Webinar

Building a Predictive Diagnostic Model from Menstrual Fluid Data

Key Highlights

Menstrual fluid is a non-invasive, data-rich source poised to change women's health diagnostics. NextGen Jane is pioneering its use, but translating this potential - from multi-omics (transcriptomics, Bulk RNA-Seq) to real-world clinical insights and diagnosis, this demands sophisticated AI. The challenge lies in synthesizing massive, siloed, and messy Electronic Medical Records (EMRs) with complex biological data.

Join us to hear from NextGen Jane and Elucidata experts. We will detail a vision for personalized diagnostics, articulate the crucial role of AI-driven EMR and omics curation, and demonstrate exactly how our combined approach is solving this foundational challenge to build high-confidence predictive and classifier models to diagnose Endometriosis, Infertility and other problems related to women’s health.

‍

Webinar

Upcoming Webinar

In collaboration with

Building a Predictive Diagnostic Model from Menstrual Fluid Data

What the AI Co-Scientist Paper Actually Demonstrates for Biologists and Data Scientists

December 2, 2025

9 AM PT

‍

Here's your

link

to the webinar recording.

Thank you for registering.

Please check your inbox for further details to join this webinar.

Oops! Something went wrong while submitting the form.

Registrations are closed!
‍

Meet the Expert of this discussion

Stephen Gire

CSO, NextGen Jane

Real-World Applications We’ll Cover

Scaling clinico-genomic data integration: Large pharmaceutical organizations working with external data providers used Polly to build interoperable clinico-genomic data products 6x faster.
Although purchased datasets are often labeled as "clean," they still lack interoperability—Polly's pipelines bridge this gap with robust integration and harmonization.
Information Retrieval: Drug safety monitoring teams used Polly's Knowledge Graph powered co-scientist to conversationally retrieve the right cohorts & assess drug response—cutting discovery time by 70%.

Join us for a behind-the-scenes look at a Multi-agent AI system that achieves:

93% recall across 23 key metadata fields including tissue, disease, cell line, donor ID, and treatment.
Outperformance of GPT-4.1 single-pass prompting on accuracy, F1 score, and traceability.
Curation of 4652 samples from 78 GEO datasets in days instead of weeks.
4x reduction in manual effort equivalent to replacing a 3-person expert team working for 1 month.
Human-level accuracy, with 100% concordance on disease and 97% on gender based on CellxGene benchmarks.
Traceable records with field-level evidence attribution and confidence scores.

‍Register for our webinar to see how the Agentic AI system fits into scalable data workflows.

What You’ll Learn

Next-Gen Diagnostics: NextGen Jane's vision for leveraging menstrual fluid multi-omics to create powerful, non-invasive predictive tools.
The Curation Bottleneck: Why AI-driven curation of complex EMRs is the critical solution to building accurate multi-omics diagnostic models.
AI Data Synthesis: How advanced AI harmonizes complex, multi-source data (EMR, Omics) into unified, analysis-ready assets.
Live EMR-to-Insight Demo: Witness the process of converting unstructured EMR data into structured evidence for diagnostic model training.
Model Validation Framework: The framework for linking molecular signatures to curated clinical phenotypes to build robust, AI-validated models.

Meet the Expert of this discussion

Stephen Gire

CSO, NextGen Jane

Meet the Expert of this discussion

Stephen Gire

CSO, NextGen Jane

What Sets polly KG Apart

Natural language querying with reasoning on
the roadmap

Cross-species graphs built from both proprietary
and public data

Custom scoring logic and domain-specific
ontology support

Seamless integration with internal tools, platforms,
and security frameworks

Who Should Attend

Translational Scientists and Discovery Leads

Computational Biologists and Data Scientists

Platform Owners, heads of R&D IT

Innovation and AI Strategy Teams

Who Should Attend

Translational Scientists and Discovery Leads

Data Science & Informatics Teams

Computational Biologists and R&D IT Leaders

Innovation & AI Strategy Teams

Why This Matters for Biomedical Researchers

If you’re working with complex biological data, you may be asking:

Can generative AI truly assist in scientific reasoning, not just data analysis?
What does it mean for hypothesis generation, literature review, or even designing experiments?
Could this accelerate—not replace—my discovery pipeline?

Whether you're skeptical, curious, or already experimenting with AI in your lab—this is a session designed to ground your understanding in evidence, not speculation.

De-Risk R&D: Overcome the EMR data curation challenge with a proven AI methodology for faster, more reliable model development.
Acquire Novel Skills: Master the methodology for integrating menstrual fluid multi-omics with clinical data, a rapidly advancing area in diagnostics.
Overcome EMR Friction: Learn practical, AI-driven solutions to the primary bottleneck in translational research: linking unstructured EMRs to high-fidelity molecular data.
Build Clinically Robust Models: Understand the framework for developing AI classifier models that are validated and reliable for downstream clinical application.

Traditional KG

De-Risk R&D: Overcome the EMR data curation challenge with a proven AI methodology for faster, more reliable model development.
Acquire Novel Skills: Master the methodology for integrating menstrual fluid multi-omics with clinical data, a rapidly advancing area in diagnostics.
Overcome EMR Friction: Learn practical, AI-driven solutions to the primary bottleneck in translational research: linking unstructured EMRs to high-fidelity molecular data.
Build Clinically Robust Models: Understand the framework for developing AI classifier models that are validated and reliable for downstream clinical application.

Polly KG

Meet the Expert of this discussion

Stephen Gire

CSO, NextGen Jane

Key Takeaways

How data providers ensure adherence to quality standards through validation and compliance.

How GUI-based workflows, CLI tools, and collaborative workspaces enable streamlined data ingestion and synchronization at scale.

Understand how automated pipelines assess conformance, plausibility, and consistency, ensuring high-quality, AI-ready data products.

Key Takeaways

Reduce operational costs by streamlining data delivery through reusable, governed products.

Accelerate diagnostic development and clinical trial execution by delivering compliant, high-quality data at scale.

Improve audit readiness and regulatory confidence through governed data products and built-in quality assurance.

Equip cross-functional teams to act on trusted data—faster, and with greater confidence.

Who Should Attend

Translational Scientists and Discovery Leads

Computational Biologists and Data Scientists

Platform Owners, heads of R&D IT

Innovation and AI Strategy Teams

What Sets polly KG Apart

First KG to integrate molecular data alongside patient data records

Feature distillation pipeline for high-dimensional clinical and trial data

Base KG usable immediately, with flexible schema extensions

Cross-species graphs built from proprietary, public, and clinical datasets

Who Should Attend?

All Webinars

De-risking Autoimmune Clinical Trials with Agentic AI

Incorporating 'Patient Data' to Knowledge Graphs

AI-Powered Insights from PK/PD Clinical Trial Data

Polly KG -A Co-Built Knowledge Graph That Evolves With Your Unique Research

AlphaGenome Unpacked: Promise, Progress, and What Comes Next for AI in Genomics

Precision at Scale: Agentic AI Delivers Human-Accurate Biomedical Metadata to Accelerate Precision Medicine

Other Resources

All Webinars Case Studies Dataset Roundup Documentation Glossary Solution Briefs Whitepapers

[Upcoming Webinar] Scaling High-Quality Data Processing: Achieve 4x Cost Reduction for Foundation ModelsRegister Now->

Reserve Your Seat