OpGen subsidiary Ares Genetics announces the strategic expansion of ARESdb proprietary contents
- Following successful completion of Phase 1, Ares Genetics has now entered into Phase 2 of its collaboration with a leading
U.S.CRO and reference lab, gaining access to 1,000 proprietary clinical isolates from key pathogens
- ARESdb contents has grown by more than 40% in a year
Antimicrobial resistance (AMR) is a growing threat to public health believed to be causing 700,000 fatalities globally each year and billions of
Conventional culture-based diagnostics can determine effective antibiotics through antibiotic susceptibility testing (AST); however, they tend to be slow and insensitive. Ares Genetics is addressing this problem from a different angle, using artificial intelligence to accurately predict directly from genomic data if a pathogen is susceptible or resistant to a given antibiotic. Central to this approach are the datasets required to train predictive models, comprised of genome and phenotypic AMR data that have been generated under controlled conditions and a robust model training and testing framework.
Ares Genetics has developed ARESdb, a leading database on AMR, and has published several scientific studies on the performance1,2 of its predictive models as well as important considerations of model training3,4. ARESdb not only comprehensively collects known genetic markers for AMR, but also harbors more than 78,000 datasets essential for the development and training of predictive models. This is up by over 40% from around 55,000 datasets a year ago.
“ARESdb is central to our development of AI-powered applications for AMR prediction” stated Dr. Arne Materna, CEO of Ares Genetics. “It is an essential component of a number of our commercial solutions, including sequencing services offered through our service laboratory located in
The value of ARESdb and machine learning for predicting antibiograms from genomic data is increasingly recognized by key opinion leaders around the world and has recently materialized in a strategic data access transaction under which a global corporation and leader in microbiology and infectious disease diagnostics was granted access to a narrowly defined subset of ARESdb corresponding to 1.1% of the current database contents.
Ares Genetics intends to further increase the value of ARESdb and grow its contents in the coming months and years through strategic collaborations with external partners and by supporting clinical trials conducted by its affiliates at
- Banerjee, R. et al. Core Genome Multi-Locus Sequence Typing and Prediction of Antimicrobial Susceptibility Using Whole Genome Sequences of Escherichia coli Bloodstream Infection Isolates. Antimicrob Agents Ch AAC0113921 (2021) doi:10.1128/aac.01139-21.
- Ferreira, I. et al. Species Identification and Antibiotic Resistance Prediction by Analysis of Whole-Genome Sequence Data by Use of ARESdb: an Analysis of Isolates from the Unyvero Lower Respiratory Tract Infection Trial. J Clin Microbiol 58, (2020).
- Májek, P., Lüftinger, L., Beisken, S., Rattei, T. & Materna, A. Genome-Wide Mutation Scoring for Machine-Learning-Based Antimicrobial Resistance Prediction. Int J Mol Sci 22, 13049 (2021).
- Lüftinger, L., Májek, P., Beisken, S., Rattei, T. & Posch, A. E. Learning From Limited Data: Towards Best Practice Techniques for Antimicrobial Resistance Prediction From Whole Genome Sequencing Data. Front Cell Infect Mi 11, 610348 (2021).
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This press release includes statements regarding Ares Genetics’ strategic expansion of ARESdb and certain of its related collaboration arrangements. These statements and other statements regarding OpGen’s future plans and goals constitute "forward-looking statements" within the meaning of Section 27A of the Securities Act of 1933 and Section 21E of the Securities Exchange Act of 1934 and are intended to qualify for the safe harbor from liability established by the Private Securities Litigation Reform Act of 1995. Such statements are subject to risks and uncertainties that are often difficult to predict, are beyond our control, and which may cause results to differ materially from expectations. Factors that could cause our results to differ materially from those described include, but are not limited to, our ability to successfully, timely and cost-effectively develop, seek and obtain regulatory clearance for and commercialize our product and services offerings, the rate of adoption of our products and services by hospitals and other healthcare providers, the fact that we may not effectively use proceeds from recent financings, the realization of expected benefits of our business combination transaction with
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