Proof or Placebo
If your supplement can’t survive contact with PubMed, it doesn’t deserve your wallet.
Channel: Proof or Placebo
Tagline: If your supplement can’t survive contact with PubMed, it doesn’t deserve your wallet.
Niche: Consumer-facing supplement evidence intelligence — an automated, opinionated site that grades trending supplements against actual clinical trials, meta-analyses, government fact sheets, and FDA adverse-event reports so normal people can tell the difference between promising compounds, overpriced wishful thinking, and capsules with a body count.
Target audience: Health-conscious adults, gym rats, sleep strugglers, longevity nerds, anxious parents, biohacker-curious professionals, and burned consumers who are tired of affiliate bloggers calling every powder “game-changing.”
Why now: The supplement market is gigantic, consumer trust is soft, and the internet is drowning in hype. Public evidence is now rich enough to automate at scale: PubMed returns 29,836 results for “herbal supplement clinical trial,” publication volume grew from 1,178 in 2010 to 1,809 in 2025, ClinicalTrials.gov shows 3,362 completed studies for just a handful of common supplements (ashwagandha, turmeric, creatine, magnesium), and openFDA exposes 148,459+ food adverse-event reports. Translation: the raw material exists for a brutally useful evidence engine, but almost nobody is packaging it beautifully, honestly, and for free.
Content Example:
Sample headline: Ashwagandha Is Not Magic — But It’s Also Not Total Nonsense
The ashwagandha economy runs on a familiar scam: take a mildly interesting plant, wrap it in “ancient wisdom” plus cortisol panic plus six-pack-adjacent masculinity, then sell the same capsule as a stress fix, testosterone booster, sleep hack, and productivity weapon. The evidence is more interesting — and less flattering — than the label. What the trial record suggests is that ashwagandha may help some people with stress and self-reported anxiety symptoms, but the typical study is small, short, and annoyingly inconsistent in extract type, dose, and outcome measures. In plain English: there is signal here, but the signal keeps showing up dressed as marketing.
That’s where Proof or Placebo earns its keep. Instead of giving readers a fake yes/no answer, the site would show the evidence stack: how many randomized trials exist, how recent they are, whether meta-analyses agree, which outcomes look strongest, what the median study duration was, how often the sponsor had skin in the game, and what safety signals show up in adverse-event databases. The verdict might be: plausible for stress, weak for everything else, not remotely worth premium-brand pricing, and definitely not a substitute for fixing your sleep, alcohol intake, or life. That’s useful. That’s shareable. And most importantly, that’s not supplement-influencer fan fiction.
Data Sources:
- NCBI PubMed E-utilities API — https://eutils.ncbi.nlm.nih.gov/entrez/eutils/ — search and pull abstracts for supplement-specific clinical trials, systematic reviews, and meta-analyses
- ClinicalTrials.gov API v2 — https://clinicaltrials.gov/api/v2/studies — structured study registry data for completed, ongoing, and terminated supplement trials
- openFDA Food Adverse Event API (CAERS-derived) — https://api.fda.gov/food/event.json — adverse event reports tied to foods and supplements
- openFDA Drug Adverse Event API — https://api.fda.gov/drug/event.json — additional safety signal tracking where compounds appear in drug-event reporting
- NCCIH Herbs at a Glance — https://www.nccih.nih.gov/health/herbsataglance — concise government summaries of evidence, side effects, and cautions
- NIH Office of Dietary Supplements Fact Sheets — https://ods.od.nih.gov/factsheets/list-all/ — standardized nutrient and supplement fact sheets for consumer and professional context
- Reddit API / public subreddit feeds — r/Supplements, r/Nootropics, r/Fitness — for demand detection and “what people are hyping now” ingestion
- Google Trends / trend monitoring — trend tracking for rising compounds and seasonal spikes
- Amazon / retail bestseller signal scraping — what consumers are actually buying, useful for prioritizing coverage
Automation Pipeline:
- Schedule:
- Daily GitHub Action to detect trending supplement names from Reddit, retail bestseller pages, and search-trend watchlists
- Weekly evidence refresh for tracked supplements across PubMed, ClinicalTrials.gov, and FDA adverse-event endpoints
- Monthly “state of the stack” rebuild to rerank the best-supported, most-overhyped, and most-concerning products
- Collect:
- Build a canonical ingredient list with aliases (e.g. magnesium glycinate vs magnesium bisglycinate)
- Query PubMed for RCTs, systematic reviews, umbrella reviews, and meta-analyses per ingredient + claimed outcome
- Pull trial metadata from ClinicalTrials.gov: sponsor type, enrollment, status, start/completion dates, outcome text
- Pull adverse-event counts, common reactions, and serious outcome signals from openFDA food/drug APIs
- Ingest NCCIH / ODS summaries for safety and interaction context
- Monitor Reddit and trend inputs to decide which supplements deserve new pages first
- Process:
- Cluster papers and trials by ingredient + claim category (sleep, anxiety, muscle, libido, immunity, cognition, etc.)
