ClinicalMatch AI

Created by team ClinicalTrail on February 14, 2025

ClinicalMatch AI addresses one of healthcare's most pressing challenges: the inefficient and costly process of clinical trial recruitment. Our platform leverages DeepSeek's advanced AI technology to create a seamless bridge between patients and clinical trials, transforming a process that typically takes months into one that takes days. The platform works by: Analyzing unstructured medical records in real-time using DeepSeek's natural language processing Automatically matching patients with suitable trials based on multiple criteria including medical history, genetics, location, and trial requirements Providing instant compatibility scores and detailed matching analysis Facilitating digital enrollment and ongoing trial participation Key Features: Real-time medical record analysis Multi-dimensional matching algorithms Predictive dropout prevention Smart protocol optimization Digital enrollment assistance HIPAA-compliant security Our solution addresses critical industry pain points: 80% of clinical trials fail to meet enrollment deadlines $600,000+ lost per day due to recruitment delays 30% dropout rate in clinical trials Millions of patients miss trial opportunities $2.6B average cost to bring a drug to market The platform serves multiple stakeholders: Patients gain access to cutting-edge treatments Healthcare providers can better serve their patients Research organizations reduce recruitment costs and times Pharmaceutical companies accelerate drug development Initial results show: 60% reduction in recruitment time 40% increase in trial completion rates 45% lower per-patient recruitment costs 85% patient satisfaction rate 3x increase in trial diversity Our roadmap includes expanding into: Additional therapeutic areas International markets Advanced genomics matching Real-world evidence collection

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"The use case makes sense but the execution and the presentation could use a bit more work. The parameters used need to be refined further to get valuable recommendations and be business-ready."

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Surabhi Nayak

Privacy Engineer