InSyBio

The new version also introduces an enhanced protein analysis module that allows users to retrieve rich structural, sequential, and functional information for any protein, including detailed GO terms, miRNA regulators, and protein interaction partners enriched with a wide range of structural, co-expression, and physicochemical features. These data can be instantly visualized through an upgraded, interactive network interface that supports multiple layouts and downloadable graph formats.

The release features a new generation of computationally predicted protein complexes, developed using an updated EEMC algorithm. These complexes are presented with functional annotations and direct links to visualization, enabling quick identification of biologically meaningful modules.

Functional exploration is further strengthened with a redesigned GO term interface, allowing researchers to examine proteins and complexes associated with any biological process, molecular function, or cellular component. A rebuilt dataset creation module enables users to generate balanced or custom PPI datasets, including optional normalization and iRefIndex-verified interactions, with an option to store them directly within the InSyBio Data Store.

For systems-level analysis, users can now create full biological networks from lists of biomarkers or protein identifiers. These networks can be interactively visualized, explored, and exported in multiple formats, with full compatibility with InSyBio BioNets for further analysis.

With Version 3.4, InSyBio strengthens the field of PPI analysis, protein exploration, and network biology. The updated InSyBio Interact environment brings together high-accuracy PPI prediction, an expanded protein search module, and complex identification. By utilizing InSyBio’s advanced ML capabilities, researchers can move smoothly from examining a single protein’s characteristics to exploring its interaction partners, regulatory molecules, functional roles, and placement within broader biological systems.

InSyBio CEO Labros Digonis stated: “Protein interaction analysis remains fragmented and technically demanding. With Version 3.4, we integrate PPI prediction, protein analysis, complex detection, and interactive network biology into a single, user-friendly platform. Our goal is to empower researchers to extract actionable insights from complex biological data without requiring programming or specialized bioinformatics expertise.”

A detailed description of all new features is available in the InSyBio Interact User Manual v3.4: ( InSyBio Interact – InSyBio )

Researchers may request a free one-month trial of InSyBio Suite, including all new functionalities, by clicking on the following link: (https://suite.insybio.com/)

About InSyBio. InSyBio is an international pioneer biotechnology company revolutionizing the medical field through targeted biomarker discovery, highly accurate predictive analytics, and the development of personalized tests for drugs. Its solutions provide the R&D departments of Pharma and Research Institutes with the means to meet their most challenging research and innovation goals. This is done through a sophisticated, software-as-a-service, machine learning platform that comprehensively integrates multi-omics and clinical data, thus reducing the number of samples and additional validation experiments needed. Since 2013, InSyBio has worked with hundreds of academics, large and small companies, hospitals, and research centers, allowing them to succeed in their biomarker discovery tasks with an increase of at least 10% in predictive accuracy and a decrease of at least 80% in overall time and cost.

A unique Machine-Learning and Molecular Modelling pipeline focusing on the interactome of the Taste Receptors has been released in a new publication from the InSyBio team in collaboration with a team of exceptional researchers from Dalle Molle Institute for Artificial Intelligence (Switzerland), and Politecnico di Torino (Italy) in the framework of VIRTUOUS Project, an EU Horizon 2020 program.

In this study, a Machine-Learning (ML) methodology was developed for predicting binary Protein-Protein Interactions (PPIs) and ranking them based on their computationally predicted affinity. The ML models developed were then applied for resolving the Taste Receptor interactome and detecting the most important interactions of Taste Receptors from the multitude of potential ones. The detected interactions were further characterized through Molecular Dynamics analysis, verifying novel interactions of TAS2R41, such as the TAS2R41-CHMP4A. The classification and regression models applied were based on InSyBio’s multi-objective evolutionary optimization algorithm that is implemented in InSyBio Suite, showcasing the wide range of applications of InSyBio’s biomarker discovery and predictive analytics algorithms and pipelines.

This pipeline aims to facilitate taste perception research for nutrition and pharmaceutical companies and laboratories by filtering and characterizing the most significant Taste Receptor interactions for further studies. The paper was published in the NPJ Science of Food journal of the Springer Nature publishing company (https://rdcu.be/euiWe).

Image: Flowchart of the proposed ML and Molecular Dynamics analysis pipeline applied for the Taste Receptor Interactome.

