Bio-IT World Judges, Community Honor Six Outstanding New Products
By Bio-IT World Staff
May 5, 2022 | Bio-IT World announced Best of Show awards yesterday evening at the Bio-IT World Conference and Expo. The new products awards program, which has not been held since 2019, recognizes innovative solutions to important problems facing the life sciences industry. The awards program is open to any Bio-IT World exhibitor with a new product released in the past year.
The judges named six award winners and the Bio-IT World community chose a People’s Choice Award.
The People’s Choice Award welcomes all attendees to vote on new products on display at the event. This year 27 new products were entered for consideration for the People’s Choice Award, and the winner of the 2022 Best of Show People’s Choice Award in MemVerge for Memory Machine.
In addition to the People’s Choice Award, the Best of Show judges chose to honor six new products. They chose products they believe solve important problems in the life sciences, present novel solutions, and have demonstrated ROI. Not constrained by categories, the judges are free to highlight any product they feel meets those criteria.
The judges chose to honor CellPort Cell Culture Suite, Cerebras CS-2 Artificial Intelligence System, Mastermind Disease-Specific Curated Content from Genomenon, Modak Nabu 2.5, CENtree 2.1 from SciBite, and—echoing the vote of confidence from the Bio-IT World community—Memory Machine from MemVerge.
Details about the winning entries are below in alphabetical order by company.
Product Name: CellPort Cell Culture Suite
Commercially launched in Q3 2021, the CellPort Cell Culture Suite is a low code, domain-agnostic Software-as-a-Service product uniquely focused on cells, including cell culture, cell manufacturing, and cell banking as well as related upstream and downstream data and processes. The role-based system includes modules for inventory management, equipment management, reagent management, cell management, protocol/SOP management, and user management. The product combines the end-to-end laboratory inventory and process management of a Laboratory Information Management System (LIMS) with the highly repeatable QC and manufacturing focus of a Laboratory Execution System (LES). Built upon the Microsoft Azure cloud computing platform, it contains validated, highly configurable browser-based applications for common cell manufacturing operations using a multi-tenant cloud model for scalability across global laboratory locations. The product includes three key features that allow it to be quickly configured to meet each customer’s specific needs: (1) Configurable Object Models that allow the out-of-the-box data definitions to be precisely mapped to a customer’s vocabulary and data standards, (2) Configurable Data Entry/Display Forms that allow the out-of-the-box forms and reports to be adapted to each organization’s needs, and (3) Configurable Workflows that allow SOPs and protocols to be digitalized according to the organization’s best practices and ensure that they are followed. The validated system is 21 CFR 11 / Annex 11 compliant and includes a full audit trail for complete traceability and transparency.
Product Name: Cerebras CS-2 Artificial Intelligence System (second-generation)
Cerebras’ CS-2 Artificial Intelligence System is the world’s fastest AI supercomputer. With every component optimized for AI work, the CS-2 delivers more compute performance at less space and less power than any other system. The CS-2 more than doubles all of the performance characteristics of Cerebras’ CS-1, including the transistor count, core count, memory, memory bandwidth, and fabric bandwidth. The second-generation Wafer Scale Engine processor (WSE-2) boasts 2.6 trillion transistors and 850,000 AI optimized cores, which is 123x more cores and 1,000x the performance on-chip high memory than GPU competitors. Accelerating training by 1000X requires a fundamental rethinking of not only the processor, but all aspects of the system design. This includes the compute core, memory architecture, communication fabric, Input/Output subsystem, power and cooling, system architecture, compiler, and the software tool chain – and this is just to name but a few of the elements that need to be optimized and tuned for performance gains that measure in orders of magnitude. Cerebras undertook all of these challenges in the development of their CS-1 & CS-2 AI systems. Finally, to have maximum impact on the industry, extraordinary performance must be coupled with ease of use. And this is where the Cerebras Software Platform rises to the fore. It has been co-designed with the WSE and allows researchers to take full advantage of all 850,000 cores while using industry-standard machine learning (ML) frameworks like TensorFlow and PyTorch. This produces extraordinary performance without requiring any changes to the user’s workflow.
