OpenDNA CardioRisk
+
Using precision genomic AI to predict and prevent heart disease
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
-
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
OpenDNA CardioRisk+
How it Works
1
Data Collection
Simple cheek swab for genetic analysis
Electronic Health Record data retrieval for patient history
2
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
OpenDNA Technology
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
Next generation genetic analysis technology
Polygenic scores from millions of DNA variations together with millions of clinical data points allow maximum prediction power
AI platform
Proprietary machine learning algorithms provide risk predictions and treatment recommendation
.png)
Interactive dynamic reports
Interactive reports are easy for physicians and engaging for patients
Scientifically backed with rigorous validation
AI algorithms are validated on a database of 500,000 patients curated by top level scientists
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
Team
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)
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
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
Nir Gamliel
BSc
Investors
