Case Studies on Reacher Technology

Identify Protocol-Specific Errors that Matter

Problem: A sponsor needed to find errors that affected whether the efficacy endpoint was collected according to the protocol. This included checking the clinical database over time, the audit trail, the training database, and the delegation of authority and comparing the...

Identify Errors That Matter From The Very First Patient

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...

Instant Error Trend Identification

Problem: While RBQM approaches such as targeted SDV may find errors, they do not recognize when an error is a systematic problem. If you don’t recognize a systematic error, you don’t find the cause, and the error is perpetuated. Government...

Minimize Risk With Conservative Study Management

Problem: For a large oncology trial with extremely complex inclusion/exclusion (I/E) criteria, finding a subject that didn’t meet criteria was very difficult to do manually. There was a high risk of enrolling a subject that did not meet all the...

Save Monitors Time With Fast Error Correction

Problem: Clinical staff may not be experts in data analytics, and often don’t have tools they need to make an assessment. Monitors wanted a tool that showed them exactly where the error occurred — the subject, the visit, the form,...

REACHER Won’t Disrupt Current Workflows

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...

Decentralized and Virtual Trial Monitoring Delivered

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...

Multiple data sources in your trial? No problem

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...