Labros Digonis, CEO of InSyBio, commented on the importance of the tool:

“We are proud for this unique application of our machine learning and network analytics technology. Resolving the molecular mechanisms of taste is essential for engineering new food products and studying the health implications and downstream effects of different food products. This was an excellent collaborative result of our R&D working together with universities and research institutes in Italy, Greece and Switzerland. Congratulations to the pioneer team!”

About Virtuous: The EU-funded VIRTUOUS project (Marie Skłodowska-Curie Research and Innovation Staff Exchange (RISE) – https://virtuoush2020.com/) is dedicated to the development of a virtual tongue made by an integrated computational framework that can screen food for natural components by binding taste receptors. This international consortium includes eight academic and industry participants from four European countries. Using a variety of computational and experimental data, partners plan to create an algorithm for the prediction of the organoleptic profile of the food based on its chemical composition. The potential application of this platform as a taste predictor is in the food industry, modern precision agriculture, and as a link to neuroscience for taste determination.

About InSyBio: InSyBio is an international pioneer bioinformatics revolutionizing the medical field, clinical trials and food/nutrition industries through targeted biomarker discovery and highly-accurate predictive analytics.

InSyBio solutions provide the R&D departments of Pharma, Research Institutes and Food/Nutrition companies, with the means both analytically and computationally, to meet their challenging research and innovation goals (such as robust biomarker discovery and accurate predictive models). This is done through a sophisticated, software-as-a-service, machine learning platform which comprehensively integrates multi-omics data reducing the number of samples and additional validation experiments needed. Since 2013, InSyBio has worked with hundreds of academics, large and small companies, hospitals and research centers allowing them to succeed in their biomarker discovery tasks with an increase of at least 10% in predictive accuracy and decrease of at least 80% in overall time and cost.

Visit www.insybio.com to see how InSyBio can help you reach your R&D goals in the era of Precision Medicine and Nutrition.

A novel predictor for multiple taste sensations based on a multi-objective Machine Learning method was published by InSyBio in the NPJ Science of Food journal of the Springer Nature publishing company (https://rdcu.be/dOVbA). This new predictor, namely Virtuous Multi-Taste, was developed in collaboration with a team of exceptional researchers from Politecnico di Torino (Italy), Industrial Systems Institute (Greece) and Dalle Molle Institute for Artificial Intelligence (Switzerland) in the framework of VIRTUOUS Project, an EU Horizon 2020 program.

This work provides a valuable tool for predicting the taste of chemical compounds based on their most important physiochemical properties. The tool is designed to analyze different compounds and provide as output the percentage of contribution of four different tastes- sweet, umami, bitter and other- to the overall taste of each query compound. The multi-class predictor was created based on InSyBio’s multi-objective evolutionary optimization algorithm that is implemented in InSyBio Suite, showcasing the wide range of applications of InSyBio’s biomarker discovery and predictive analytic algorithms and pipelines.

The Virtuous Multi-Taste tool will accelerate taste perception research by providing nutrition and pharmaceutical companies and laboratories with a much-needed tool for compound design based on taste. The tool itself can be accessed through a web-based interface: https://virtuous.isi.gr/#/virtuous-multitaste.

Image: (a) The Virtuous Multi-Taste web-based interface and the result of compound search indicating (b) each compound’s structure and (c) the percentage of each taste’s representation in the final compound taste.

The vision of the Virtuous project, as previously stated by Dr. Marco Agostino Deriu, was to “build an intelligent machine able to decrypt a sensation by modelling the biophysical architecture of our body, covering all required competencies for this ambitious challenge, starting from molecular and multiscale modelling techniques, to artificial intelligence algorithms; experimental facilities to analyze natural product typical of the Mediterranean diet such as wine and oil“

Labros Digonis, CEO of InSyBio, commented on the importance of the tool:

“We are proud of acquiring, at last, the ability to predict the taste of chemical compounds based on their physiochemical properties. The potential to revolutionize multiple industries by improving product development processes, enhancing consumer satisfaction and fostering innovation in taste-related research is inherent to this revolutionary discovery and is here to stay. We will be seeing a lot of new, cost-efficient, more targeted and senses-satisfying products based on this. Congratulations to the pioneer team!”

