MemVerge Memory Machine Takes Best of Show Award in Berlin
By Bio-IT World Staff
October 20, 2022 | BERLIN—Bio-IT World has announced the winner of the first Bio-IT World Europe Best of Show Awards. Among finalists from Dassault Systèmes BIOVIA, Evotec, The Hyve, Ontoforce, and Quilt Data, MemVerge was named the Best of Show People’s Choice winner.
The Best of Show Awards at Bio-IT World events offer exhibitors exclusive opportunities to distinguish and highlight new products. All of the finalists solutions were on display in the Exhibit Hall, and the more than 300 attendees voted on the products they were most excited about.
MemVerge’s Memory Machine Cloud Edition is Linux-based memory virtualization software that allows genomic researchers to provision large pools of software-defined memory without modifying their app. The company highlighted three new capabilities: a new System and Cloud Orchestration Service which makes it possible for Memory Machine to mitigate the impact of Spot terminations, a new class of snapshot called an AppCapsule that captures the entire application state which enables app mobility at the speed of memory, and an updated Memory Tiering Service with support for CXL memory.
MemVerge’s Memory Machine Cloud Edition was also honored by the community last April at the Bio-IT World Conference & Expo in Boston.
The other finalists included:
Dassault Systèmes BIOVIA, BIOVIA Generative Therapeutics Design
BIOVIA Generative Therapeutics Design (GTD) is an artificial intelligence (AI) solution that automates the virtual creation, testing and selection of novel small molecules to reduce expensive real-world testing and accelerate the discovery phase. It is a cloud-based solution built on the collaborative 3DEXPERIENCE platform of Dassault Systèmes, which supports the end-to-end process for lead identification and optimization. GTD combines proven technologies that BIOVIA pioneered in its Pipeline Pilot and Discovery Studio product lines. A structure generation engine uses both proprietary and pre-competitive data sources for identifying favored chemical substructures for particular target families or desirable ADME characteristics. The virtual compounds generated are evaluated with a combination of physics-based (generally 3D) modeling methods and knowledge-based (2D) machine learning methods. Accurate, but traditionally CPU-intensive methods such as molecular docking are executed in a highly scalable cloud architecture. A robust multi-objective optimization procedure is used to balance these design criteria that are often competing. Fast design cycles are critical to speed up to Active Learning (AL) process. The best compounds suggested in this virtual design cycle are analyzed and prioritized based on practical considerations specified by the chemist. Integrated Electronic Lab Notebook capabilities allow for managing the rapid synthesis and testing of proposed virtual compounds. GTD has an open architecture as it allows for the incorporation of third party or in house algorithms and models hosted in other clouds or on premise environments. The 3DEXPERIENCE platform meets the highest industry security standards to ensure customer data is protected.
Dassault Systèmes BIOVIA, BIOVIA Discovery Studio & GOLD on the Cloud
CCDC’s GOLD protein-ligand docking software identifies the binding modes of active molecules—supporting the life sciences industry with proven success in virtual screening and lead optimization. GOLD supports single, detailed, high-accuracy, and virtual compound library docking into the binding site of target proteins. It then ranks and prioritizes the compounds by their likelihood of binding. GOLD is highly regarded within the molecular modeling community for its accuracy, reliability, flexibility, and configurability. By integrating GOLD with BIOVIA’s industry-leading Therapeutics Design software, we are now providing a complete portfolio of therapeutics modeling technology on the 3DEXPERIENCE platform.
Evotec SE, EVOpanHunter
With our SaaS product EVOpanHunter, we are addressing the challenges of combining, visualizing, and analysing large omics datasets. This is particularly relevant as academia and industry shift to various omics technologies for unbiased, in-depth measurement of cellular processes to gain new insights into disease signatures and mechanisms of action. The diversity of data types and sources presents a first challenge in combining and linking these data sets. A second challenge is to extract concise insights and lead the researching disease expert directly to the most interesting disease patterns and interactions. To this end, EVOpanHunter provides an interactive, unified, and intuitive platform. Through the modular web interface, a researcher can easily advance from a high-level overview of a disease's drive patterns to detailed comparisons of pathway regulations, interaction networks, and a wealth of detailed views. Overall, our system significantly increases the efficiency of researchers exposed to any multi omics technologies.
The Hyve, Fairspace 0.7.25
Fairspace is a data repository that enables researchers to securely store and organize their research data sets and share the data with collaborators. Fairspace lets researchers annotate their data collections with relevant metadata properties and link the data to associated metadata entities (subjects, samples, projects, etc.). Faceted search provides summaries of the available data and enables easy and fast filtering based on a selection of relevant properties. This helps researchers find their own data and make it findable for others, contributing to implementation of the FAIR principles. Fairspace ensures that all metadata entities have a unique identifier and checks metadata consistency and validity upon data entry. Fairspace allows organisations to customize the configured data model, by specifying custom entity types and constraints. This enables the adoption of community standards for metadata relevant for the research domain, which contributes to the reusability of the data. Fairspace uses the Resource Description Framework and WebDAV standards for data exchange and stimulates the use of standard vocabularies, contributing to the interoperability of data.
Ontoforce, DISQOVER, 6.60.0
DISQOVER is an award-winning knowledge discovery platform for life science & healthcare to enable smarter data-driven decisions. The data ingestion engine transparently merges and links your siloed data sources, including third-party and public data sources. DISQOVER helps scientists to answer complex questions concerning your research in one platform. Uncovering new insights from data at scale is a core objective of DISQOVER. It solves complex use cases over a multitude of heterogeneous data sources with our simple, intuitive, and customizable dashboards. At any time, the knowledge graph allows you to follow links to additional, related information for a result set revealed by your search. DISQOVER filters results in real-time and visualizes the data using responsive and interconnected charts. Find the most relevant data faster, smarter, and simpler. With DISQOVER, you can provide context to a text search, narrow down your search results with dynamic filters, and leverage the power of linked data across different data sources to gain new insights.
Quilt Data, Quilt SDMS
Quilt is an AWS-native data platform that helps biopharma companies bring therapies to market faster by making their data findable, accessible, interoperable, and reusable (FAIR). Quilt integrates instrument data, metadata, analysis, and visualizations into reusable datasets that can be linked to ELN and leveraged throughout the organization. Quilt runs in customers' AWS accounts and includes an easy-to-use web catalog, a Python API, and backend services that manage users and access control. Quilt connects to customers' SSO providers and builds on their existing security and auditing mechanisms in AWS. Quilt follows AWS best-practice architecture and security principles and can be run in highly secure and compliant environments, including GxP and HIPAA.