Research Grid Ltd., a UK-based AI innovator in clinical trials, has launched a new global Site Feasibility solution designed to revolutionize how trial sponsors and contract research organizations (CROs) identify and activate trial sites. The tool, announced on August 6, 2025, uses real-world data and automation to streamline feasibility assessments that historically took up to six months—reducing the process to just minutes.
The solution leverages Research Grid’s proprietary global network of over 400 million people across 157 countries and data from more than 96,000 verified communities and thousands of trial sites. These capabilities are intended to support rapid and equitable site selection, faster trial startup, and better recruitment outcomes.
The product is now commercially available, both as a self-service platform and as a fully managed solution, offering flexibility for sponsors conducting single studies or managing global trial portfolios.
What Problem Does Research Grid’s New Site Feasibility Tool Solve?
Clinical trial feasibility remains a chronic weak link in the drug development pipeline. Site selection and activation are often manual, inefficient, and based on outdated or incomplete information. The result is a costly and delay-prone process. According to industry benchmarks cited by Research Grid, up to 80% of clinical trials fail to meet enrollment timelines, and 85% require costly extensions due to poor recruitment. Worse, more than 11% of sites fail to recruit a single patient, and 30% under-enroll overall.
Trial sites themselves report being overwhelmed by feasibility-related tasks, spending an estimated 4,500 hours per year on the process. These inefficiencies not only drain financial and human resources but also undermine efforts to bring treatments to market in a timely and inclusive manner.
Research Grid’s CEO, Dr. Amber Hill, characterized the tool as a foundational step toward eliminating administrative bottlenecks. “We’re showing that with the right AI tech, trials can be safely admin-free,” she said. “That’s not just a workflow improvement. It means life-saving treatments are more likely to succeed in trials and reach the people who need them, faster.”
How Does the Site Feasibility Solution Work?
At the core of Research Grid’s offering is an AI-driven platform that instantly matches protocol-specific criteria with real-world patient availability, site infrastructure, and trial readiness.
Instead of relying solely on historical site performance or paper-based feasibility surveys, the system analyzes verified patient and community data at scale. The network includes over 96,000 medically relevant communities and thousands of trial sites globally that have pre-verified their facilities, specialties, and population access.
The tool also automates feasibility outreach, generates site assessments, and auto-scores responses using protocol-aligned algorithms. Sponsors can compare multiple sites, prioritize equity metrics, and monitor global feasibility progress within a unified digital environment. As such, the solution provides real-time insights that inform both individual trial design and broader site engagement strategies.
Why Is Trial Site Selection Such a Persistent Bottleneck?
Despite the proliferation of trial software platforms and EDC (electronic data capture) systems over the past two decades, the site feasibility process has largely remained manual. Sponsors and CROs often engage sites through email surveys and spreadsheets, requesting estimates on potential patient access, staff capacity, and infrastructure readiness.
This analog process leads to inconsistent site responses, selection bias favoring historically over-utilized sites, and the exclusion of underrepresented regions. The cost implications are significant: recruitment delays are a leading cause of trial budget overruns and failed studies. Moreover, ineffective feasibility planning is often blamed for lack of diversity in clinical trials, with racial, ethnic, and geographic disparities in participant representation persisting across most therapeutic areas.
Research Grid’s automation tool addresses these pain points by providing instant, evidence-based feasibility scores across diverse geographies. The platform is engineered to highlight and enable trial participation in underserved regions that have historically been left out due to poor access to site selection pipelines.
How Will the Industry React to Research Grid’s Disruption?
The launch of Research Grid’s feasibility platform is expected to resonate with both midsize biotech firms and global pharmaceutical players, particularly as the industry faces mounting pressure to reduce trial cycle times and broaden patient access. Over the last five years, major regulators—including the U.S. FDA and the European Medicines Agency—have emphasized the importance of diversity plans and decentralized trial models in protocol design. AI-powered tools like Research Grid’s may be instrumental in meeting these evolving compliance standards.
Market observers suggest that sponsors with high trial throughput or global portfolios stand to benefit most from the platform’s scalable architecture. Some analysts have informally noted that while the feasibility space has been historically overlooked in favor of electronic trial master files and remote monitoring tech, it may represent one of the last “high-friction” areas ripe for disruption.
Given the expanding role of real-world data and automation in pharma operations, the site feasibility category may see increased investment interest and M&A activity in the coming quarters. Early reaction from digital health forums and clinical ops groups has been cautiously optimistic, with several users praising the platform’s interface simplicity and geo-tagged patient match capabilities.
What Does This Mean for Global Patient Access and Equity in Trials?
One of the most promising elements of the Site Feasibility tool is its built-in focus on trial equity. The platform flags geographies and populations that are traditionally underrepresented in clinical studies but may be well suited for specific protocols. For example, a trial sponsor developing a sickle cell disease treatment can now identify high-prevalence regions in Africa or underserved urban areas in the U.S. where patient demand and unmet medical need are both high.
This capability is expected to significantly expand access to investigational therapies for marginalized communities. Furthermore, it aligns with the growing push from public health institutions, advocacy groups, and investors to diversify clinical trial participation.
Research Grid also appears to be responding to recent global initiatives—such as the World Health Organization’s Global Clinical Trials Forum and the FDA’s Project Equity Blueprint—which promote equity-driven trial infrastructure as a measure of scientific and social responsibility.
Can This Innovation Shorten Drug Development Timelines?
While feasibility is only one step in the complex lifecycle of clinical development, it plays an outsized role in determining a trial’s success trajectory. Faster and smarter site activation can lead to quicker first-patient-in milestones, improved adherence to enrollment targets, and earlier database lock—all of which accelerate regulatory submission timelines.
Industry averages currently place the time from protocol finalization to first-patient-in at 6–8 months. With Research Grid’s automation reducing feasibility from weeks to minutes, this window could shrink considerably—particularly in multicenter or global studies where coordination delays are common.
If widely adopted, such tools could compress the average time to market for new therapies, especially in high-need disease areas such as oncology, rare diseases, and infectious diseases. That acceleration may also improve investment returns for biopharma R&D portfolios, which are increasingly scrutinized for both capital efficiency and trial diversity.
Although it remains to be seen how widely and rapidly sponsors adopt this new model, early signs suggest that Research Grid has introduced a high-impact lever for transforming feasibility from a manual bottleneck into a strategic asset.
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