About Virtuous: The EU-funded VIRTUOUS project (Marie Skłodowska-Curie Research and Innovation Staff Exchange (RISE) – https://virtuoush2020.com/) is dedicated to the development of a virtual tongue made by an integrated computational framework that can screen food for natural components by binding taste receptors. This international consortium includes eight academic and industry participants from four European countries. Using a variety of computational and experimental data, partners plan to create an algorithm for the prediction of the organoleptic profile of the food based on its chemical composition. The potential application of this platform as a taste predictor is in the food industry, modern precision agriculture, and as a link to neuroscience for taste determination.

About InSyBio: InSyBio is an international pioneer bioinformatics revolutionizing the medical field, clinical trials and food/nutrition industries through targeted biomarker discovery and highly-accurate predictive analytics.

InSyBio solutions provide the R&D departments of Pharma, Research Institutes and Food/Nutrition companies, with the means both analytically and computationally, to meet their challenging research and innovation goals (such as robust biomarker discovery and accurate predictive models). This is done through a sophisticated, software-as-a-service, machine learning platform which comprehensively integrates multi-omics data reducing the number of samples and additional validation experiments needed. Since 2013, InSyBio has worked with hundreds of academics, large and small companies, hospitals and research centers allowing them to succeed in their biomarker discovery tasks with an increase of at least 10% in predictive accuracy and decrease of at least 80% in overall time and cost.

Cardiovascular diseases (CVDs) are the leading cause of death globally, with 17.9 million annual deaths. InSyBio has partnered with Syndesis, the data and technology catalyst to a truly global, multi-continent network of healthcare and life sciences organizations, to address this enormous global health issue.

We focused on two specific heart diseases, congestive heart failure (CHF) and hypertrophic cardiomyopathy (HCM). Congestive heart failure (CHF), or heart failure, is a long-term condition characterized by the inability of the myocardium to meet the body’s blood supply needs. Hypertrophic cardiomyopathy (HCM) is a genetic heart muscle disease that causes alterations in heart’s structure. It is associated with high mortality due to sudden cardiac arrest and frequently requires heart transplant. When faced with patients suffering from CHF or HCM, doctors are often challenged in ensuring the optimal therapeutic protocol that reduces the risk of dangerous complications or death.

Existing clinical scores (Qrisk2, SCORE, Framingham) perform poorly in predicting 5-year mortality and short-term outcome (<60% Area Under the Curve, AUC) in both disease areas. Artificial Intelligence can provide significant support in such clinical decisions, by predicting outcomes for patients based on certain therapeutic protocols.

PrecisionCHF and PrecisionHCM

InSyBio analyzed a highly curated cardiovascular data set using Syntium, Syndesis Health’s data platform of anonymized clinical data, in order to develop two Precision Medicine Tools based on Artificial Intelligence. These tools predict CHF and HCM risk and can help to reduce it by recommending changes to the therapeutic protocol of the patients suffering from these diseases.

The AI tools – “PrecisionCHF” and “PrecisionHCM” – were trained on data from 1044 patients hospitalized with Congestive Heart Failure (CHF) and 255 Hypertrophic cardiomyopathy (HCM) patients with full clinical annotation and outcomes mined from Syntium.

Following training on the data, the AI tools performed impressively well: PrecisionCHF was able to predict 5-year mortality for CHF with 75% AUC, while PrecisionHCM was able to predict short term outcome (i.e. mortality until discharge) with 97% AUC. Using the AI tools 37% of CHF and 28% of HCM patients at risk can substantially reduce their risk (>5% reduction) with the optimization of their medication plan. Moreover, 12% of the rest of CHF and 11% of the rest of HCM who are not at risk can further reduce their risk by at least 5%.

The collaboration between InSyBio and Syndesis has demonstrated the enormous value of training AI pipelines for medical applications using relatively “small” but highly curated and validated clinical data, and the importance of innovative platforms such as InSyBio Diagnostics Platform and Syntium.

These tools can be accessed via the newly launched InSyBio Diagnostics Platform: https://diagnostics.insybio.com

About InSyBio. InSyBio is an international pioneer biotechnology company revolutionizing the medical field through targeted biomarker discovery, highly accurate predictive analytics and the development of personalization tests for drugs. Its solutions provide the R&D departments of Pharma and Research Institutes with the means to meet their most challenging research and innovation goals. This is done through a sophisticated, software-as-a-service, machine learning platform which comprehensively integrates multi-omics and clinical data, thus reducing the number of samples and additional validation experiments needed. Since 2013, InSyBio has worked with hundreds of academics, large and small companies, hospitals, and research centres allowing them to succeed in their biomarker discovery tasks with an increase of at least 10% in predictive accuracy and a decrease of at least 80% in overall time and cost.

