Selventa

Selventa

Patient data analysis for therapeutic and diagnostic decisions.

HQ location
Cambridge, United States
Launch date
Employees
Enterprise value
$26—39m
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DateInvestorsAmountRound
investor investor

€0.0

round
N/A

€0.0

round
N/A

$5.0m

Debt
Total Funding000k
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Selventa, formerly known as Genstruct Inc., was a biomarker discovery and personalized healthcare company founded in 2001. The firm focused on analyzing complex patient data to support therapeutic and diagnostic decisions for its partners in the pharmaceutical and biotechnology sectors.

The company's core technology was its Systems Diagnostics (SysDx) platform, an analytics engine designed to identify disease-specific biomarkers by integrating various types of biological data, including genomic, proteomic, and electronic medical records. This platform utilized a computable causal modeling approach to gain mechanistic insights into diseases, particularly in areas like oncology, autoimmune diseases, metabolic disorders, and inflammation. One of its key products was ClarifyRA, a decision support tool intended to help physicians select the most effective treatment for rheumatoid arthritis (RA) patients based on their molecular profile. In 2012, Selventa released its Biological Expression Language (BEL) as an open-source platform to foster a broader knowledge ecosystem.

Originally founded as Genstruct, the company rebranded to Selventa in late 2010 to reflect a new strategic focus on partnerships and personalized healthcare. David de Graaf was appointed CEO in December 2010, having previously served as Chief Scientific Officer. Throughout its history, Selventa raised a total of $12M-$13.5M in funding from investors including Flagship Pioneering and Pappas Capital. The company ceased operations around June 2017.

Keywords: biomarker discovery, personalized healthcare, systems biology, patient data analytics, therapeutic development, diagnostic tests, causal modeling, Genstruct, Systems Diagnostics, SysDx, ClarifyRA, rheumatoid arthritis, oncology, autoimmune diseases, drug discovery, patient stratification, molecular diagnostics, computational biology, biological data

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