TrialMatch announces AI platform connecting patients to clinical trials in under 30 seconds, addressing global trial participation gaps.
— A New Approach to Clinical Trial Accessibility
TrialMatch, an AI powered healthcare technology platform founded by Joseph Oladokun, has announced its continued rollout in public beta, focusing on improving access to clinical trial opportunities for patients and caregivers. The platform addresses a long-standing structural challenge in clinical research, where a significant number of trials experience delays due to insufficient participant enrollment while many eligible patients remain unaware of available studies.
Bridging the Clinical Trial Participation Gap
Clinical trials are essential for advancing medical research and developing new treatments, yet participation barriers have limited their efficiency. Industry estimates indicate that nearly seventy five percent of clinical trials experience delays linked to recruitment challenges, while a large proportion of eligible patients are not informed of relevant opportunities through traditional healthcare pathways.
TrialMatch was designed to address this disconnect by creating a direct connection between patient medical data and active clinical research studies.
AI Driven Medical Record Interpretation
At the core of TrialMatch is an artificial intelligence system that processes patient submitted medical records in PDF format. The system extracts structured clinical indicators such as conditions, diagnoses, and biomarkers. This information is then analyzed against a database of active clinical trials to identify potential matches.
The process is designed to reduce manual navigation of complex medical registries and replace it with an automated matching system that returns results in a significantly shorter timeframe. According to the company, matching outcomes are delivered in under 30 seconds once records are processed.
Early Access and Public Beta Progress
TrialMatch is currently operating in public beta and has reported engagement from patients, caregivers, and research stakeholders. The platform has supported more than 1000 individuals in identifying relevant clinical trial opportunities during its early deployment phase.
Feedback collected during this phase has focused on usability, accessibility, and the ability to interpret complex eligibility criteria in a simplified format. The development team continues to refine matching accuracy and expand trial coverage as additional research partnerships are integrated.
Security and Data Handling Framework
Given the sensitivity of medical data, TrialMatch applies structured processing protocols to ensure secure handling of uploaded documents. Patient records submitted to the platform are analyzed for relevant clinical markers without requiring manual review of entire documents.
The system is designed to prioritize data minimization principles, extracting only necessary clinical attributes required for trial matching while limiting exposure of unnecessary personal information.
Founding Perspective and Mission Context
Joseph Oladokun, Founder of TrialMatch, developed the platform after identifying major inefficiencies in clinical trial recruitment and a widespread lack of patient awareness. Many trials face delays due to fragmented data and limited outreach, leaving eligible patients unaware of opportunities that could benefit them.
TrialMatch addresses this gap by using automation and data-driven matching to connect patients with relevant clinical trials. The platform is designed to simplify discovery, improve accessibility, and help accelerate research timelines by increasing participation. Its mission is to make clinical research more efficient while giving patients greater visibility into available treatment options.
Joseph Oladokun is a Data Scientist and Machine Learning Engineer specializing in Applied LLMs and healthcare AI. He has a strong track record of building AI systems across healthcare and technology. At Helium Health, he developed clinical NLP models that automated medical coding across hospital systems in Africa, improving both efficiency and data accuracy. He also brings experience from companies such as Asana, eHealth Africa, and Autochek Africa, where he contributed to scalable, data-driven solutions.
With a strong technical foundation and focus on healthcare innovation, Joseph is working to modernize clinical trial access and improve outcomes through AI.
Development and Future Expansion
TrialMatch continues to develop its platform with a focus on expanding integration across additional clinical trial registries and improving the precision of its matching algorithms. Future updates are expected to enhance interoperability with healthcare systems and broaden access to international trial databases, supporting a wider range of medical conditions and research categories.
Digital Access to Clinical Research Infrastructure
TrialMatch integrates across thousands of active clinical trials and continues to expand its dataset as new research opportunities become available. The platform is designed to function as a digital access layer between patients and clinical research infrastructure, translating medical documentation into structured eligibility insights.
The company’s website provides additional information and access to the beta platform.
About TrialMatch
TrialMatch is an artificial intelligence powered healthcare platform focused on improving access to clinical trials. The system enables patients and caregivers to upload medical records securely and receive automated matches to relevant clinical studies. By transforming unstructured medical documentation into structured clinical insights, TrialMatch aims to improve awareness and accessibility of research opportunities.
Media Contact
Joseph Oladokun
Founder, TrialMatch
Email: oladokunjoseph2@gmail.com
Website: TrialMatch
Contact Info:
Name: Joseph Oladokun
Email: Send Email
Organization: TrialMatch
Website: https://www.trial-match.com/
Release ID: 89187963
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