Tech-Enabled Services
Optimized for Life Sciences

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The cohorts you need. Now.
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Visually explore complex, multimodal, longitudinal datasets to identify, analyze, and compare purpose-built cohorts. Create custom, compound phenotypes and connect with genetic and biomedical imaging data. Seamlessly synchronize and share cohorts and analyses between GUI users and R/Python users. Capture context, purpose, and provenance.
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Business impact. Fast.
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Science-ready software packages for multimodal data analysis informed by years of close partnerships. Or build your own with a running start from extensible, open APIs, and bioinformatics schema. Integrative analytics across public and proprietary datasets and trials. Ad hoc, tertiary analytics with an experience that lets you focus on what you want to ask, not how to ask it. Ensure provenance and reproducibility.
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Business impact.
Even faster.
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A superset of Analyze. Adds automated massively scalable computing with Burst Mode. Includes Single Cell, Spatial Transcriptomics, Proteomics packages.
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Optimal price/performance for cloud files.
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Cut cloud storage and operational overhead costs for research data commons and biomedical imaging data. Eliminate over provisioning with infinite elasticity. Accelerate massively parallel cloud computing with unrivaled throughput.

"We continue to marvel at Paradigm4’s ability to manage the ever-growing complexities in the day-to-day work of incorporating new genetics tool sets and the constant expansion of novel, diverse phenotypic data. They have transformed the pace of our daily research."

Greg Hinkle

V.P., Research Informatics

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Ad Hoc Analytics, Collaboration, Visualization
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GUI-centric cohort exploration and creation
Use Case Solutions Packages with (hundreds) APIs for bioinformatics common queries and computations (R, Python)
Use Case Solutions Package: Biobank
Use Case Solutions Package: Variant Datastore
Use Case Solutions Package: Single Cell & Spatial Transcriptomics
Use Case Solutions Package: Proteomics
Unified Data Management and Compute
Autonomous Elastic Compute
Extensibility for New Bioinformatics Algorithms
Scalability for New Bioinformatics Algorithms
Support for ML Workflows (Tensor, Pytorch, more)
Seamless round trip analyses between GUIs and Notebooks
GUI-based Association Set Data Explorer: PheGe
Variant Registry with source and annotations
Longitudinal data analysis in both Cohort GUI and programmatic solutions packages
OMOP support
Cross-Study Analyses
Customizable Data Visualizations with Popular R and Python graphing packages
Automated workflows
Jupyter notebooks for tutorials and documentation
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Multi-Modal Dataset Support
Complete FAIR Compliance
Preloaded, Ready-to-Use Ontologies (eg SNOMED, OMAP, Human Cell Atlas)
Preloaded, Ready-to-Use Reference Data (eg HG38)
Preloaded, Ready-to-Use Public Datasets (eg TCGA, Association Datasets)
Enterprise VPC Deployment
Variant Registry with source and annotations
Data Organized & Optimized for Both Discovery and Compute
Automated Annotation for Filtering and Interpretation (eg VEP, Loftee)
Metadata Loading and Creation
Alignment With Specific Version of Reference Genome
Pre-defined data models for biologicial entities
Import & Load Custom File Types and Objects (VCF, TileDB Objects)
Support for running workflows using Nextflow and Snakemake
flexFS Elastic File System for speciality bioinformatics files formats and other file-specific data
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ISO27001 Certified
Integration with Enterprise Identity & Access Management
Project and dataset level data access control
High Resolution Logging
Metadata and Data Versioning
Analytical Environment Versioning

Elastic Data Storage

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Launched in 2023 to address the needs of biopharma R&D teams querying vast multimodal datasets simultaneously, flexFS’s cloud-agnostic, infinitely elastic and POSIX-compliant profile has since also proven its value in other data-intensive fields, including climate science and insurance risk modeling. 

Its benefits go beyond just reducing operating and cloud costs to something far more critical: clearing bottlenecks that can slow R&D, streamlining the application of data to answer critical questions and delivering business impact faster. Unlike most attempts at building file systems backed by object storage, flexFS strongly delivers on uncompromising performance, reliability, simplicity, and fully networked POSIX-compliance.

Elastic Data Storage

FlexFS

Launched in 2023 to address the needs of biopharma R&D teams querying vast multimodal datasets simultaneously, flexFS’s cloud-agnostic, infinitely elastic and POSIX-compliant profile has since also proven its value in other data-intensive fields, including climate science and insurance risk modeling. 

Its benefits go beyond just reducing operating and cloud costs to something far more critical: clearing bottlenecks that can slow R&D, streamlining the application of data to answer critical questions and delivering business impact faster. Unlike most attempts at building file systems backed by object storage, flexFS strongly delivers on uncompromising performance, reliability, simplicity, and fully networked POSIX-compliance.

FlexFS