Projects Archive - BioVariance - data-driven diagnostics

BioVariance is a partner in the EU-funded project “BEATsep”, which aims to combat the long-term effects of sepsis.

Sandra Bayreuther — Thu, 14 Sep 2023 08:35:07 +0000

The research consortium BEATsep, established by the Cellular and Molecular Immunoregulation (CMI) research team at the International Clinical Research Centre (ICRC) at St. Anne’s University Hospital (FNUSA) Brno (Czech Republic), has been awarded a 6.9 million euro HORIZON EUROPE grant. The project entitled “Biomarkers established to stratify sepsis long-term adverse effects to improve patients’ health and quality of life (BEATsep) aims to define markers of poor recovery of patients after sepsis and septic shock. This will be achieved through the discovery of novel mechanisms and their markers predicting the decline of health-related quality of life after sepsis. Sepsis and septic shock, affecting up to 50 million people worldwide with mortality reaching 20%, leaves large cohorts of vulnerable patients suffering from long-term complications that affect their quality of life.

The BEATsep project will apply an interdisciplinary approach bringing together research and clinical teams working on specific aspects of the development, treatment and prevention of the long-term consequences of sepsis and its impact on patients’ quality of life. Comprehensive clinical and research data generated during the project will be integrated using artificial intelligence algorithms into an easy-to-use predictive tool capable of identifying patients at high risk of complications. BioVariance GmbH is involved here in the development of algorithms that link these collected data. Furthermore, the consortium plans to design a tertiary prevention strategy to improve the recovery outcomes.

For the next five years, the consortium brings six European countries together in a joint mission to understand and fight the long consequences of sepsis.

The consortium is coordinated by ICRC-FNUSA and will consist of leading European institutions including: 1) CIML – Centre d’immunologie de Marseille-Luminy – (Aix-Marseille Université/CNRS/Inserm); 2) Institute of Innate Immunity, at the Medical Faculty of the University of Bonn, Germany; 3) Faculty of Medicine at the Comenius University in Slovakia; 4) Ludwig Boltzmann Institute for Traumatology, Vienna, Austria; 5) BioVariance GmbH, Germany; 6) Masaryk University, Brno, Czechia; 7) National Institute of Health, Prague, Czechia; 8) University of Galway and 9) APHM – Marseille Hospitals. BEATsep assembles renowned experts in immuno-metabolism and epigenetics, immunophenotyping, diagnostic research and several clinical teams treating adult and pediatric sepsis patients. “It has taken nearly two years of intensive preparation and networking to assemble the consortium. We used the advantage of bringing together teams with whom we have been already collaborating on several other projects.” says Dr. Marcela Hortová-Kohoutková from the CMI research group, who co-headed the project’s preparation.

In total, 9 partners from renowned European research and clinical institutions and 1 commercial partner in six EU countries will be involved in the BEATsep. “The project is an example of an innovative and successful combination of translational and clinical research, the know-how of several international scientists, and the collaboration between hospitals, universities and other scientific institutions.

For more information and updates:

www.beatsepsis.eu

https://shorturl.at/isRZ9 (LinkedIN)

Der Beitrag BioVariance is a partner in the EU-funded project “BEATsep”, which aims to combat the long-term effects of sepsis. erschien zuerst auf BioVariance - data-driven diagnostics.

Antibody study gives way to the telomere length study

Sandra Bayreuther — Tue, 27 Jun 2023 08:33:55 +0000

We would like to take this opportunity to thank the volunteers for their willingness to support Ms. Schraml in her doctoral thesis.

Due to known difficulties and the long outdated topic, the antibody study will not take place as planned. We apologize for this and would be pleased if Ms. Schraml and BioVariance would nevertheless continue to support and participate in our first study on telomere length determination, which can be used to determine a person’s biological age.

Telomere length determination is a fascinating field of research that gives us information about the condition and health of our cells. Telomeres are the protective caps at the ends of our chromosomes that are associated with the aging process. By analyzing telomere lengths, our team can gain important insights into the biological aging process and thus determine biological age. With this telomere length determination study, we are once again setting the standard in medical research and reaffirming our position as a pioneer in the field of biomedical innovation.

To further this important research, we are seeking volunteers of either gender, 18 years of age or older, who are willing to have a sample of their oral mucosa taken with a simple cheek swab. This can be done on-site at our facility or at your home, using a so-called test kit (similar to a rapid PCR test), which we will send to you by mail.

The telomere length determination study will take place in July and offers you the opportunity to participate in groundbreaking research. Interested individuals are welcome to call 09631 / 30 89 200 or email studie@biovariance.com, stating your address, gender and age, for more information and to register to participate.