Single-cell RNA sequencing is a powerful genomic method used to detect and analyze RNA molecules in biological samples at a single-cell level. It has proven successful in studying cell composition, proliferation, and migration. However, analyzing the data presents challenges due to standardization issues, data scarcity, and difficulties in integrating datasets with other sequencing technologies.

The new version of InSyBio Suite introduces new functionalities and toolboxes within the InSyBio ncRNAseq tool for streamlining and optimizing the processing of single-cell RNA-sequencing data and performing all required analyses to facilitate the discovery of biomarkers, cell trajectories, cell-cell communication patterns overcoming the challenges of existing workflows and tools.

In particular, the following functionalities are enabled/supported in the new version of InSyBio ncRNAseq tool:

• optimized analysis from raw data simplifying the process and ability to be run by non-bioinformatics experts.
• Efficient integration of multiple scRNAseq datasets, removing efficiently the technical biases and maintaining biological variability.
• Cell-deconvolution of bulk transcriptomics and proteomics data using scRNAseq data.
• Discovery and documentation of cell-cell communication patterns using CellChat workflow.
• Discovery of single-cell trajectories and RNA-velocity patterns using scVelo workflow
• Custom figure preparation and documented bioinformatics analysis integrated with additional tools of InSyBio Suite for biomarker discovery, network and AI/ML analysis.

The CEO of InSyBio, Labros Digonis, stated: “In the past 5 years, scRNAseq data have been extensively used in the literature but their analysis is difficult, demanding and it is very easy to get misleading results if not conducted by a coding and bioinformatics expert. In line with our company’s priorities, the new version of InSyBio Suite democratizes the use of such data by non-bioinformatics experts allowing the people who generate the data to perform elaborate analytics and get the most out of their data using our user-friendly, web-based platform.”

Read more details about this tool in the updated InSyBio ncRNAseq’s user manual: InSyBio-ncRNASeq-Manual-v3.2.

InSyBio is offering a one-month free license to use InSyBio Suite including the new version of InSyBio ncRNAseq tool. Request your free trial now by completing a simple form at: Get a free one month license of InSyBio Suite.

About InSyBio. InSyBio is an international pioneer biotechnology company revolutionizing the medical field through targeted biomarker discovery, highly accurate predictive analytics and the development of personalization tests for drugs. Its solutions provide the R&D departments of Pharma and Research Institutes with the means to meet their most challenging research and innovation goals. This is done through a sophisticated, software-as-a-service, machine learning platform which comprehensively integrates multi-omics and clinical data, thus reducing the number of samples and additional validation experiments needed. Since 2013, InSyBio has worked with hundreds of academics, large and small companies, hospitals, and research centres allowing them to succeed in their biomarker discovery tasks with an increase of at least 10% in predictive accuracy and a decrease of at least 80% in overall time and cost.

Barcelona, October 25^th, 2023: CPHI Barcelona announced the winners of the prestigious 2023 CPHI Pharma Awards. The awards recognise outstanding achievements and contributions from the global pharma industry and supply chain across 12 wide-ranging categories. InSyBio won the best Start-Up Initiative in Pharma for 2023.

CPHI is the biggest worldwide exhibition and event for the Pharma Industry and is organised annually. The CPHI Pharma Awards recognise progress and innovation across the pharma supply chain. The details about the CPHI awards and the awarded companies can be found at CPHI Awards.

In the CPHI awards 2023 press release (https://www.pharmiweb.com/press-release/2023-10-26/cphi-pharma-award-winners-2023), it is mentioned that: “InSyBio impressed the judges reviewing the brand-new Start-Up Initiative category for its ability to revolutionize the medical field, clinical trials and food/nutrition industries through its targeted biomarker discovery. They have developed highly accurate predictive analytics enabling personalization of tests for drugs, nutraceuticals and nutrition products. Its solutions provide the R&D departments of Pharma, Research Institutes and Food/Nutrition companies with the means both analytically and computationally to meet their challenging research and innovation goals.”

