At Ares Genetics, we develop precision diagnostics for precision medicine to improve the way infections are diagnosed and treated.
We are data scientists, bioinformaticians, microbiologists, pharmaceutical, diagnostic and commercial experts that share a vision for the next-generation of genomics-based infectious disease diagnostics & therapeutics.
Join us in taking infectious disease diagnostics to the next level!
Besides the openings listed below, we are regularly offering part- or full-time positions as well as PhD and master theses and welcome unsolicitated applications.
At Ares, we pursue a partnership based, open-innovation approach with academic and industry partners and are committed to sharing our developments with the community.
Joint Ares Genetics publication with Johns Hopkins University. Mutations in the AmpC-AmpR region are associated with treatment-emergent ceftolozane-tazobactam (TOL-TAZ) and ceftazidime-avibactam (CAZ-AVI) resistance. We sought to determine if these mutations impact susceptibility to the novel cephalosporin-siderophore compound cefiderocol.
Joint Ares Genetics publication with the Medical University of Innsbruck and the Danube University Krems. In this retrospective study, we investigated genetic resistance mechanisms, sequence types (ST) and respective phenotypes of linezolid-resistant Staphylococcus epidermidis (LRSE) recovered from a cohort of patients receiving or not receiving linezolid within a tertiary hospital in Innsbruck, Austria.
The work led by Ares Genetics and performed in collaboration with Prof. Thomas Rattei from the Division of Computational Systems Biology at the University of Vienna critically assessed different machine learning (ML) techniques for whole genome sequencing (WGS)-based AST on several thousand genome assemblies across more than 50 species/compound combinations collated from public databases. The publication describes the combination of different machine learning architectures for robust and accurate WGS-based AST.
This publication demonstrates applicability of k-mer based clinical microbiology assays for whole-genome sequencing (WGS) including variant calling, taxonomic identification, bacterial typing as well as AMR marker detection. The wet-lab and dry-lab workflows were developed and validated in line with Clinical Laboratory Improvement Act (CLIA) guidelines for laboratory-developed tests (LDTs) on multi-drug resistant ESKAPE pathogens.
Have you ever wondered how rapidly resistance develops against new antibiotics? Unfortunately, very soon after their introduction into clinic. Have you ever wondered about the number of infections that cannot be treated with existing antibiotics? Luckily only very few, in fact less than 0.1%. The world is on the verge of losing antibiotics as its most powerful tool in healthcare. Read our whitepaper why new antibiotics won’t solve the antibiotic resistance crisis, but better diagnostics could.
Multi-center US study demonstrating feasibility and potential of next-generation sequencing based antibiotic susceptibility prediction using ares-genetics.cloud. The study evaluated the performance of pathogen identification and antibiotic susceptibility testing based on whole genome DNA sequencing (WGS) using Ares Genetics’ AI-powered cloud-based bioinformatics platform and the underlying reference database, ARESdb. WGS-predicted susceptibility to antibiotics showed 89% categorical agreement with the current reference method of broth microdilution susceptibility testing across a total of 129 pathogen-drug pairs analyzed. Categorical agreement exceeded 90% in 78, and reached 100% in 32 pathogen drug pairs.
Joint Ares Genetics publication with Prof. Müller (HIPS Saarbrücken) and Prof. Keller (CCB Saarland). The study introduces a novel, universally applicable high-throughput workflow for rapid identification and functional validation of antimicrobial resistance (AMR) biomarkers from >1,000 clinical isolates. When combined in a multiplex diagnostic in silico panel, the identified AMR biomarkers reached high positive and negative predictive values of up to 97 and 99%, respectively. Additionally, we demonstrate that the developed workflow can be used to identify potential novel resistance mechanisms.
Joint Ares Genetics publication with Prof. Keller’s group at Saarland University introducing GEAR-base as a standardized research resource for antibiotic resistance genotypes and phenotypes. GEAR-base was originally established in collaboration with Universität des Saarlandes and Siemens and forms the nucleus of our proprietary ARESdb now combining whole-genome sequencing data for > 35,000 isolates with quantitative antibiotic susceptibility data for >100 antibiotics..
Joint Ares Genetics publication with Prof. Keller’s group at Saarland University assessing the heterogeneity of in silico plasmid predictions based on whole-genome-sequenced clinical isolates. The study identified a high degree of heterogeneity and variation in sensitivity and precision for plasmid identification across taxa and computational approaches. Nevertheless, existing open source tools are very valuable for investigating the plasmid-borne resistome. Building upon the peer-reviewed research findings, the proprietary ARES Technology allows for fast and optimized plasmid identification from whole-genome sequencing data.
We offer a comprehensive portfolio of solutions for antimicrobial drug discovery, clinical development, and product lifecycle management. Our solutions aim at supporting data-driven target and lead prioritization, accelerating clinical trials, augmenting clinical data for regulatory submissions, and informed antimicrobial drug use for effective antibiotic stewardship post launch.
Joint Ares Genetics publication with Prof. Keller’s group at Saarland University comparing genome versus proteome-based identification of clinical bacterial isolates. Key findings include that taxonomic identification based on the proteome (by mass spectrometry, MS-biotyping) and the genome (by next-generation sequencing, NGS) show high concordance for clinical application. While NGS successfully resolved all clinical isolates on the species level, for 12% of the cases MS-biotyping resulted in genus level classification only. Building upon the peer-reviewed research findings, ARES Technology allows for fast and accurate taxonomic identification on the species level.