The results of this research could lead to new insights into the aging process and form the basis for future medical advances.

Der Beitrag Antibody study gives way to the telomere length study erschien zuerst auf BioVariance - data-driven diagnostics.

New Categorization of a Cancer Indication

Marco Vollath — Mon, 19 Oct 2020 05:47:12 +0000

The Goal – Advance Personalized Medicine

BioVariance GmbH focuses together with a global player from the pharmaceutical industry on advancing research in personalized medicine. Due to the outstanding cooperation and the excellent expertise of both partners, a new categorization of tumor indications will be available for the pharma and healthcare sector. The new categorization based on the individual characteristics of the tumor tissue shall provide a deeper understanding of disease mechanisms and further allow a more individual diagnosis and a more targeted and personalized therapy for affected patients prospectively.

Challenges

The rapid development of technologies for the biomedical and pharmaceutical research enable the generation of complex interdisciplinary data sets. Within the scope of this project, next-generation sequencing (NGS) and innovative optical measurement techniques were applied to characterize tissue sections to newly categorize the tumor indication of interest. Due to our broad expertise in Big Data related challenges, such as data processing, exploratory statistics and machine learning, the BioVariance GmbH was assigned to perform preprocessing of the datasets and to develop and evaluate the clustering models. To make both NGS and tissue characteristics data sets comparable and to correct for a possible bias caused by the new optical measurement technique, normalization of each data set was mandatory. The challenge was to find an appropriate normalization strategy that fulfilled both requirements. In addition, normalization should not produce spurious correlations within the data. Therefore, several normalization strategies were selected and tested. To ensure the absence of spurious correlation within the normalized data, the coefficient of variation ^[1] and partial correlations were determined. Finally, the best normalization strategy was chosen taking all three criteria (comparability of data, correction of bias, absence of spurious correlation) into account. Thus, the data scientists ensured, that the linear correlations between two variables of the data set (visualized by the scatterplot matrix) were not due to spurious correlations. The scatterplot matrix, however, did not show any clusters in the pairwise comparison of variables (in contrast to the scatterplot matrix from test data presented in Fig. 1). Consequently, the next step comprised a principal component analysis (PCA). For this purpose, the normalized tissue characteristics required a Box-Cox transformation, since none of these variables followed a normal distribution.

Fig. 1. Scatterplot matrix reveals linear correlations and clusters in a test data set

The road to success

Within the scope of this project, the team of data analysts at the BioVariance GmbH relied on descriptive statistics including state-of-the-art algorithms and exploratory data analysis to uncover differences, correlations and clusters in the data.

No clusters were observable in the scatterplot matrices. Consequently, a PCA was enriched by the Marchenko-Pastur distribution to find the discriminating factors. PCA reduces the number of variables in a data set by searching linear combinations, that describe the highest degree of variance – the so-called principal components (PCs). These PCs are the new variables that have the potential to visualize inherent clusters. The first PC describes the largest ratio of variance in the data, the second PC the second largest, etc. They construct an orthogonal coordinate system, of which the axes point into the direction of highest variance. Plotting the first two or three PCs is often sufficient to visualize clusters.^[2] By means of the Marchenko-Pastur distribution the number of PCs carrying discriminating information was determined.^[3] In this case, the first PC was identified as the only significant factor.

To confirm the visual result from the PCA, several clustering algorithms (hierarchical clustering using Manhattan distance, k-Means and PAM algorithms as well as dbscan) were

performed. Applying two parameters (e.g. the so-called silhouette-width) that describe the quality of cluster assignment for each patient, the most differentiated clusters were identified.

These newly discovered groups could be visualized and reinsured by labeling them in the PCA-Biplot (see Fig.2).

Fig. 2. Group labeled PCA Biplot of an example dataset

An established categorization which is based only on gene expression was compared to the new categorization. The results of this comparison were visualized by a heatmap representation. The two categorizations could be clearly distinguished from each other. In this study, the gene expression data of the tumors were applied additionally to identify biochemical processes responsible for the tissue characteristics.

The results from this successful cooperation were published in a high impact cancer research journal. They will strongly support the development of personalized therapy strategies.

If you are interested in a targeted extraction of information from your data set, too, then do not hesitate to contact us and request support of our experts.

Contact Person

Helen Schneider | Sales and Distribution

helen.schneider@biovariance.com

Sources

Der Beitrag New Categorization of a Cancer Indication erschien zuerst auf BioVariance - data-driven diagnostics.

