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OpenDNA  CardioRisk 

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Using precision genomic AI to predict and prevent heart disease
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Heart disease is a global problem

It is the leading cause of death in the world -- claiming 18.6 million lives a year

Genomics can predict heart disease and point the way to prevention

Our prediction models help identify high risk patients and their key (or targeted) prevention strategies

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  • Diabetes

  • Hypertension

  • High Cholesterol

Taking action is critical

Lifestyle changes and treating related diseases are essential for preventing heart disease.

Better care = lower costs

Preventing heart disease keeps people healthier and reduces healthcare expenses 

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OpenDNA CardioRisk+ 
How it Works 

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Data Collection

Simple cheek swab for genetic analysis

Electronic Health Record data retrieval for patient history

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Precision Genomic Modeling for Risk Score

Polygenic risk score is developed to estimate the genetic risk to heart disease, calculated according to a person’s genotype profile and based on relevant genome-wide association study (GWAS) data

3

Patient Education Tool

OpenDNA-CARDIO’s interactive education tool presents a patient’s heart disease risk score, risk factors and targeted prevention strategies for improving heart health

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Technology

OpenDNA Technology

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Genetic and clinical data collection

Genetic testing is done using a simple cheek swab. Rich, longitudinal clinical data
is imported from EHRs for the most complete dataset

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Next generation genetic analysis technology

Polygenic scores from millions of DNA variations together with millions of clinical data points allow maximum prediction power

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AI platform

Proprietary machine learning algorithms provide risk predictions and treatment recommendation

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Interactive dynamic reports 

Interactive reports are easy for physicians and engaging for patients 

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Scientifically backed with rigorous validation

AI algorithms are validated on a database of 500,000 patients curated by top level scientists

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 Patented technology for unique treatment algorithms

Patented treatment algorithms using polygenic risk score technology

Combining genetic data with clinical data allows for heart attack predictions with up to 85% accuracy*

*Open DNA internal validation
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News

News

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OpenDNA announces know-how and research agreement with Mayo Clinic
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Our team

Team

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Eran Feldhay 

MD, MBA

Over 20 years experience in medical software and devices; CEO of ApiFix, CEO of Trendlines Medical, GM at McKesson Israel after the acquisition of his company Medcon 

Associate Prof of Clinical and Molecular Epidemiology, Imperial College London, UK and University of Ioannina, GR. Over 190 publications, over 17,500 citations and 20 Nature Genetics publications. Top 2% scientist worldwide (Ioannidis et al. PLoS Biology;2020)

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Evangelos Evangelou

PhD 

25 years experience in software development. Software group leader in Bio-Rad. Holds a BSc. in computer sciences, BA in management from 
Tel-Aviv university, and MA in Philosophy from the Haifa university

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Erez Ornan

BSc, MA

Decades of entrepreneurship and international business development experience in Fortune 500 and startups. CEO of PharBeyond, VP BD at BioLineRx, VP Sales at Compugen USA, Inc. and franchise manager at J&J. B.Sc. in Biology from Bar Ilan University 

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Nir Gamliel

BSc

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