Clinical trial matching AI
TrialScreen
TrialScreen is a free global clinical trial search engine at trialscreen.org, operated by Australian company TrialScreen Pty Ltd, which acquired the Opin recruitment business from ASX-listed Opyl in 2024 under Dr. Hugo Stephenson. Patients can search 100,000+ recruiting trials and self-check eligibility without an account, while the company's revenue comes from recruitment software and services for sponsors, CROs, and sites, including AI-assisted eligibility criteria and digital triage. TrialScreen is corporately independent of Outcomes4Me.
Public-source research has been drafted; final human publication review and change-log detail are still required.
Summary judgment · 55% toward patient-directed
Mixed, open patient search funded by sponsor recruitment
The free no-account trial search genuinely widens patient access to research options worldwide, but the operator is a recruitment business whose paying clients are sponsors and sites, so featured placement, managed-trial prioritization, and funnel incentives need scrutiny.
Patient agency
How this tool changes agency
Global trial search, condition hubs, eligibility self-screening, direct connection to researchers, and research-literacy FAQ content support patients in finding and pursuing research options their clinicians may never mention.
The privacy policy provides access and correction rights for personal information, but no public workflow exists to challenge an automated eligibility outcome, which the policy says depends on the information provided and the trial criteria.
Patient-facing signals
Who does this AI serve?
The search engine is free and openly patient-usable, but the operator's stated clients are biopharma, CROs, SMOs, sites, and academics, and the patient funnel is the recruitment product, with Opyl retaining a 20% equity stake.
Can patients tell AI is involved?
The privacy policy discloses that the eligibility checker is an automated process, and researcher pages disclose AI-assisted criteria for registry-sourced trials, but how clearly the patient-facing flow labels automation, AI involvement, and paid or managed trial placement needs verification.
Can patients meaningfully choose?
Search requires no account or registration, eligibility checks are self-initiated, contact details are shared with study teams only by the user's choice, and removal can be requested, though removal requests after connection are forwarded to study teams rather than handled directly.
Can patients correct or challenge what the AI produces?
The privacy policy provides access and correction rights for personal information, but no public workflow exists to challenge an automated eligibility outcome, which the policy says depends on the information provided and the trial criteria.
Does it help patients understand or act?
Global trial search, condition hubs, eligibility self-screening, direct connection to researchers, and research-literacy FAQ content support patients in finding and pursuing research options their clinicians may never mention.
Text findings
Who is left out or burdened?
Evidence incomplete
Free no-account access lowers barriers, and the company markets multilingual triage and underrepresented-population recruitment as sponsor-side specialties, but patient-side language support, accessibility, digital access burden, and geographic trial density gaps are not independently evidenced.
What happens to patient data?
Moderate disclosure with hygiene concerns
The policy states personal information is not sold, health data is collected only with explicit consent, data is stored on AWS in the US, GDPR/CCPA/APP rights apply, and sharing with sponsors and sites is consent-based, but the published policy contains leftover placeholder text and duplicated sections, retention is loosely defined, and AI model training use is not addressed.
Are the clinical boundaries clear?
Partial
The platform is framed as a search and connection tool rather than medical advice, and the eligibility checker is disclosed as automated and non-definitive, but explicit medical-advice disclaimers and escalation language were not located in this pass.
Who defined what good looks like?
Vendor-defined recruitment metrics
Public success measures are recruitment speed (4x faster claims), search volume, and enrollment outcomes for research clients; no patient-partnered governance or independent evaluation of matching accuracy or patient outcomes was found.
Review method
Public-source review of trialscreen.org and info.trialscreen.org homepage, about, researchers, and FAQ pages, privacy policy, Vic Trials partner listing, and Opyl/Opin divestiture press coverage; no platform walkthrough, vendor interview, or independent evaluation of matching accuracy.
Draft profile · Medium draft, official sources and divestiture news coverage