In academic publishing, peer review systems must strike a delicate balance between efficiency and integrity. One of the most overlooked—but essential—features is conflict of interest detection.
"Can you add conflict of interest filtering to our API integration?" This request came from publishers using our Referee Finder tool, and it seemed straightforward. After all, our conflict detection already worked effectively in our user interface, identifying co-authorship and co-affiliation patterns across our database of over 177+ million articles.
However, this "simple" addition became a lesson in understanding the hidden complexity of peer review technology and the importance of architectural planning in academic publishing systems.
Our Referee Finder was designed with user interface optimization in mind. The workflow was logical and efficient: generate large candidate pools from our database, apply initial filters to narrow down to approximately 50 candidates, present these candidates through our dashboard, and calculate conflict of interest information only for the displayed reviewers.
This approach made perfect sense for manual peer review processes. We optimized computational resources by calculating conflicts only for candidates that users would actually evaluate, reducing processing time and system load while maintaining accuracy.
When publishers began integrating our system through API endpoints, we discovered a significant limitation. Our API returned candidate lists without conflict information, creating a fundamental problem for editorial teams using automated workflows. They were selecting reviewers with undisclosed conflicts of interest because the critical conflict data was only available through our standard interface.
This issue directly impacted the core value of our conflict detection capabilities and highlighted how systems designed for one use case can struggle when applied to different workflows.
Our engineering team initially implemented what we now recognize as a technical workaround. We took the standard filtered candidate list of 50 reviewers, calculated conflict information for these candidates, removed those with identified conflicts, and backfilled from the larger candidate pool to maintain list size.
While this solution addressed the immediate need, it created several problems. The approach was inefficient because we were processing conflicts for candidates that might be filtered out. It also created inconsistent experiences between our UI and API, with different conflict handling methods. Most importantly, it established code paths that were difficult to maintain and extend, creating what developers call technical debt.
Rather than attempting a complete system rewrite, we implemented changes through careful phases. We analyzed our existing system to understand how conflict detection integrated with other Referee Finder components, recognizing that conflicts needed to be calculated earlier in the candidate evaluation process rather than just at the display layer.
Each phase was implemented, tested, and deployed independently, allowing us to maintain system stability while making fundamental architectural improvements. This approach proved much more effective than attempting large-scale changes that could disrupt service for active publishers.
The rebuilt system addresses several key requirements that the original architecture couldn't handle effectively. Conflict detection now processes thousands of candidates efficiently, supporting both small and large-scale reviewer selection processes. Both UI and API endpoints use identical conflict detection logic, ensuring consistent results across all integration methods.
Performance improvements reduce processing time while maintaining accuracy in identifying co-authorship and co-affiliation conflicts. The new architecture also supports additional conflict types and integration patterns without requiring fundamental changes, providing flexibility for future development.
This architectural improvement has significantly enhanced our API integration capabilities for academic publishers. Editorial teams can now integrate conflict-aware reviewer selection directly into their editorial management systems, receiving pre-filtered candidate lists with conflicts already identified and handled according to their preferences.
The system provides documented conflict detection processes that support editorial board oversight requirements, helping publishers maintain compliance with journal standards and editorial integrity requirements.
This experience highlighted several principles that apply broadly to academic publishing technology development:
Ultimately, conflict detection systems must be designed for handling growing research networks efficiently.
The transformation of our conflict detection system demonstrates why architectural decisions have long-term implications for academic publishing technology. Systems that appear to work well in limited contexts may reveal significant limitations when applied to broader use cases or scaled to larger operations.
For publishers evaluating peer review solutions, it's important to consider not just current capabilities but also the architectural foundation that will support future requirements. Key considerations include:
At Prophy, our enhanced conflict detection system directly addresses the challenges publishers face in managing peer review processes. The system helps maintain the integrity of peer review processes through robust conflict identification, reduces manual effort while improving accuracy in reviewer selection, and handles both small specialty journals and large-scale publishing operations effectively.
Our API capabilities support diverse editorial workflow requirements and existing system integrations, providing publishers with the flexibility needed for modern academic publishing operations.
The complexity of modern academic publishing requires peer review systems that can adapt to diverse requirements while maintaining reliability and performance. Our experience rebuilding conflict detection architecture illustrates both the challenges and opportunities in developing robust academic publishing technology.
By investing in scalable architectures and comprehensive conflict detection capabilities, publishers can improve editorial efficiency while maintaining the integrity that makes peer review valuable to the academic community. Our database of over 177+ million articles continues to provide the foundation for sophisticated conflict analysis that serves publishers across diverse academic disciplines.
Prophy's Referee Finder provides comprehensive conflict detection and reviewer matching capabilities for academic publishers. Learn more about how our conflict detection technology can enhance your editorial workflows.