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Unlock enhanced clinical trial monitoring
and accelerate drug development

Work with mpathic to improve clinical trial quality and integrity with AI-powered fidelity monitoring, behavioral analytics, and real-time performance feedback.

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What mpathic enables for Life Sciences teams

Monitor Fidelity

Incorporate AI-powered analytics for fidelity monitoring to maintain the highest standards of trial quality and integrity.

Enhance Patient Experience

Prioritize patient-centric engagement, reduce dropout, and increase retention to improve trial success.

Reduce Bias & Variability

Identify and mitigate bias and clinician variability—especially critical in subjective or 
high-touch studies.

Accelerate Drug Development

Optimize trial management and timelines with AI-driven insights that support faster review and better decision-making.

Integrate Seamlessly

Connect analytics across sites, enable collaboration, and streamline trial management without disrupting your team’s processes.

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x
improvement in the speed of the review process
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%
sessions reviewed with mpathic vs. only 10% with human review
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cost savings with mpathic AI medical monitoring
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more accuracy than average medical monitor

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Backed by Science

mpathic is built on proprietary ML models developed with over a decade of scientific validation, using healthcare conversations labeled by psychologists and doctors to objectively enhance more than 200 human behaviors.

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Secure & Compliant

mpathic is built to support regulated environments and protect sensitive trial data. Our solutions are built in compliance with GDPR, HIPAA and SOC 2 Type II standards, independent penetration testing is conducted annually, and data segmentation is applied to all custom solutions.

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Powerful Solution for Psychedelic Clinical Trials

Psychedelic clinical trials have unique challenges: subjective participant experiences, heightened clinician influence, and increased risks of expectancy bias and variability. mpathic supports these studies with AI-driven tools built to increase fidelity and consistency, Identify and mitigate expectancy bias, and prevent functional unblinding and safeguard participants.

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