Biomarker Discovery Management
The development of a biomarker management tool by Sonrai represents a significant advancement in managing and utilizing diverse biomarker data, enabling drug developers and diagnostic companies to maximize output from their data and increase the efficiency of biomarker discovery.
Sonrai’s biomarker repository is a multifaceted tool that streamlines biomarker management, accelerates discovery and fosters a collaborative and compliant research environment.
Its integration capabilities, adherence to data protection standards, and scalable design make it a valuable asset for users who want to identify promising biomarkers for their research. The repository facilitates the practical aspects of research and contributes to the broader strategic goals of knowledge advancement and innovation in biomarker discovery.
Sonrai’s biomarker repository offers significant holistic and practical value to users. As a centralized knowledge hub, it enhances organization-wide knowledge and research efficiency by acting as a core repository for biomarker data. This cloud-based centralization facilitates collaborative research within teams and with external partners, fostering innovative outcomes and strategic decision-making through easy access to relevant information.
It increases time and resource efficiency by streamlining data search and organization, enabling researchers to concentrate on analysis and discovery rather than wasting time trying to find data saved in multiple locations. The repository is cloud-based and ensures enhanced data accessibility for global teams, supporting remote and distributed research. The tool maintains quality control and standardization in data handling and analysis methods, thereby elevating the overall quality of research.
Usually, differential expression and biomarker discovery are done in isolation, with different outputs generated and saved in different locations. There is currently no consensus on how to bring these two together in an effective and streamlined manner, to determine which biomarker is the most relevant. Sonrai’s biomarker repository allows researchers to see quickly which biomarker comes up most often across disease types, making it easier to select the most promising biomarker for further research
Key Features and Functionality
- User-Specific Libraries: Customizable for each user, allowing them to store and manage their unique biomarker data.
- Searchability: Advanced search features to quickly find specific biomarkers, crucial for teams working on complex projects.
- Knowledge Sharing: Facilitates the exchange of biomarker information within and possibly across different client teams, enhancing collaborative research.
- Efficiency: Allows quick decision-making based on accurate data overview, saving valuable time which would usually be wasted on the wrong biomarker.
- Reproducibility: The streamlined biomarker management tool helps to organize datasets allowing various teams to quickly reproduce their findings, helping to overcome the reproducibility crisis.
Biomarker Management Workflow
1. Find your markers with Sonrai Dash Apps, save and publish them
2. Pull request (PR) your data (Data as Code principle) to keep it clean and tightly controlled
3. Analyze all your markers across your business, projects and data sights to generate meaningful real-time business intelligence with advanced analytical and intuitive controls
Image 1. Volcano Plot App with Save/Publish features and a list of markers.
Image 2. Data PR screen showing spreadsheet and Reject/Approve buttons. This depicts the approval process for merging a new list of biomarkers into the centralized management tool. At Sonrai we treat the approval process for biomarkers the same way as we do for code. This level of rigor ensures traceability and the ability to rollback data when needed.
Image 3. Biomarker list screen with charts to visualize findings. Users can perform analysis on aggregated differential expression experiments from multiple datasets. The tool allows users to understand which features are common across cohorts, indications or therapeutic areas. This provides insights into new predictive biomarkers and mechanisms of action (MoAs) or to validate current hypotheses by providing a consensus across the organization’s data assets.
- Seamless Integration with Existing Systems: The repository is able to integrate with existing databases, research tools, and data analysis platforms, ensuring a smooth workflow.
- Compatibility with Various Data Formats: To handle diverse data types typical in biomarker research, from genetic sequences to protein structures.
- Data Privacy and Security: Compliant with global data protection legislation and best practice to safeguard sensitive information.
- Audit Trails and Reporting: Features for tracking data access and modifications, crucial for investigations, audits and quality control.
- Role-based Action Control: Only authorized users can access the data in the repository and approve actions.
Future Roadmap and Scalability
- Scalability: Designed to handle increasing amounts of data and users, crucial for growing organizations.
- Continuous Feature Updates: Regular updates to include the latest research tools and data management technologies.
- Integration with Emerging Technologies: Potential to integrate AI and machine learning for predictive analysis and advanced data mining.
- Consolidation of in-house and public biomarker data: Ability to compare users’ in-house data to publically available data in order to review findings and improve reproducibility.