Product Name: Mastermind Disease-Specific Curated Content
Mastermind Disease-Specific Curated Content (DSCC) is a new and novel capability that solves the challenges described above by providing access to provisional pathogenicity calls and evidence for variant interpretation that is initially gathered through AI-based techniques to ensure maximal completeness of the data, and then manually reviewed by expert variant scientists to ensure the utmost accuracy of the final determinations. When users of Genomenon’s Mastermind Genomic Search Engine search a variant for which there is curated content, DSCC presents them with a notification ribbon across the top of the screen. Users see a provisional pathogenicity call (based on ACMG criteria), along with a link to a trusted source for additional information about the disease. From there, they will be prompted to explore further with the option to “View Interpretation,” which opens detailed variant data in a new window, including ClinGen classification, population data, ACMG calls with relevant literature citations, in silico prediction models, and data intrinsic to the gene. For ease in reporting, these results can be copied, exported, and/or printed by selecting the “Export to Report” button on the bottom left of the detail page. We predict that access to this evidence will increase clinical diagnostic rates, and further, notification of clinical trials and available therapies will increase clinician awareness of disease and appropriate treatment of patients.
Product Name: MemVerge Memory Machine
MemVerge Memory Machine is the first in a new class of Big Memory Software that virtualizes DRAM and persistent memory so the pool of lower cost memory can be accessed without changes to an application. The software builds on its transparent memory service with in-memory data services that allow terabytes of cell data to be managed at the speed of memory. Memory Machine Standard Edition • Transparent Memory Service – virtualizes DRAM and PMem and makes the pool of mixed memory appear to the application as familiar DRAM. • Memory Tiering Service – Dynamically places hot data in DRAM and warm data in persistent memory. • Memory Quality of Service (QoS) – Allows “noisy neighbor” applications to be isolated and guarantee memory bandwidth to most important applications. Memory Machine Advanced Edition • All of the features in Standard Edition. • ZeroIO In-Memory Snapshots – in-memory snapshots copy data from DRAM to either persistent memory or storage, and the foundation of in-memory data services that allow data management at the speed of memory. • AppCapsules – In-memory snapshots that capture an entire application state including registers, cache, GPUs, and storage. Allows an application to quickly re-start after a system crash, burst to the cloud or move from cloud to cloud. • Local and Remote Memory Replication – In-memory snapshots used to instantly replicate up to terabytes of data for disaster recovery, or to clone data for parallelism. • Rollback – With frequent snapshots, researchers can easily change a parameter in their pipeline by rolling back their application to a snapshot at a specific point-in-time.
Product Name: Modak Nabu 2.5
Modak Nabu is an integrated data engineering platform that converges data ingestion, data profiling, data indexing, and data exploration into a unified platform, driven by metadata. This metadata-driven approach helps to automate and augment many repetitive tasks. Modak Nabu uses data spiders to automate capturing technical metadata, for both structured and unstructured data sources. Modak Nabu provides 1. Automated data pipelines – Simplifies the process of onboarding data from a variety of sources to different cloud environments. 2. Automated data discovery and profiling – Democratizes access to data assets by making them accessible and understandable. 3. Monitoring and Visibility – Provides a real-time view of the progress of data management tasks for different stakeholders, from operations to the executive team. 4. Self-service data management – Complex data management tasks can be executed using a simple intuitive interface, with adequate governance controls. 5. Tags in data connections and data pipelines: To add context to data engineering activities, Nabu 2.5 provides the ability to add tags to data connections and pipelines.
SciBite, an Elsevier company
Product Name: CENtree 2.1
CENtree, a centralized, enterprise-ready resource for ontology management, transforms maintaining and releasing ontologies. CENtree recognizes and ingests multiple publicly available ontologies. Ontology browsing is oriented around a tree view tailored to visualize biomedical ontologies, their entities, and their relationships. CENtree 2.1 expands SciBite’s commitment to open standards via support for importing and exporting terminologies in the W3C Simple Knowledge Organization System (SKOS) format, to add to our existing support for the Web Ontology Language (OWL) format. CENtree enables the creation of custom ontologies from public and proprietary ontologies; the steps for creating these application ontologies is stored and replayable for ease of update. Adding new classes and editing/enriching existing classes is simplified enabling broader audience contributions. Edits are captured using open standards to make the resulting ontology reusable elsewhere. A deep learning component helps users edit by suggesting possible relationship connections for a given class. Provenance is captured for every edit action, with user comments to explain edits, and the ability to reject/undo an undesired change. A roles-based governance model controls the ability to affect changes. CENtree employs a Git-like approach to managing change with our custom versioning engine, empowering an organization to keep current with the latest public versions, whilst internally adding new content such as extending with new classes or fixing errors. The CENtree interface is founded on a flexible API which can be directly integrated into existing systems. As a SaaS solution, CENtree is secure and simple to deploy, Professional Services support integrations, ontology curation and advice.