Effective Data Processing with BioCore Studio

Marco Vollath — Thu, 23 Jul 2020 07:10:55 +0000

Due to the rapid development of bioanalytical high-throughput technologies, such as NGS or HPLC/UPLC-MS, it became easy to generate complex data in record time. To answer research questions adequately, it is of utmost importance to successfully uncover hidden patterns and correlations in these data sets. Thus, the challenge in science today is mostly not the generation of sufficient data sets but their bioinformatic analysis. Consequently, it is time to provide a platform that allows to manage and analyze Big Data efficiently. Therefore, BioVariance GmbH developed BioCore Studio.

What is BioCore Studio?

BioCore Studio is a web-based software for the assembly, automation and parallelization of data analysis workflows, so-called pipelines (see Fig. 1). It was built to assist in computation-intensive biomedical research.

Fig. 1: Automation and Parallelization of Analysis Pipelines with BioCore Studio

The platform comprises tool packages that enable the user to intuitively design tailored analysis pipelines by drag and drop. There is no programming knowledge required. Additionally, BioCore Studio is suitable for all data types.

Visualization of the process in real time and insights into results and output of each step guarantee a transparent workflow. Regularly occurring tasks can be scheduled or started immediately. Due to its innovative parallelization and automatization technologies BioCore Studio enables time and cost savings as well as an optimal utilization of technical resources.

BioCore Studio is flexibly scalable in terms of computing power and adapts to individual needs. Huge amounts of data can be processed quickly and safely. Thanks to the Kubernetes cluster, available computing capacities are used efficiently.

The Product in Action

The BioVariance GmbH employs BioCore Studio to analyze high-throughput NGS data for its clients in the pharmaceutical and medical industry (see Fig. 2). For this purpose, ready-to-use pipelines are implemented. These are continuously expanded and optimized by the BioVariance GmbH with regards to new biomedical trends.

Fig. 2: Discovering Complex Patterns in Genomic Data with BioCore Studio

Benefits with BioCore Studio

State-of-the-art parallelization and automation technologies (i.e. Kubernetes, Docker)
Fast Processing of Big Data
User-friendly, intuitive interface
No programming required
Applicable for all data types without conversion
Transparent process tracking
Scalability of computing capacity
Ready-to-go-Pipelines
Implementation of Tailored Tools possible

BioCore Studio makes state-of-the-art computation technologies effectively usable for scientists.

Contact Person

Helen Riessbeck | Sales and Distribution

helen.riessbeck@biovariance.com

Der Beitrag Effective Data Processing with BioCore Studio erschien zuerst auf BioVariance - data-driven diagnostics.

Validation of PCR oligos for SARS-CoV-2 test

Marco Vollath — Tue, 07 Jul 2020 05:00:51 +0000

The global SARS-CoV-2 pandemic is an emerging, rapidly evolving situation. Therefore, increasing the test capacity to detect a virus infection is of utmost importance. BioVariance GmbH helped to fortify the regulatory submission proposal of a globally acting in-vitro diagnostics company, to receive FDA (Food and Drug Administration) approval for a novel and rapid COVID-19 PCR test. This was achieved in record time by employing computer aided (in-silico) validation methods, and the dedication of our team of Data Specialists. Within the scope of this project, two main objectives were confirmed:

Primer and Probe Sensitivity

To confirm primer and probe sensitivity, alignments of the oligonucleotide sequences and all publicly available SARS-CoV-2 sequences were performed. Hits were prioritized by scoring criteria such as e-value, and mismatches were assessed and evaluated. Furthermore, the hits were further filtered for a potential formation of PCR products.

Fig. 1: Alignment of SARS-CoV-2 sequences

Cross-reactivity prediction

To predict potential cross-reactivity of the oligonucleotides, sequence homologies with the human genome, other coronaviruses and respiratory related pathogens were detected. This step was essential for ruling out false positive PCR results.

Fig. 2: Decision workflow to evaluate the sequence homologies.

Customer Value

Demonstration of analytical specificity and exclusivity of the oligonucleotides
Fortification of regulatory submission proposals
Reduced wet lab work time and resources
Detection of mutations such as Single Nucleotide Polymorphisms (SNPs)
Detailed report of scientific quality including compelling figures

Please do not hesitate to contact us if you are interested or have any further questions.

Contact Person
Helen Riessbeck | Sales and Distribution
helen.riessbeck@biovariance.com

Der Beitrag Validation of PCR oligos for SARS-CoV-2 test erschien zuerst auf BioVariance - data-driven diagnostics.