How We Do It – OmicEra Diagnostics

Source: European Patent Office

Source: European Patent Office

How
we
do it

Building on technology and experience developed in the laboratories of leading proteomics pioneers, OmicEra Diagnostics has developed a preeminent and ultra-robust platform for mass spectrometry-based proteome analysis of clinical samples on a large scale.

How
we
do it

Building on technology and experience developed in the laboratories of leading proteomics pioneers, OmicEra Diagnostics has developed a preeminent and ultra-robust platform for mass spectrometry-based proteome analysis of clinical samples on a large scale.

Large-scale
cohorts

OmicEra can handle more than 100,000 samples per year with its scalable platform. Founding members of OmicEra such as Dr. Philipp Geyer have pioneered the exploration of the plasma proteome and developed novel biomarker discovery strategies such as the ‘rectangular strategy’. Here, large cohorts of hundreds or thousands of samples are investigated in discovery and validation phases with the same, high proteome coverage. This is facilitated by new technology deployed and developed at OmicEra.

Quality control
from sample to data

To detect and potentially correct for sample collection- or storage-related quality issues, we routinely apply quality marker panels and quality assessments strategies that can correct for biases in plasma samples caused by erythrocyte lysis, platelet recontamination, and partial blood coagulation. Moreover, OmicEra has established standard operation procedures (SOPs), sample tracking strategies, and real-time quality control software to monitor the performance of liquid chromatography and mass spectrometer systems.

Automation

Automation facilitates high-throughput, increases reproducibility and dramatically improves the quality of proteomics data. Therefore, processing steps such as the preparation of clinical samples to peptides and their purification are automated at OmicEra. Furthermore, automation enables sample tracking throughout the pipeline as samples are transformed into proteomics data and actionable knowledge.

Large-scale
cohorts

OmicEra can handle more than 200,000 samples per year with its scalable platform. Founding members of OmicEra such as Dr. Philipp Geyer have pioneered the exploration of the plasma proteome and developed novel biomarker discovery strategies such as the ‘rectangular strategy’. Here, large cohorts of hundreds or thousands of samples are investigated in discovery and validation phases with the same, high proteome coverage. This is facilitated by new technology deployed and developed at OmicEra.

Quality control
from sample to data

To detect and potentially correct for sample collection- or storage-related quality issues, we routinely apply quality marker panels and quality assessments strategies that can correct for biases in plasma samples caused by erythrocyte lysis, platelet recontamination, and partial blood coagulation. Moreover, OmicEra has established standard operation procedures (SOPs), sample tracking strategies, and real-time quality control software to monitor the performance of liquid chromatography and mass spectrometer systems.

Automation

Automation facilitates high-throughput, increases reproducibility and dramatically improves the quality of proteomics data. Therefore, processing steps such as the preparation of clinical samples to peptides and their purification are automated at OmicEra. Furthermore, automation enables sample tracking throughout the pipeline as samples are transformed into proteomics data and actionable knowledge.

Reproducibility

Our proteomics pipeline delivers data with the highest reproducibility. Several peptides are usually quantified per protein and each peptide is quantified several times within an analysis, resulting in highly reproducible data and accurate protein quantification. In contrast to antibodies and other affinity assays, mass spectrometry is deterministic and identifies analytes by their physical properties. Therefore, peptides and proteins are identified with almost 100% specificity.

Strong
tech partners

OmicEra is co-developing new technology to push the boundaries of clinical proteomics. Currently, our tech partners include Bruker Daltonics, a leading mass spectrometer vendor, and Evosep Biosystems, a pioneer in liquid chromatography systems for clinical or translational applications. Through the technology development collaborations with leading instrument vendors like Evosep and Bruker, Omicera has early access to technologies before their general market release.
Moreover, scientists of OmicEra have previously pioneered several technological breakthroughs in proteomics such as sample preparation automation, novel quantification strategies, ultra-deep proteome coverage and new strategies for liquid chromatography.

Strong
clinical partners

OmicEra has excellent on-going co-operations with several hospitals and intends to be at the forefront of proteomics for clinical applications.

Reproducibility

Our proteomics pipeline delivers data with the highest reproducibility. Several peptides are usually quantified per protein and each peptide is quantified several times within an analysis, resulting in highly reproducible data and accurate protein quantification. In contrast to antibodies and other affinity assays, mass spectrometry is deterministic and identifies analytes by their physical properties. Therefore, peptides and proteins are identified with almost 100% specificity.

Strong
tech partners

OmicEra is co-developing new technology to push the boundaries of clinical proteomics. Currently, our tech partners include Bruker Daltonics, a leading mass spectrometer vendor, and Evosep Biosystems, a pioneer in liquid chromatography systems for clinical or translational applications. Through the technology development collaborations with leading instrument vendors like Evosep and Bruker, Omicera has early access to technologies before their general market release.
Moreover, scientists of OmicEra have previously pioneered several technological breakthroughs in proteomics such as sample preparation automation, novel quantification strategies, ultra-deep proteome coverage and new strategies for liquid chromatography.

Strong
clinical partners

OmicEra has excellent on-going co-operations with several hospitals and intends to be at the forefront of proteomics for clinical applications.

Machine Learning

At OmicEra, we develop and contribute to Open Source tools, employing AI on all levels. We discover and validate novel biomarkers by cutting-edge machine learning techniques such as Ensemble Learning to build predictive models for patient stratification or disease course projections. Moreover, we apply machine learning to strengthen technical aspects of our pipeline by predicting peptide retention times, collisional cross-sections or MS/MS spectral intensities of peptides.

Clinical
graph database

Building on recent Open Source developments, OmicEra has adopted a graph database containing a range of clinical studies, which reflects protein perturbations across different health and disease states. This knowledge base is integrated with other biomedical information systems into a graph database to maximize medical and biological insights into the proteomics data.

Open Source and
proprietary software

Software is a main pillar of all of OmicEra’s activities. Headed by Dr. Maximilian Strauss, we build upon and contribute to Open Source efforts for the research community. Additionally, OmicEra develops its own software, which allow us to dynamically adapt to the needs of our biotech and pharma partners and provide both all-in-one and tailored solutions.

Machine Learning

At OmicEra, we develop and contribute to Open Source tools, employing AI on all levels. We discover and validate novel biomarkers by cutting-edge machine learning techniques such as Ensemble Learning to build predictive models for patient stratification or disease course projections. Moreover, we apply machine learning to strengthen technical aspects of our pipeline by predicting peptide retention times, collisional cross-sections or MS/MS spectral intensities of peptides.

Clinical
graph database

Building on recent Open Source developments, OmicEra has adopted a graph database containing a range of clinical studies, which reflects protein perturbations across different health and disease states. This knowledge base is integrated with other biomedical information systems into a graph database to maximize medical and biological insights into the proteomics data.

Open Source and
proprietary software

Software is a main pillar of all of OmicEra’s activities. Headed by Dr. Maximilian Strauss, we build upon and contribute to Open Source efforts for the research community. Additionally, OmicEra develops its own software, which allow us to dynamically adapt to the needs of our biotech and pharma partners and provide both all-in-one and tailored solutions.

You
and
us

Serving a selected group of customers, OmicEra can process large sample numbers and provide deep proteome profiling in both targeted and untargeted analyses. Our clients are mainly pharma/biotech companies and clinical centers but we also often collaborate with academic researchers.

Partner with us

You
and us

Serving a selected group of customers, OmicEra can process large sample numbers and provide deep proteome profiling in both targeted and untargeted analyses. Our clients are mainly pharma/biotech companies and clinical centers but we also often collaborate with academic researchers.

Partner with us