- Score evidence quality based on study type, sample size, replication, recency, consistency, and sponsor bias risk
- Separate “evidence for outcome A” from “evidence for outcome B” so one decent sleep signal doesn’t become fraudulent claims about hormones, longevity, and fat loss
- Compute a Hype Gap Score: market attention minus evidence quality
- Compute a Safety Friction Score: adverse-event density, interaction warnings, liver-risk mentions, stimulant burden, etc.
- Use AI to draft verdict pages, weekly “supplement court” roundups, and shareable explainers with source citations
- Generate:
- Ingredient report cards (A–F)
- Claim-by-claim score grids
- Trial-quality waterfalls and evidence pyramids
- Adverse-event reaction heatmaps
- “Worth your money?” badges and “Hype Gap” posters for social sharing
- Stylized editorial illustrations: pill bottles on trial, lab notebooks, courtroom receipts, placebo ghosts, neon verdict stamps
- Publish:
- Static TypeScript site rebuild on GitHub Actions
- Auto-generated supplement pages, claim pages, category hubs, RSS feed, sitemap, and weekly dispatch archive
- Deploy to GitHub Pages or Cloudflare Pages with zero manual publishing after setup
Tech Stack:
- Static site: TypeScript + Astro
- Image generation: D3 / Observable-style SVG charts, server-side canvas for verdict cards, optional AI header art for editorial pieces
- Data collection: Node.js pipelines calling PubMed E-utilities, ClinicalTrials.gov API v2, openFDA APIs, plus light scraping for trend inputs
- CI/CD: GitHub Actions
- Hosting: Cloudflare Pages or GitHub Pages
Monetization Model:
- Channel 1: reader donations — “Help keep the supplement grifters on the witness stand” is a strong public-service pitch
- Channel 2: premium research tier — deeper ingredient dossiers, interaction checkers, category watchlists, monthly evidence briefs for coaches, dietitians, and health journalists
- Channel 3: sponsorship / affiliate, carefully constrained — books, lab testing kits, evidence-focused tools, maybe a “we do not take supplement-brand money” sponsorship rule as a trust moat
- Projected month-1 revenue: $300–$900
- Projected month-6 revenue: $3,000–$8,000 with SEO traction, repeat readers, and a premium subscriber base
Launch Complexity: 4/5 — the data exists and is fetchable, but the hard part is building a sane evidence-scoring system and normalizing messy ingredient aliases
Content Quality Score: 5/5 — this is genuinely useful, directly tied to spending decisions, and solves a painful trust problem for millions of people
Automation Score: 5/5 — trials, papers, adverse events, trend signals, and fact-sheet updates are all machine-ingestable on recurring schedules
Revenue Potential: 5/5 — huge audience, powerful SEO, newsletter potential, premium conversion, and high donation friendliness if the voice stays sharp and trustworthy
Total: 19/20
Why This Will Work: This one has the holy trinity: money, confusion, and recurring data. People are already paying for supplements, already googling whether they work, and already getting terrible answers from SEO swamp monsters. The site’s unfair advantage is that it doesn’t pretend all evidence is equal. It can tell a much more useful story: this ingredient has decent support for X, weak support for Y, obvious hype inflation, and enough safety caveats that you should stop dry-scooping it like a raccoon with a credit card. That voice matters. It gives the project character, and character is what turns a useful site into a habit. Visually, the site can be gorgeous: bold verdict cards, pill-bottle mugshots, evidence ladders, clean red/green/yellow grading, and “court transcript” style article layouts that beg to be screenshotted. SEO-wise, this is a monster: every ingredient, every claim, every comparison query, every “does it work” search, every “side effects” search, every “best evidence-backed supplements” roundup. It also scales cleanly into adjacent products: protein powders, nootropics, energy drinks, adaptogens, and eventually a full “Wellness Lie Detector” network.
Risk & Mitigation:
- Risk: Medical-content liability and overclaiming
Mitigation: Make the site aggressively source-first, avoid treatment advice, show evidence confidence explicitly, and include medical disclaimers everywhere - Risk: Supplement ingredients have alias chaos and dirty taxonomy
Mitigation: Build canonical ingredient mapping with synonym tables and manual overrides for top compounds - Risk: Adverse-event databases are noisy and do not prove causation
Mitigation: Present them as signals, not verdicts; show counts, caveats, and reporting limitations clearly - Risk: Revenue could be corrupted by supplement-brand sponsorship temptation
Mitigation: Make anti-conflict rules part of the brand; readers trust a judge who doesn’t take money from the defendant