Researchers and clinicians conduct meta-analyses using fragmented tools like spreadsheets, scripts, and manual workflows, which are error-prone and hard to reproduce. The client wanted a single, reliable platform for end-to-end evidence synthesis.
2. Goal of the MVP
Validate whether researchers would adopt a simple, transparent, web-based tool to run publication-ready meta-analyses without complex tooling.
3. My Role & Stack
I worked on MVP development and product execution:
Built core workflows from data upload to reporting
Implemented analysis and visualization flows
Designed usability for non-technical researchers Stack: Next.js, Supabase, statistical libraries, cloud hosting
4. Approach & Key Decisions
Focused only on core meta-analysis workflows
Prioritized transparency and reproducibility over advanced customization
Built guided steps: upload, model selection, analysis, export
Kept UI beginner-friendly while supporting rigorous methods
5. Outcome & Impact
Delivered a complete end-to-end meta-analysis MVP
Reduced dependency on spreadsheets and scripts
Enabled faster analysis with fewer manual errors
Validated strong demand for an integrated evidence synthesis platform