Your Intelligent Patient-to-Trial Matching Assistant for Precision Therapies

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About Our Platform

AI-Powered Patient Matching for Smarter Trial Enrollment

TrialFit.Ai is an integrated, AI-powered platform that accurately matches patients to the most suitable therapies and clinical trials, whether approved or investigational. By leveraging patient clinical data from electronic health records (EHRs/EMRs), the platform constructs digital twins and aligns them with therapies using disease models trained on real-world multimodal data.

WHY USE TRIALFIT.AI?

Accelerating Patient Access to the Right Therapies Through Intelligent Trial Matching

TrialFit.Ai expands access to clinical trials by moving beyond rigid, narrow matching criteria, ensuring that patients are considered for studies that genuinely align with their individual clinical profiles. Its streamlined, data-driven matching accelerates trial enrollment and improves recruitment efficiency. Most importantly, by prioritizing therapies based on predicted treatment response and disease progression, TrialFit.Ai supports personalized strategies designed to improve long-term patient outcomes.

HOW IT WORKS

Turning Patient Data Into Precision
Trial Matches

TrialFit.Ai integrates advanced AI, disease modeling, and real-world clinical data to match patients with the right therapies and clinical trials.

Creating Digital Twins

Patient data from EHRs and EMRs is transformed into rich clinical profiles—digital twins—that capture each individual’s disease characteristics with precision.

Multimodal Disease Models

TrialFit.Ai leverages advanced disease models built using machine learning and foundation models trained on public datasets. These patient-agnostic models draw from thousands of cases and are optimized to predict drug response, disease progression, and long-term outcomes.

Therapy Matching

Digital twins are mapped onto the disease model space to evaluate clinical similarities. This comparison helps identify therapies most likely to deliver meaningful, long-term results for each patient.

Clinical Trial Matching

Matched therapies are linked to relevant clinical trials through BioThinkHub—ThinkBio.Ai®’s integrated knowledge platform. BioThinkHub aggregates global trial registries, scientific literature, and drug databases to recommend trials best suited to each patient profile.

Key Features & Capabilities

Smarter therapy decisions. Faster trial access. Better patient outcomes

Precision Therapy Matching

Advanced algorithms transform EHR and EMR data into rich patient profiles, analyzing complex clinical features to identify therapies with the highest likelihood of success. Patients are matched to treatments using disease-specific model projections for optimal outcomes.

Digital Twin Technology

Real-time digital twins reflect each patient’s evolving clinical state. Built from actual medical data, these dynamic models simulate disease trajectories and predict therapy response—enabling truly personalized care decisions.

AI-Driven Disease Models

Trained on data from thousands of patients, our disease models offer a scalable, unbiased foundation for therapy guidance. They’re fine-tuned to forecast drug response, disease progression, and long-term outcomes across conditions.

Clinical Trial Matching Engine

Patients are instantly connected to relevant clinical trials. The platform scans global trial databases, literature, and drug registries—filtering by eligibility, location, and therapeutic fit—to surface the best opportunities in real time

End-to-End Clinical Enablement

TrialFit.Ai bridges the gap between care and trial enrollment. It automates matching within existing workflows, reduces delays, and expands access to investigational therapies, ensuring every patient gets the best next step.

Scalable & Secure Infrastructure

Designed for enterprise deployment, TrialFit.Ai integrates with major EHR systems and supports disease-specific customization. Built to meet global data privacy standards, including HIPAA, with security and compliance at its core.

Contact Us

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