This product was not featured by Product Hunt yet.
It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).

Product Thumbnail

ClinicalTrial OS

Open source AI operating system for clinical trials

Open Source
Artificial Intelligence
GitHub
Health
Visit WebsiteSee on Product HuntGithub ⧉Twitter ⧉Streamlit ⧉

Hunted byzeeshen ul abidzeeshen ul abid

ClinicalTrial OS is an open-source AI platform that analyzes 5,000+ real clinical trials from ClinicalTrials.gov. It provides: 🧠 Protocol Intelligence πŸ“ˆ Recruitment Prediction πŸ₯ Site Selection ⚠️ Trial Risk Prediction βœ… ICH-GCP Compliance πŸ’Š Pharmacovigilance using FDA FAERS data πŸ“Š Analytics across 10 diseases 100% Free β€’ 100% Open Source β€’ Python + Streamlit

Top comment

I built ClinicalTrial OS because clinical trials fail too often due to problems that AI can solve. 50% of trials fail due to recruitment. Sites are chosen badly. Protocols have errors nobody catches. I spent 4 days building a tool that analyzes 5000+ real trials using AI β€” completely free and open source. Would love feedback from anyone working in clinical research or drug development. Live: https://clinicaltrial-os.streaml...

Comment highlights

Hi Product Hunt! πŸ‘‹

I built ClinicalTrial OS because planning a clinical trial still depends on expensive enterprise tools or hours of manual searching on ClinicalTrials.gov. I wanted researchers, students, small biotechs and CRO teams to get trial intelligence for free, from real public data.

What it does today:

πŸ” Search 4,785 trials by drug, sponsor, condition or NCT ID, with full trial details

πŸ“ Rank 20,000+ real trial sites across 124 countries on a world map

πŸ“ˆ Benchmark recruitment timelines from similar completed trials

⚠️ Estimate early-stop risk (model accuracy shown openly, not hidden)

βœ… 23-point registry quality check for any trial

🧠 Break down eligibility criteria and compare complexity with peer trials

πŸ’Š FDA adverse event reports (FAERS)

πŸ“„ One-click PDF trial reports

Everything is built on ClinicalTrials.gov and FDA data, every model explains its method and limitations, and it's fully open source (MIT).

It's for research and education, not medical advice.

I'd love your feedback:

- Which feature would you actually use in your work?

- What data or disease areas should I add next?

GitHub: https://github.com/sahilabid9593-cloud/clinicaltrial-os

Thanks for checking it out! πŸ™

About ClinicalTrial OS on Product Hunt

β€œOpen source AI operating system for clinical trials”

ClinicalTrial OS was submitted on Product Hunt and earned 0 upvotes and 2 comments, placing #83 on the daily leaderboard. ClinicalTrial OS is an open-source AI platform that analyzes 5,000+ real clinical trials from ClinicalTrials.gov. It provides: 🧠 Protocol Intelligence πŸ“ˆ Recruitment Prediction πŸ₯ Site Selection ⚠️ Trial Risk Prediction βœ… ICH-GCP Compliance πŸ’Š Pharmacovigilance using FDA FAERS data πŸ“Š Analytics across 10 diseases 100% Free β€’ 100% Open Source β€’ Python + Streamlit

ClinicalTrial OS was featured in Open Source (69k followers), Artificial Intelligence (481.6k followers), GitHub (41.4k followers) and Health (7k followers) on Product Hunt. Together, these topics include over 187.4k products, making this a competitive space to launch in.

Who hunted ClinicalTrial OS?

ClinicalTrial OS was hunted by zeeshen ul abid. A β€œhunter” on Product Hunt is the community member who submits a product to the platform β€” uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.

Want to see how ClinicalTrial OS stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.