Trial Tracker for Patients
A patient-facing clinical trial radar that watches registries like ClinicalTrials.gov and surfaces trials patients might actually qualify for, with plain-language summaries of what each trial is testing.
Patients with serious or chronic conditions (HIV, cancer, autoimmune) who want to find relevant clinical trials without jargon
- Plain-language trial summaries auto-generated from registry entries, with eligibility explained
- Personal match score based on diagnosis, stage, location, and prior treatments
- Push alerts when new trials open in your disease area
- 'Questions to ask my doctor' printable PDF for each matched trial
With the HIV vaccine entering human trials and dozens of other breakthroughs in the pipeline, patients need a faster way to find and understand trial options beyond their doctor's awareness.
ClinicalTrials.gov hosts 400,000+ studies across 220 countries and many derivative search portals exist, indicating real ongoing patient search volume for trials.8 Clinical Trial Databases Open to Patient Search ↗
Highly crowded field: Antidote (well-funded, sponsor-backed), Trial-Finder.com, ClinicalTrialsFinder.org, ClinTrialFinder (AI-powered), PMATCH, Clinical Trials Navigator, plus NIH itself released its own AI matching algorithm in Nov 2024.NIH-developed AI algorithm matches potential volunteers to clinical trials ↗Clinical Trial Patient Recruitment | Antidote ↗
Patients almost never pay; the dominant model is pharma/CRO sponsorship (Antidote sells recruitment to sponsors). The official ClinicalTrials.gov is free and authoritative, making direct patient monetization very difficult.Clinical Trial Patient Recruitment | Antidote ↗Antidote: Pricing, Reviews & Features 2025 | Pharma Tools ↗
Clinical trial volume and patient demand are structurally growing; AI-driven matching is a durable trend backed by NIH, Nature, and major pharma investment.Matching patients to clinical trials with large language models ↗
ClinicalTrials.gov API is public and plain-language LLM summarization is straightforward, but accurate patient-to-trial eligibility matching over complex inclusion/exclusion criteria is technically hard and competes with NIH's own TrialGPT-class systems.