Multiple data sources in your trial? No problem

MANA RBM

Problem: A trial includes more than 10 different data collection tools. How do you monitor the data from so many systems to find errors in how the study is being conducted? Solution: REACHER analyzes the data across all different data sources and finds errors immediately.  No need to spend the resources to build a “data…

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Decentralized and Virtual Trial Monitoring Delivered

MANA RBM

Problem: How do you monitor trials in a remote world, when there are no “sites” for all or some of the data? Solution: REACHER analyzes the data for errors, regardless of where the data were entered, or by whom. REACHER is not dependent on traditional trial models. This groundbreaking approach assures sponsors and CROs that…

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REACHER Won’t Disrupt Current Workflows

MANA RBM

Problem: Disrupting the entire clinical trial process is a big concern for most organizations.  How to implement RBQM without making major changes to current processes is a question that challenges most Sponsors and CROs. Solution: REACHER delivers answers directly to study team management or to team members. No changes in workflow are required to enhance…

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Identify Errors That Matter From The Very First Patient

MANA RBM

Problem: RBQM approaches like Key Risk Indicators and Statistical Outliers require that a large number of subjects are enrolled first. False positive (system signals an error but no error exists) results are frequent.  Solution: REACHER finds the errors from the very first subject and tells the monitor exactly what the error is, and how to…

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