Custom Clinical Data Management (CDM) System

• Ingesting trial data from diverse sources (EDC, lab and imaging providers, etc.).
• Data anonymization.
• Automatic inspection of incoming data for invalid, missing, or out-of-range values and discrepancies across different sources.
• The option to manually reconcile issues with incoming data (resolving import issues flagged by automated algorithm).
• Automatic standardization of incoming data (e.g., unifying units of measurement, date formats).
• Automated data coding for adverse event terms and medication names using common dictionaries (e.g., MedDRA, WHODrug).
• Automatic loading of processed data into a clinical data repository (e.g., data warehouse).

• A library of pre-configured data check rules.
• No-code builder for custom data check rules.
• ML/AI-powered detection of errors, inconsistencies, and anomalies in patient records, such as:

• Errors and discrepancies (wrong dosage, concomitant medication inconsistency across hospital visits, etc.).
• Abnormal changes in patient condition (e.g., sudden shifts in lab results between visits).
• Patient profiles with data distributions deviating from the overall cohort.
• Inconsistencies across listings (e.g., across adverse events, medical history, and concomitant medication datasets).

• Unified data manager workplace with access to listings, patient profiles, source patient data, exception reports, and query tracker.
• Collaborative clinical data reviewing and commenting.
• Automated change tracker flagging new or modified data for review.
• Automated approval workflows forwarding data for review based on user roles.
• Customizable exception reports highlighting active issues, queries, and changes made since the last review.
• Data locking upon review completion.

• Creating EDC queries and assigning them to specific individuals or user roles for resolution.
• Sending queries to external partners (e.g., to labs via email) directly from the CDM system.
• Automated query generation, prioritization (e.g., for long outstanding issues), and closure.
• Query tracking by priority, patient, assignee, due date, site, data domain, etc.
• Automated query approval, escalation, and resolution workflow.

• Patient profiles with all aggregated observation data for each patient (eCRF and eCOA data, wearables output, lab results, X-rays, etc.).
• Dashboards with visualized patient condition and treatment data.
• Access to patient records stored in the EDC or any other integrated source system directly from the patient tracker.
• Tracking data cleaning progress and data readiness status.

• Drag-and-drop expression builder for creating and editing listings and other curated datasets.
• Pre-built listing templates and the ability to reuse custom listings as templates.
• Pre-built functions for calculating derived values (e.g., complication risk scores) and the ability to create and save custom functions.

• Real-time tracking of data processing progress and readiness status for individual patients, patient groups, countries, and sites.
• Creation of scheduled and ad-hoc reports (e.g., data quality reports, coding status reports).
• A library of report templates.

• Exporting clean data packages in a predefined format, either on-demand or on an automated schedule.
• Exporting data in bulk.
• Support for different formats (CSV, PDF etc.).
• Saving data as SAS/SPSS datasets.
• Data exchange according to HL7, FHIR, DICOM standards; adherence to CDISC data interchange standards.

• Configuring key risk indicators (KRIs) and quality tolerance limits (QTLs) for site performance and trial quality.

• Dashboards for monitoring KRIs, QTLs, and associated site, country, and study-level risks.
• AI-powered risk analysis to identify potential site performance, compliance, or data quality issues.

• Role-based access controls (user authentication, access rights, action permissions, automatic logoff, etc.).
• Granular data access (e.g., for individual reports, specific fields).
• Multi-factor authentication (MFA).
• End-to-end data encryption at rest and in transit.
• Audit logs for all user and system actions, detailing changes made, the responsible party, and timestamps.
• Compliance with FDA 21 CFR Part 11, ICH E6(R2) GCP requirements, HIPAA, HITECH, GDPR, ISO 14155:2020, and other applicable regulations.

Main capabilities:

• Data ingestion from EDC.
• Aggregated patient data view.
• Query tracking.
• Change tracking.
• Automated workflow for role-based review task assignment.

From $120,000

In addition to the capabilities of the basic system:

• Trial data management automation.
• Query management automation.
• Automated data export to the clinical data repository/DWH and statistical computing environment.

From $300,000

In addition to the capabilities of the standard system:

• Data ingestion directly from partners’ systems (EHRs, LIMS, and RIS).

From $900,000