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Evidence Mapper

A hands-on learning project built to develop practical digital health PM skills: ETL pipelines, AI-powered relevance scoring, and product design for clinical workflows.

Live: evidence-mapper.com


What it does

Evidence Mapper lets you search, filter and AI-score 63,000+ completed clinical trials against a specific research question — structured as a 6-step guided workflow.

Step 1 — Objective: Define your research question in free text
Step 2 — Filters: Build a PICO search (condition, intervention, phase, date range)
Step 3 — Bronze: All trials matching your filters from ClinicalTrials.gov
Step 4 — Silver: AI removes noise — keeps only trials relevant to your objective
Step 5 — Gold: AI scores each trial 0–10 against your objective
Step 6 — Report: Evidence landscape, intervention clusters, Go/No-Go signal


What I built

  • ETL pipeline over 63,394 completed trials from ClinicalTrials.gov via AACT (January 2026 snapshot), normalized and indexed in PostgreSQL/Supabase
  • MeSH-indexed condition search with autocomplete and server-side paginated RPC to avoid Supabase's URL row limits
  • GPT-4 scoring pipeline that reads every abstract and scores it against a free-text objective
  • 6-step guided UX wizard with persistent state, milestone toasts, live PubMed enrichment, and PDF export

What I learned

The most interesting outcome wasn't technical — it was strategic. Building this led me to map the competitive landscape in clinical evidence AI and identify a structural gap: no existing platform indexes post-approval regulatory sources (EPAR, NICE Technology Appraisals, JCA reports, G-BA decisions). That's a separate case study.


Stack

Layer Technology
Frontend React + TypeScript + Tailwind CSS
Backend Supabase (PostgreSQL)
AI OpenAI GPT-4
Data ClinicalTrials.gov via AACT
Live enrichment PubMed E-utilities API
Hosting Lovable.dev

Key database schema

em.study_index_complete      -- 63,394 studies (base)
em.mesh_condition            -- MeSH condition index
em.intervention              -- intervention index
em.v_ui_study_list_v2        -- main view for UI
em.search_studies_paged()    -- server-side paginated RPC

MIT License

About

Human-in-the-loop LLM pipeline for clinical evidence analysis. Bronze→Silver→Gold workflow on ClinicalTrials.gov (63k studies).

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