V.HEART Discovery
Select candidates with human QT prolongation predictions
Company profile
Company profile
ELEM Biotech is a healthcare technology company specializing in cardiac digital twin platforms that transform drug development and clinical decision-making. The company's flagship products, V.HEART Trials and V.HEART Discovery, enable pharmaceutical companies, clinical research organizations, medical device manufacturers, and healthcare providers to simulate virtual clinical trials and predict cardiac safety risks before human testing. V.HEART Discovery focuses on early-stage cardiac safety prediction, allowing researchers to screen drug candidates for QT prolongation and arrhythmic risk across concentration ranges up to 50x effective doses. V.HEART Trials enables full clinical trial simulation on the cloud, allowing users to configure virtual patient populations, apply treatments, and analyze results in hours rather than months. The technology combines patient-specific data, high-performance physics-based simulation, and advanced AI to create virtual human populations that reflect real-world diversity. ELEM's platforms help clients reduce R&D costs by up to 80%, decrease failure rates by 30%, and generate scientific evidence for regulatory submissions. The company serves multiple healthcare sectors including pharma, CROs, regulators, medical device companies, and health delivery organizations, supporting applications from hit-to-lead optimization to precision medicine and value-based healthcare initiatives.
Company description ELEM Biotech official website
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01 · Operating footprint
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Cloud Saas deployment with recorded integration context.
Company milestones
Published AI-enhanced cardiac digital twins paper on drug proarrhythmic risk assessment. Conducted cardio-oncology safety trial with 120 virtual patients. Completed pacing optimization study using 15 real patient digital twins expanded to 150 synthetic patients. Developed respiratory drug delivery optimization for 5,000 virtual population from 100 anatomies.
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02 · Flagship portfolio
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Select candidates with human QT prolongation predictions
Configure, run and analyse virtual clinical trials on the cloud
03 · Research intelligence
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Research
Regulatory toxicology and pharmacology : RTP · Jun 1, 2026
Can in silico models predict drug-induced cardiac risk in vulnerable populations?Toxicology reports · Jun 1, 2026
Advancing aortic stenosis assessment: Validation of fluid-structure interaction models against 4D flow MRI data.The Journal of physiology · Apr 4, 2026
Incidental findings and duty-of-care protocols in cardiovascular magnetic resonance among older adults: a prospective population-based study from MyoFit46.The lancet. Healthy longevity · Feb 1, 2026
Higher Life-Course Blood Pressure Associates With Reduced Myocardial Perfusion in Older Age: Insights From MyoFit46.Circulation. Cardiovascular imaging · Feb 1, 2026
Electromechanical computational modeling of heart failure provides extensive analysis of cardiac pathophysiological features.Biomechanics and modeling in mechanobiology · Jan 13, 2026
Clinical validation
NCT07462572 · Sponsor · NOT YET RECRUITING
Regulatory
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04 · Company-reported outcomes
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Reducing R&D expenses by identifying cardiac risks earlier
Reducing failure rates with advanced cardiac safety predictions
Created 120 virtual cardio-oncology patients from real cohort
Screen molecules up to 100x effective concentrations for QT prolongation
Test multiple scenarios in hours instead of months
Accelerate cardiac safety assessment for new cancer treatments
5x matching virtual cardio-oncology cohort of 120 gender-balanced Virtual Patients delivered within days, enabling prevention of adverse events and avoiding recruitment delays
Pacing optimization for pediatric patients using digital twins to assess device therapy efficacy
Studied 10 different pacing scenarios for each of 15 real patients, then developed synthetic population of 150 additional patients to fill study gaps
Maximize efficacy of respiratory nasal spray drug delivery
Created virtual population of 5,000 from 100 detailed human respiratory anatomies, optimized drug delivery to target area with studies completed in days
05 · Leadership
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06 · Company updates
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07 · HAIC coverage
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08 · Official presence
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09 · Market pathway
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Market context
Companies applying AI to cardiovascular disease detection, ECG/EKG analysis, heart failure management, cardiac imaging, arrhythmia detection, or cardiovascular risk assessment. Includes AI-powered cardiac diagnostics, non-invasive hemodynamic monitoring, and tools for early detection and personalized management of heart conditions.
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