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CGN enters into collaboration with Novo Nordisk to generate data on STARNET.


CGN signs agreement with Mount Sinai on license agreement to the Beat-IT technology.


Clinical Gene Networks AB is a SME in the EU-project, CVD@target financed within the 7th frame program. CGN will perform data analysis to evaluate genetic markers associated with coronary artery disease. Leading scientists of genome-wide association studies (GWAS) in Germany and United Kingdom are other partners in this project


Prof. Eric E Schadt becomes major shareholder and board member of CGN. Dr Schadt's belief in CGN:s unique biobanks and datasets is a key motivation for his increased engagement in CGN something the board of directors warmly welcome. "The last 2-3 years have been tough for CGN, Eric's recognition of CGN:s business concept to build predictive disease models from clinical gene networks is therefore particular important" say newly elected chair of the board, Johan Björkegren.


CGN:s CEO since 9 years, Johan Björkegren today announces his retirement. "The growth of CGN now requires a full-time CEO that can take recent success of the company's network-based drug-discovery pipeline to collaborations with the pharmaceutical industry" says Björkegren who will remain on the board and provide support for the new CEO who is currently being recruited. Björkegren's choice of time point for his retirement relates to his parallel commitment as a full-time researcher at the Karolinska Institutet. In the overlapping period, operative matters will be handled by the board.

CGN on the cover of Science

Science at CNG


Coronary and carotid artery disease (CAD) are the underlying causes of two of our time's most deadly diseases, myocardial infarction (MI) and stroke. A common misconception is that cardiovascular disease (CVD) mainly in the form of MI and stroke are isolated problems of the western societies, particularly in men. Instead, the development is particularly grave in emerging economies like Russia, China, India and South America. Already today, CVDs kill 17 million individuals per year (~30% of all deaths) and are predicted to cause over 30 million deaths annually after year 2030 (~37% of all deaths). As nearly 50 % of people are at risk, CVD drug sales account for an astonishing $76 billion annually (2008).

Clinical Gene Networks (CGN), founded in 2003, seeks to commercialize clinical gene networks underlying CAD, MI and stroke identified through a systems-based, integrated and data-driven research pipeline provided mainly through access to unique clinical cohorts gathered at the Karolinska University hospital and more recently at Tartu University Hospital in Estonia. CGN is together with its academic partners applying computer-supported algorithms on genome-wide datasets in peta-byte scale generated from a wide range of CAD-relevant tissues isolated from unique clinical CAD cohorts and from model systems of CAD. All data and results from the data analysis is stored in a dataset referred to as AtheroCode. CGN has been fundamental to help finance data generation and perform data analysis in the AtheroCode.

AtheroCode is the source from which clinical gene networks underlying CAD are defined. These networks contain genes previously known to affect CAD development (we call them "effector" genes), previously unknown effector genes as well as genes that has little or no known effect. However, the most interesting genes are those that are central in the networks with many interactions (we call them "master regualtors", like transcription factors, kinases and G-coupled proteins). Since these genes frequently control the activity of many if not all effectors genes, master regulators are beleived suitable targets against which new CAD drug candidates can be screened s well as suitable biomarkers for molecular disease activity reflected by networks. By inferring disease networks CGN seeks to eventually benefit the patients who suffer from CAD, MI or stroke. Unlike current drugs and diagnostics defined by studies of disease genes one by one, CGNs targets are in this way selected from networks that can be described as detailed maps of the entire wiring diagram in and across tissues acting to cause CAD. These maps are also the basis for how CGN defines biomarkers for predictive diagnostics and small molecules as candidate drugs. CGN develops these candidates to a stage at which they can be taken into clinical trials in collaboration with pharmaceutical companies.

2010, CGN in collaboration with its academic partners defined its first network-based candidate drug that currently are being tested in model systems of CAD after which successful candidates will enter into negotiations with major pharmaceutical companies to pursue clinical trials.

Please read more about CGN at this website. I hope you'll find the company to be appealing and interesting. If you do and like to know more - do not hesitate to make contact!

Statement of the Board of Clinical Gene Networks AB