROs, and clinical trial sites, directly tackling the disconnect that hinders effective collaboration in the industry.
Here are key insights from the discussion to address challenges in today's clinical trial landscape:
When sites apply for trials, they provide patient recruitment estimates. However, these projections are often met with skepticism from sponsors. Inato’s survey highlights this disconnect: while 77% of sites claim to offer achievable enrollment projections, a mere 12% of sponsors express strong confidence in these figures. This cycle of mistrust leads to friction, delays, and budget overruns. Acknowledging this gap allows stakeholders to develop proactive measures that foster credibility and transparency in site selection. Shah highlighted that although her site is only two years old, "the core team actually has between 15 and 20 years of experience in clinical research each." This expertise enables them to "draw on primary care networks, research bodies, and most importantly patient groups” to come up with numbers and strategies that inspire trust for the sponsor. However, the challenge for smaller startups lies in gaining recognition from sponsors. Even with their experience and reliable data, these sites often struggle to receive the same attention as well-established ones.
CROs play a crucial role in building trust between sites and sponsors. Westgate noted that CROs recognize the need to expand the number of sites they recommend to sponsors. However, they also face a challenge since sponsors "set a very high bar in terms of the evidence they require for us to recommend a site to them." CROs can bridge this gap by gathering "good quality feasibility survey data from sites…to help build up a more complete picture for a site” and add valuable context for a sponsor. By gathering this contextual information and using external data sources, CROs can improve the accuracy and quality of site data. This comprehensive approach enables sponsors to gain a more reliable understanding of each site's capabilities, ultimately streamlining feasibility processes.
Site networks can be instrumental in elevating smaller, community-based sites by providing resources, support, and connections to potential sponsors. These networks not only offer guidance but can also vouch for their members' quality and capacity, building confidence among sponsors and expanding trial opportunities for sites that might otherwise be overlooked. Westgate confirmed this, saying, "This process helps us identify sites that maybe wouldn't have been at the top of our list... I think there's a lot of value there."
For research-naive sites, support from sponsors and CROs is critical. Simplifying feasibility forms, offering training, and providing mentorship can help expand the pool of capable sites and foster diversity. Investing in these sites doesn't just promote inclusivity; it also strengthens the overall ecosystem by allowing a wider variety of sites to participate. Sponsors and CROs play a crucial role in helping these sites grow and develop over time. Shah emphasized the importance of human interaction and personal investment in sites. When someone takes the time to reach out and ask, "Can you clarify this?" or "Can you explain that?", it creates an additional touchpoint that allows sites to be truly heard and seen. This human connection ensures that sites can fully express their qualitative data and experiences, fostering a deeper understanding and more effective collaboration.
For sites aiming to build trust, transparency is essential. Kravet explained that Inato's research found “sponsors don't necessarily have full trust in site-reported data…but if they had a trusted third party or more metrics, that might sway their opinion of a site." Panelists encouraged sites to use third-party verification and openly share case studies and evidence of past performance. By reflecting on previous trials and refining their projections over time, sites can bolster their credibility, making themselves more attractive partners for sponsors. Shah's site makes a point at the end of every study to identify where they flourished, where they failed, and provide some context into what they're saying to sponsors that ran this trial.
Achieving diversity in clinical trials is complex and requires more than data analysis alone. It also calls for qualitative insights and community engagement. To break down barriers to participation, sites need to understand the specific challenges faced by diverse groups and adapt their recruitment strategies accordingly. Shah's team ensures they consider patients in all aspects of the trial. For example, Shah mentioned, "If we're looking at achieving more enrollment in women, we're looking at all of the barriers that women are facing... trying to use all of those qualitative approaches" and look beyond just the quantitative data.
While AI offers the potential to streamline and improve the process, there are concerns that current models perpetuate existing biases. As Marcy Kravet, Vice President of Strategic Operations at Inato, pointed out, "[AI] models for site selection are biased towards experienced sites because they are trained on data that favors those sites." This creates a significant challenge for lesser-known sites. Despite having skilled personnel and a strong commitment to research, these sites often struggle to get noticed by sponsors and CROs. On the other hand, Westgate offered a potential solution: AI could be used to identify promising sites that may not appear at the top of traditional data-driven rankings. He explained that AI could help to "bridge the knowledge gap" by identifying sites that "share attributes with high-performing sites, even if the new sites have less experience." For instance, AI could analyze various factors beyond just past trial experience, such as staff expertise, patient demographics, and community engagement strategies.
The potential for AI to improve clinical trial site selection is vast. However, it's crucial to address the inherent biases in current models. By incorporating a wider range of data points and focusing on factors beyond just past trial experience, AI can help to create a more equitable and efficient site selection process. This will ultimately benefit sponsors, CROs, and, most importantly, patients by accelerating the development of new and innovative treatments.
In Summary
The panel concluded with a unified message: building trust and transparency in clinical trials is a collaborative effort. Effective clinical trials require open communication, a willingness to share information, and a commitment to supporting sites of all experience levels. By working together, we can create a clinical trial landscape that is not only more efficient but also more inclusive and successful.
At Inato, we are dedicated to empowering diverse sites and fostering trust at every stage of the clinical trial process to build a more inclusive and effective research landscape.