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