Data Monitoring

Visualise and transform your clinical data with R

Explore the dashboards created by Genpro’s R and SAS programmers to keep track of the accrual and stratification factors in your study. We provide customized dashboards tailored for your needs.

Dashboard Structure

The entire dashboard is divided into two sections: Pre enrollment analysis and Post enrollment analysis.


Pre-Enrollment Analysis

This section of the dashboard focuses on defining the sample size and predicting the enrollments at the initial phase of the study.


  1. Sample Size Calculator: Calculates adjusted sample size for a given dropout rate for each cohort.

  2. Enrollment prediction: Forecasts the time duration for subject enrolment based on enrolment start date, total number of planned sites, sites active per month, sample size and enrolment rate. 

  3. Simulate Data: Simulates scan and visit data based on enrolment duration, total number of planned sites, sites active per month and enrolment rate

Post-Enrollment Analysis

Post-Enrolment Analysis focuses on displaying the actual collected Scan & Visit data for all enrolled subjects and predicting the further Scans & Visit details along with a summary.


  1. Data Preparation: Prepares the actual scan and visit data used for analysis.

  2. Scan info: Provides a summary and analysis across the prepared scan and visit data. 

  3. Cohort Expansion: Simulate enrollments at cohort level for expanded cohorts



Sample size calculation

Sample size estimation is one of the key aspects of every clinical trial protocol and is usually the most important factor determining the time and cost of the study. The dashboard enables users to calculate the adjusted sample size at cohort level as well as stage level considering the dropout rate and predefined sample size. The user can also specify if there is any positive response in any cohort and the cohort size will be expanded accordingly considering the dropout rate.

Enrollment Projection

Patient recruitment is a necessary condition of success for clinical trials. The dashboard models clinical trial enrollment prediction using available information prior to the initiation of the trial. The user can calculate enrollment duration based on enrollment start date, total number of planned sites, number of sites active per month, enrollment rate(p/s/m), number of initial subjects enrolled and number of initial sites active

Data Simulation

The dashboard has the feature to simulate scans and visits based on enrollment duration, enrollment rate, number of sites per month and total sites available. Simulation of visit information helps in estimating the duration of the trial and also helps in estimating the number of visit information that could be gathered in a selected duration of time.

Import, Analyze, and Export data

The dashboard enables users to import visit/scan data into the dashboard, validate imported data and analyze it. The user can get summaries of the subject information that will be available within a selected time frame. The dashboard has information tabulated at subject level, site level and cohort level based on the input grouping level. The tool also enables users to export summaries and results in excel format with color coding applied. Interactive data tables in the dashboard make it easier to monitor study progress and highlight records that need attention with easy filtering and grouping options.

Cohort expansion

When one or more positive responses are identified within a cohort, cohort expansion can occur. In such cases, specific tabs on the dashboard simulate additional subject information of the expanded cohorts based on the number of responses identified. This could aid in future planning and determining the additional trial duration. The simulations can be based on the expected number of monthly enrollments or on the enrolment rate, number of responses, and number of available sites.

Data Validation and Cleaning

The process of testing the validity of data in accordance with the specifications is a critical process. Data validation checks in the dashboard ensures collection, integration and availability of data at appropriate quality and cost. This feature could be further extended to provide easy identification and resolution of data discrepancies in the CDM process. Users can define rules to cross check data and automatically identify discrepancies, thereby making data cleaning simple.

Data Visualization

Critical analysis of clinical data can be made simple with bar charts, line graphs and more. Interactive visualization methods can help visualize and analyze clinical data from screening and enrollment to tracking adverse events. Dashboard can generate study enrollment reports, data validation reports and interactive plots that allow you to visualize data, from exploring cohorts down to individual patients.