Our CEO, Labros Digonis who received the award stated: “This award is a recognition of the hard work of our team in the past years to develop and commercialize a biomedical data analysis platform that could really expedite and speed up research in Pharma and Nutrition and eventually save lives. The CPHI event through the award as well as through our presence and exhibition in the start-up market, gave us the opportunity to connect with many pharma and nutraceutical product companies. We are looking forward to forming strong alliances that will lead to the development of personalized medicine and nutrition solutions”.

About InSyBio. InSyBio is an international pioneer biotechnology company revolutionizing the medical field through targeted biomarker discovery, highly accurate predictive analytics and the development of personalization tests for drugs. Its solutions provide the R&D departments of Pharma and Research Institutes with the means to meet their most challenging research and innovation goals. This is done through a sophisticated, software-as-a-service, machine learning platform which comprehensively integrates multi-omics and clinical data, thus reducing the number of samples and additional validation experiments needed. Since 2013, InSyBio has worked with hundreds of academics, large and small companies, hospitals, and research centres allowing them to succeed in their biomarker discovery tasks with an increase of at least 10% in predictive accuracy and a decrease of at least 80% in overall time and cost.

InSyBio, a leading biotechnology company that has developed a suite of advanced AI tools for biomarker discovery in clinical and multi-omics data, has announced a strategic partnership with Syndesis Health, a leader in global real-world evidence. The partnership aims to leverage the clinical and genomic data on Syntium, Syndesis’ data platform of global healthcare data, to accelerate research and development in several therapeutic areas, including cardiovascular health, oncology, and rare diseases.

The importance of biomarkers

Biomarkers are body characteristics that can be measured, such as the biological molecules found in bodily fluids or tissues, including DNA, antibodies, proteins, or other smaller molecules. They are necessary to predict the effectiveness of drugs and patient outcomes; however, biomarker discovery is a very complex and costly process that often results in poor or inaccurate outcomes due to the use of disparate tools and datasets, and the high complexity of high-throughput -omics data.

InSyBio’s platform simplifies and accelerates the process of biomarker discovery by providing a single, highly accurate, and effective processing pipeline that uses machine learning to analyze biodata. Syntium’s longitudinal datasets, which include clinical, genomic, and other data, are ideal for applying InSyBio’s suite of tools in biomarker discovery. Combining Syntium data with InSyBio’s platform will create a unique opportunity for biopharma and diagnostic companies to uncover breakthrough discoveries with the potential to vastly improve global patient outcomes.

“Precision medicine is still in its infancy and many patients are misdiagnosed or do not get the most beneficial treatment for them. The wealth of Syntium’s data sets when harnessed by our automatic AI-driven technology holds the potential to upend the medical field practices, and highly impact overall healthcare quality at national and international levels. We are looking forward to working with the innovative team of Syndesis Health“, said Labros Digonis, InSyBio CEO.

“We are incredibly excited to embark on this partnership with InSyBio to enable biomarker discovery for cutting-edge healthcare innovation”, said Josh Sutton, Syndesis Health CEO. “Together we seek to raise the bar for global health research and innovation in service of patients worldwide.”

About Syndesis Health. Syndesis Health is the data and technology catalyst to a multi-continent network of healthcare and life sciences organizations. Its primary aim is to enhance global health outcomes and equity through its secure data platform, Syntium, and the Syndesis Health Network, a member community promoting research collaboration, information sharing, and access to common tools. Visit https://syndesis.com to learn more.

About InSyBio. InSyBio is an international pioneer biotechnology company revolutionizing the medical field through targeted biomarker discovery, highly accurate predictive analytics and the development of personalization tests for drugs. Its solutions provide the R&D departments of Pharma and Research Institutes with the means to meet their most challenging research and innovation goals. This is done through a sophisticated, software-as-a-service, machine learning platform which comprehensively integrates multi-omics and clinical data, thus reducing the number of samples and additional validation experiments needed. Since 2013, InSyBio has worked with hundreds of academics, large and small companies, hospitals, and research centres allowing them to succeed in their biomarker discovery tasks with an increase of at least 10% in predictive accuracy and a decrease of at least 80% in overall time and cost. Visit http://www.insybio.com for more information.