EMA Wellness and Mira Analytics Form Exclusive Partnership to Deploy AI-Driven Endpoint Validation in CNS Clinical Trials
核心洞察
EMA Wellness (搜索) and Mira Analytics (搜索) announced an exclusive partnership to deploy AI-driven endpoint validation and rater surveillance across global CNS (搜索) clinical trials using advanced large language models.
The partnership integrates Mira's AI models directly into EMAW's GIANT™ (搜索) platform, enabling real-time quality assurance and continuous monitoring of clinical interviews instead of retrospective review.
Mira's AI models can independently score clinician-rated interviews at a level comparable to expert human raters, helping sponsors improve rater consistency and reliability in real time.
EMA Wellness (搜索) (EMAW), a leading clinical trial data platform for AI-enabled eCOA, central ratings and analytics, announced an exclusive partnership with Mira Analytics (搜索) to deploy AI-driven endpoint validation and rater surveillance across global CNS (搜索) clinical trials. The collaboration will leverage EMAW's market-leading data capture platform to run advanced large language models validated in today's global CNS registration trials.
Platform Integration and Capabilities
EMAW's platform standardizes the collection of multimodal data including eCOA, audio/video, EMA, digital biomarkers, and passive sensor data within a unified architecture. The EMAW single stack platform enables real-time analytics and AI-driven signal detection to enable Real Time Clinical Trials, inform precision study design and drive enhanced subject selection/stratification, and endpoint reliability. EMAW's single code platform has been validated across multiple Phase 2 and 3 global trials, and is HIPAA, GDPR and 21 CFR part 11 compliant.
Mira Analytics (搜索)' AI models are grounded in its founding team's experience working to assess and independently score thousands of recorded clinical interviews in Phase 2 and Phase 3 global CNS (搜索) trials. This experience and access to data, combined with one of Europe's most sophisticated engineering teams, enables Mira to deliver AI-enabled rater surveillance with improved accuracy, speed and cost.
Real-Time Quality Assurance
Mira's AI models generate independent scores and quality assessments which automate flags where there is discordance from primary ratings, thereby helping sponsors improve rater consistency and reliability in real time, and make better inclusion, stratification and remediation decisions during the course of a trial.
"Our focus is on ingesting high-quality, multi modal clinical data and making it actionable in real time," said Colin Bower, co-founder and CEO of EMA Wellness (搜索). "By integrating Mira's models directly into our platform, sponsors can move from retrospective review to continuous quality assurance across their trials. This effort, combined with the API access we provide our sponsor partners for real time data access, also enables our partners to use AI to signal detect across data modalities at a study and enterprise level – something sponsors and the FDA are seeking today."
Clinical Interview Analysis
"Clinical interviews remain the most information-rich data we collect in CNS (搜索) trials, and also the hardest to measure consistently," said Mira co-founder and CEO, Adam Kolar. "That's the gap our models are built to close. Working alongside EMAW means we can apply that precision at scale, across more programs and more therapeutic areas."
Mira's approach builds on findings presented by its founders at a leading CNS (搜索) clinical trials methodology conference, showing that AI models can independently score clinician-rated interviews at a level comparable to expert human raters. Building on this foundation, Mira develops models for rater surveillance and endpoint validation, with ongoing validation across different measures and conditions.
Platform Performance and Impact
EMAW has achieved strong ROI for sponsor partners, including the ability to capture and quality assure 100% of all clinical interviews and remediate poor quality sites and raters. AI-driven flagging enables targeted, real-time review by clinicians, significantly reducing manual effort and cost while improving ratings quality and consistency.
The EMAW GIANT™ (搜索) platform standardizes multimodal data collection in clinical trials, including eCOA, EMA/diary, sensor, passive and other real-world data sources, via its proprietary application, browser-based interface, SDK, or API. Standardization of these data enables real time AI enabled analysis and signal detection for enhanced subject selection, endpoint reliability and phenotyping for treatment effect.
EMAW's multi modal platform is being used to more effectively assess data, signal detect, and phenotype patients for faster readouts as well as to predict treatment effect and define inclusion/exclusion criteria in smaller, higher powered follow-on trials. The platform provides full audit trails across data and the patient journey, enhancing how sponsors report to the FDA.
Global Reach and Validation
The EMAW platform is being used in more than 25 countries and by over 250 sites. EMAW was founded in 2018 by clinical research leaders, technology experts, and industry executives to improve outcomes in CNS (搜索) clinical trials through contemporary, validated technology.
Mira's platform surfaces trends across raters, sites and studies, giving sponsors an analytical view of measurement quality that has historically been difficult to access. These insights help identify systematic rating patterns early, support targeted training, and improve consistency across global programs. Mira Analytics (搜索) is headquartered in Czechia, and works with leading biopharma sponsors and CROs running global CNS (搜索) programs.