Clindata Cloud - Operational View

Key Challenges on Clinical Trials 

Clindata Cloud receives pre-clinical / clinical / Risk Metric data from multiple data sources / sites, and empowers the clinical operations teams, with submission ready data sets, analytics and risk based monitoring alerts.

Step 1: Consolidate & harmonize study data from multiple data sources into a comprehensive study data model

 

Step 2: Validate received data for completeness, accuracy, integrity and consistency and raise alerts and notifications in case of exceptions or risk patterns

 

Step 3: Standardize data to CDISC data standards, to eliminate noise and create submission ready data sets in real time for continious validation of data & analysis

 

Step 4: Generate submission ready analytics in real time based on standardized data 

 

Step 5:  Trend analysis and data pattern recognition to support Risk Based Monitoring in real time.

How does Clindata Cloud work ?

Risk Monitoring

Clindata Cloud Implementation Roadmap

Our structured implementation methodology, Create-Configure-Run (CCR) is based on Agile SDLC. This rapid deployment methodology enables a study to be up and running in 10 days from the date of mapping spec sign off.  

 

1) Sponsor provides key study artifacts such as Protocol, Data Management Plan, Statistical Analysis Plan etc.

 

2) We create a dedicated insulated Clindata Cloud ( Private Cloud)  instance for the new study

 

3) Sponsor SMEs could use our "drag-and-connect" graphic mapping generator to create mapping specifications

 

4) We configure the system to automatically Receive, Convert, Report / Analyze raw clinical data from multiple data providers

 

5) Sponsor tests and signs-off on the system and can run the instance themselves or we can help with our support options