About
Polly by Elucidata is an enterprise-grade, AI-ready data platform built exclusively for Pharma and BioPharma R&D teams. It centralises and harmonises multi-modal biomedical data — including single-cell RNA-seq, bulk RNA-seq, proteomics, spatial transcriptomics, EHR assay data, and whole slide imaging — into standardised, ML-ready formats that power faster drug discovery workflows. Core platform modules include Polly Xtract for AI-powered extraction from complex scientific documents, a Harmonization Engine for cross-modal data standardisation, Atlas as a structured multi-modal data repository, and Polly Co-Scientist for generating actionable insights from proprietary and public datasets. A Data Concierge service filters noise from scientific literature, while FAIR-compliant ETL pipelines enable seamless data integration at scale. Elucidata additionally supports custom bioinformatics pipeline building, metadata curation, data quality assessment (conformance, completeness, consistency, plausibility), and development of bespoke web apps and dashboards. Public datasets from GEO, PRIDE, and CPTAC are available on the platform out of the box, enriching in-house data with curated external resources. Designed for flexible enterprise deployment — cloud, on-premise, or managed — with robust security and compliance controls, Polly is suited for large R&D organisations seeking to operationalise multi-omics data for target identification, biomarker discovery, meta-analysis, and patient stratification.
Key Features
- Polly Xtract: AI-powered extraction of structured, analysis-ready data from complex scientific documents, literature, and raw experimental datasets.
- Harmonization Engine: Automatically harmonises multi-modal biomedical data — omics, EHR, and imaging — into consistent, ML-ready formats suitable for downstream AI and statistical analysis.
- Atlas Multi-Modal Repository: A structured, searchable repository for storing and accessing both proprietary and curated public datasets including GEO, PRIDE, and CPTAC.
- FAIR ETL & Bioinformatics Pipelines: Build FAIR-compliant ETL and bioinformatics pipelines customised to specific assay types, data modalities, and analytical requirements at scale.
- Polly Co-Scientist: An AI-powered research assistant that generates actionable biological insights from harmonised multi-omics and biomedical datasets.
Use Cases
- Target identification by integrating harmonised multi-omics datasets to rapidly discover and validate drug targets across disease areas.
- Biomarker discovery using machine learning on structured multi-modal data to identify diagnostic, prognostic, or companion diagnostic biomarkers.
- Patient stratification by combining EHR, genomics, and imaging data to segment patient populations for precision medicine and clinical trial design.
- Meta-analysis across large curated public and proprietary omics datasets to derive statistically robust, reproducible biological insights.
- Bioinformatics pipeline development with FAIR ETL workflows and custom processing pipelines tailored to specific assay types and data modalities.
Pros
- Comprehensive Multi-Modal Data Support: Handles a broad range of data types — single-cell, bulk omics, EHR, proteomics, spatial transcriptomics, and imaging — with consistent FAIR-compliant standardisation.
- Accelerates Drug Discovery: Significantly reduces time-to-insight for critical BioPharma workflows including target identification, biomarker discovery, and patient stratification.
- Proven Enterprise Adoption: Trusted by 50+ leading BioPharma organisations including Janssen, Genentech, and Alnylam, demonstrating real-world reliability at scale.
- Flexible Deployment Options: Supports cloud, on-premise, and managed service deployments with robust security and compliance controls suited for regulated industries.
Cons
- Opaque Enterprise Pricing: Pricing is not publicly listed and is tailored to enterprise contracts, potentially making it inaccessible for smaller biotech firms or academic research groups.
- Significant Onboarding Complexity: The breadth of modules, data types, and pipeline configuration options can require considerable time and expert support to fully operationalise.
- Narrow Industry Focus: Purpose-built for life sciences and BioPharma R&D, limiting its applicability and value proposition outside of these domains.
Frequently Asked Questions
What types of biomedical data does Polly support?
Polly supports a wide range of data types including single-cell RNA-seq, bulk RNA-seq, microarray, proteomics, spatial transcriptomics, single-cell CITE-seq, ATAC-seq, EHR assay data, and whole slide imaging.
What public datasets are available on the Polly platform?
Polly provides pre-processed, harmonised access to major public repositories including GEO (Gene Expression Omnibus), PRIDE (proteomics data), and CPTAC (cancer proteogenomics atlas).
Can Polly be deployed on our organisation's own infrastructure?
Yes, Polly supports flexible deployment including cloud, on-premise, and fully managed service environments to meet enterprise-grade security, compliance, and data sovereignty requirements.
What is Polly Co-Scientist?
Polly Co-Scientist is an AI-powered assistant embedded within the platform that helps researchers extract actionable insights from harmonised multi-omics and biomedical datasets through natural language queries and guided analysis.
Who is Elucidata's Polly platform designed for?
Polly is designed for Pharma and BioPharma R&D teams — including data scientists, bioinformaticians, and computational biologists — who need to manage, harmonise, and analyse large-scale multi-modal biomedical data for drug discovery and development.
