Discover how Ryght's AI Site Twins can revolutionize clinical trial site selection, enabling faster, data-driven decisions for biotech sponsors and CROs.
A promising protocol needs the right sites to move forward. Finding them should not mean months of manual research, disconnected data and repeated feasibility follow-ups.
At BioTechX USA 2026, Ryght’s Director of Business Development, Dylan Wallace, presented how AI Site Twins can help sponsors and CROs move from protocol requirements to more informed site decisions.
Held on September 29–30 at the Hynes Convention Center in Boston, BioTechX USA brought together expertise across pharma, academia and clinical research. The programme explored the role of data, AI, precision medicine and digital transformation in advancing healthcare and life sciences.
For Ryght, the focus was practical: how can better site intelligence help clinical teams identify suitable sites and move studies forward faster?
Clinical trial site selection requires more than a record of previous studies. Teams need to understand how a site’s experience, capabilities and patient access align with the specific demands of their protocol.
Dylan’s presentation centered on Ryght’s AI Site Twins: continuously updated digital models that bring together information about research sites, including their infrastructure, capabilities and trial experience.
Better site intelligence means less time searching and more time moving studies forward. With AI Site Twins, we’re helping teams find the right sites for their protocol and act sooner.
Dylan Wallace, Director of Business Development, Ryght
By connecting these insights, Ryght helps teams assess site suitability with a richer understanding of the factors that could influence study performance.
The goal is straightforward. Give clinical teams a stronger starting point for deciding which sites to prioritize, investigate and contact.
A broad database search can identify sites with relevant experience. The next challenge is deciding which are best suited to a particular study.
Ryght’s Network Navigator analyzes protocol requirements and ranks sites against study-specific criteria. These can include therapeutic experience, required facilities, patient access and competing trials.
The resulting list gives teams a clearer order of priority, with ranking dimensions configured around their protocol. Teams can then explore individual AI Site Twins to investigate potential strengths and bottlenecks before beginning outreach.
For biotech sponsors and CROs, this creates an opportunity to spend less time assembling information and more time evaluating the sites that warrant attention.
Explore AI-powered clinical trial site selection
Identifying promising sites is only part of the process. Teams still need to confirm interest, validate capabilities and collect the information required to make selection decisions.
Ryght’s Feasibility Accelerator connects site intelligence with that workflow. It uses information held in each AI Site Twin to pre-populate feasibility questionnaires, allowing sites to review, confirm and update their answers.
Automated follow-ups and progress tracking help teams manage outreach, while site responses feed back into the corresponding twin. This keeps feasibility information connected to the site intelligence used for future decisions.
The presentation also explored how a shared data foundation could support the stages that follow site identification and feasibility.
Ryght’s study startup model illustrated how earlier access to relevant information could allow some activities to begin sooner and proceed in parallel. The projected timeline was a planning model, rather than a measured customer result.
It highlights the broader opportunity: connecting site intelligence across the startup process can help teams examine where delays occur and where workflows could improve.
Dylan’s presentation brought a concrete clinical research application to BioTechX USA’s wider discussion of AI: helping teams understand their site options and act on them sooner.
Want to see how that approach applies to your study?
Request your free protocol-matched site list and explore which research sites align with your requirements.
For a quick starting point, run a free site search on RyghtSites.com by indication, phase and country.
RyghtSites.com is a free, publicly accessible search engine for clinical research sites. No login. No contract. No catch.
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