StudyTwin helps clinical teams stress-test a trial before it reaches the first patient.
❚ The Problem
Clinical trials often look workable during planning, then struggle once sites and patients are involved. Visit schedules can become too dense, eligibility rules can screen out too many people, consent forms can be hard to understand, and site workflows can become overloaded. These issues usually appear late, when they are expensive, slow, and difficult to fix.
❚ The Solution
StudyTwin turns a trial protocol into an operational digital twin. It analyses the protocol, visit schedule, eligibility criteria, consent content, and site assumptions, then simulates where the study is likely to create friction. The app highlights risks, shows their likely impact, and helps teams improve the study design before launch.
❚ Who It’s For
StudyTwin is for clinical operations teams, sponsors, medical writers, study designers, site teams, and patient experience leads who need to understand whether a trial can work in the real world, not just on paper. It supports the people responsible for protocol design, recruitment planning, site workflow, consent quality, and trial readiness.
❚ Key Benefits / Features
StudyTwin provides protocol stress-testing, patient burden scoring, visit schedule review, recruitment and screen-fail risk signals, consent readability analysis, site workflow risk mapping, and readiness reporting. Teams can view the study through different roles, such as clinical operations, sponsor leadership, medical writing, site coordination, and participant experience, so decisions are clearer and more practical.
❚ Why It’s Different
Most clinical trial tools focus on one part of the process, such as scheduling, feasibility, consent, or site management. StudyTwin brings these views together and tests how they affect each other. It does not simply ask whether the study can be planned. It asks whether the study can actually run, whether patients can follow it, whether sites can deliver it, and where the protocol should be improved before costly problems appear.
