Ryght AI has announced a strategic partnership with Biorasi, a clinical research organisation (CRO) specialising in dermatology, oncology, neurology, and nephrology studies.
The collaboration enhances Biorasi’s service offering to biotech and biopharma sponsors with Ryght’s AI-driven site selection and feasibility platform.
The partnership addresses critical industry challenges that cost sponsors millions annually: inaccurate site selection, prolonged feasibility timelines, unpredictable enrollment forecasting and suboptimal site performance. By integrating Ryght AI’s platform into Biorasi’s operations, sponsors gain access to granular, real-time insights on site performance and recruitment capacity – transforming site selection, feasibility and trial performance from guesswork into data-driven decision making.
“Traditional feasibility models can be limited by static, self-reported data,” said Chris O’Brien, CEO at Biorasi.
“Ryght AI’s platform revolutionises these models. With continuously updated digital twins of clinical sites and AI-powered feasibility automation, Biorasi can now provide sponsors with recruitment forecasts grounded in real-world, site-specific data.”
Ryght AI’s platform addresses these limitations through:
Dynamic AI Digital Twins: Continuously updated profiles of global clinical sites featuring real-time recruitment capacity, historical trial performance, and operational readiness metrics
Automated Feasibility Workflows: Pre-populated feasibility questionnaire webforms with validated data compress traditional feasibility timelines from several months to less than 3 weeks
Agentic AI Copilots: Rapid protocol parsing and automated generation of feasibility questionnaires, IRB packets, and investigator outreach materials
“We’re transforming clinical trial feasibility into reliable and vital study data,” said Simon Arkell, CEO at Ryght AI.
“Biorasi’s focus on pragmatic AI solutions makes them a perfect partner for optimizing clinical site selection.”
Biorasi said its sponsor clients can expect improvements in study startup and execution across multiple categories, including:
Enhanced Accuracy: More precise enrollment forecasting and budget modeling reduce financial risk
Reduced Delays: Faster site startup through intelligent automation and comprehensive site prequalification
Cost Optimization: Decreased risk of mid-trial delays and cost overruns through better upfront planning
Improved Efficiency: Streamlined site engagement reaching only high-fit, high-capacity research partners
Jim Cornall is editor of Deeptech Digest and publisher at Ayr Coastal Media. He is an award-winning writer, editor, photographer, broadcaster, designer and author. Contact Jim here.
