Life Science SMEs drive our custom application development services, supported by leading-edge technologists and software development experts seasoned in delivering solutions and services that resonate with our sponsors. Our technical teams support solutions development and services in the following areas:
- Next generation enterprise platform
- Ability to integrate and leverage data from multiple sources
- Anonymization of data for sharing it internally or externally in real time
- Leveraging new technologies to support artifact generation from protocol to CSR
- Automated process workflows to facilitate Governance, Artifact Generation, Review / Approval / Sign-off
- Availability of Structured Governance Framework to track metadata at multiple hierarchical levels
- Impact Analysis/Traceability Tool (across all levels)
Looking to enhance your organization’s impact?
Our technology-empowered experts are available to assist you in the following areas:
- Study, Doc, Repository, Strategy Application, and tracking of strategies applied
- Parameter-driven Risk Analysis and Data Utility per EMA guidance. Determine by data/variable or determine for entire study/project.
- Repository and “Pre-De-ID Analysis” tools provide methods/strategies to the user to leverage with confidence speeding setup and delivery.
See datasets before/after and strategies applied immediately to confirm which provide the best results for a specific project. “Sync scroll” summary statistics and histograms are available to make it easier for reviewers/analysts to evaluate the effectiveness of applied de-identification strategies.
View docs before/after with “Redaction Proposal”-like display. De-identified values are highlighted and easily found for review by either the navi panel or via a drop-down menu directly over the doc. Annotations show how the value will appear in accordance with EMA Policy 0070 in the final de-identified doc.
Get results before/after with interactive visualizations to identify data risks over/under threshold(no comma) and alternate displays to view risk separately by quasi-identifiers/variable.
- From basic “search-and-replace/redact” to ML and regular expressions to leveraging of de-identified datasets to queries and patient-specific/narrative strategies.