Biostatistical Programming Studio for Regulatory Compliance
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current biostatistical programming systems, such as SAS, lack effective file and data management, traceability, and record-keeping capabilities required for regulatory compliance in the life sciences industry, particularly for biomedical data analysis, leading to inefficiencies and complexities in workflow management among diverse professionals with different specialties and priorities.
Innovation Solution
A biostatistical programming studio (BPS) is developed as a desktop application running on WINDOWS or LINUX, providing a graphical user interface for file and data management, automated processes, and enhanced communication among professionals, with features like version control, audit trails, and permission management to ensure compliance with 21 CFR Part 11/EU Annex 11 regulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If SAS OA is used for biostatistical programming, then computing and reporting results are provided, but file and data management, traceability, and record-keeping capabilities required for regulatory compliance are insufficient
Solution Approach 1:
The patent combines multiple separate functions (file management, data management, audit trail tracking, version control, and regulatory compliance monitoring) into a single integrated workflow management system. This integration ensures that all components work together seamlessly to maintain regulatory compliance while reducing the complexity of managing separate systems.
Solution Approach 2:
The workflow management system acts as an intermediary layer between the SAS programming environment and regulatory requirements. It provides the necessary traceability, audit trails, and record-keeping capabilities without requiring changes to the core SAS programming functionality, thus bridging the gap between computational needs and compliance requirements.
2Ease of operation
If web-based SAS server is used for drug development, then remote access is enabled, but adoption for managing workflows involving biostatistical analysis is limited due to validation and reporting requirements
Solution Approach 1:
The system segments the workflow management functionality from the core SAS computing environment. By separating the workflow management, audit trail, and compliance monitoring functions into a distinct layer, the system can provide remote access capabilities through web interfaces while maintaining robust validation and reporting capabilities through the segmented workflow management component.
3Adaptability or versatility
If multiple professionals with different specialties collaborate on biostatistical analysis workflow, then comprehensive analysis is achieved, but organization, cooperation, and coordination become complex and highly interactive
Solution Approach 1:
The workflow management system is designed as a universal platform that can accommodate multiple specialties (statisticians, programmers, data managers, regulatory specialists) with different needs and priorities. It provides unified interfaces and standardized processes that work across all roles, reducing the complexity of coordination while maintaining the ability to handle diverse analytical requirements.
Solution Approach 2:
The system implements feedback mechanisms including automated notifications, status tracking, and audit trails that keep all participants informed about workflow progress and changes. This continuous feedback loop improves coordination among multiple professionals by providing real-time visibility into the state of the analysis workflow without requiring complex manual communication protocols.
4Adaptability or versatility
If manual processes are used for file and data management in biostatistical analysis, then flexibility is maintained, but errors and inefficiencies increase
Solution Approach 1:
The system provides dynamic workflow management where processes can be automatically executed according to predefined rules and conditions, yet remain flexible enough to accommodate changes in requirements. Automated file and data management operations maintain consistency and reduce errors, while the system's configurable nature allows adaptation to different analysis scenarios and regulatory requirements.
Data Source
AI summary
A method and system for managing a workflow for producing a biostatistical analysis (BA) of biomedical data. The data originates from a milestone (or snapshot) of a clinical study performed by, or on behalf of a life science company that performs the BA. The data may be from a blinded or un-blinded clinical study. SAS programs are used for the BA. An audit trail is produced to track changes to any of the data or programs used during the course of the workflow. The programs and data used to produce reported results from the BA are stored in electronic format for sending to a regulatory agency.