In precision medicine, identifying the right patient populations is critical. However, scientists and clinicians spend up to 80% of their time just trying to organize messy, disconnected data from databases and spreadsheets before they can even start looking for the patients who might respond to a new treatment.

The data exists, but the heavy lifting required to actually use it is a massive roadblock. That’s exactly why we built the Polly Cohorter. It supports a specific user journey to identify, build, share, save cohorts from curated data that may be accompanied with visualizations as required.

The End-to-End Cohort Journey

The Polly Cohorter streamlines the entire machine learning and bioinformatics lifecycle, allowing researchers to easily navigate from raw data extraction to downstream analysis.

1. Identify and Isolate Patient Sub-Populations

Researchers can bypass complex coding and use AI-assisted text-to-query features to search large, complex databases. The platform maps your queries against standardized medical ontologies, allowing you to accurately identify and isolate specific patient cohorts across 25+ distinct data modalities.

2. Analyze and Visualize Instantly

The cohort is accompanied by immediate visual context. Users can interact with their isolated data subsets through integrated notebooks or a user-friendly GUI. The platform natively generates custom dashboards to visualize trends, patterns, and cell-type composition in real time, empowering in-depth exploration before exporting any data.

3. Save, Share, and Reproduce

The platform allows you to save your identified cohorts as distinct bundles. You can easily share these cohorts with your team to ensure total reproducibility and a seamless handoff to downstream machine learning or bioinformatics pipelines.

Built for High-Value Science

By transitioning teams away from static data repositories and into an active discovery framework, the Polly Cohorter powers a wide range of critical R&D applications:

• Patient Stratification & OOD Detection: Isolate specific sub-populations using multi-omics profiles. Instantly identify out-of-distribution (OOD) signals to spot rare patient groups that rigid pipelines miss.
• Meta-Analysis: Harmonize fragmented, multi-modal studies into a single, unified dataset to uncover subtle biological signals and validate findings across independent cohorts.
• Biomarker Prediction: Track how biological markers evolve over time. Leverage versioned cohorts to see how newly integrated data directly impacts your predictive models.
• Target Identification: Interrogate fully contextualized, clean data to uncover deep biomolecular knowledge. Seamlessly hand off these high-fidelity insights directly to downstream pipelines.

Secure, Compliant, and ML-Ready

Data security is non-negotiable. The Polly platform is fully audited, HIPAA, and SOC2 compliant.

By automating the messy work of data cleanup, the Polly Cohorter helps you identify, visualize, and share patient cohorts 4x faster. Whether you are finding novel drug targets, validating biomarkers, or matching patients for clinical trials, Polly Cohorter is built to scale with your research.

‍