T2D2: Turing Test for Drug Discovery

We're redefining AGI by the value of work it delivers and testing whether autonomous systems can execute expert-level research from raw data to novel insights.

Focus on Research that works in real R&D pipelines

T2D2 replaces subjective assessment with a grounded framework that ensures AI agents meet the highest standards of scientific rigor:

01

Causal Insight
Data-centric AI Focus
The agent distinguishes real causes from coincidences.

02

Proactive Risk Sensing
Customization-First PaaS
The agent spots safety problems early enough to change course.

03

Scalable Reproducibility
Every decision remains traceable, auditable, and repeatable.
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Three-layered Architecture That Holds Biological Context

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How Polly Helps?

Build a Custom, ML-ready Atlas Specific to Your Research

Develop a customized Atlas with ML-ready data for bias-free target predictions.

Create a disease-specific Atlas comprising meticulously curated data enriched with critical metadata and engineered for seamless integration into target prediction models.

Enhance prediction accuracy and mitigate bias through model training with multi-modal, harmonized datasets.

Instill confidence in your predictions by combining consistently processed samples for robust results.

Derive Expression Signatures From Relevant Cohorts

Explore healthy and patient cohorts on Polly for a comprehensive molecular profiling of the disease being studied.

Conduct gene expression analysis to uncover differentially expressed signatures specific to the disease condition.

Identify potential candidate genes by assessing their druggability scores and cross-referencing with publicly available evidence.

Validate Identified Targets With Public Data

Cross-reference your results with published evidence using curated public data delivered on Polly.

Validate target reliability by meta-analyzing relevant studies on Polly.

Evaluate targets for sensitivity, specificity, and clinical utility with rigorous statistical analysis.

Real Impact, Real Stories

Case study

Six Months to Success: Accelerating AML Target-indication Assessment With Advanced Knowledge Graphs

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On-demand Webinars on Knowledge Graph

Case study: Accelerated Target ID using ML-Ready data on Polly
Incorporating 'Patient Data' to Knowledge Graphs
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Case study: Accelerated Target ID using ML-Ready data on Polly
Polly KG -A Co-Built Knowledge Graph That Evolves With Your Unique Research
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Case study: Accelerated Target ID using ML-Ready data on Polly
Precision at Scale: Agentic AI Delivers Human-Accurate Biomedical Metadata to Accelerate Precision Medicine
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Can AI do a Computational Biologist's Job?

Inspired by Andrew Ng's Turing-AGI framing, T2D2 evaluates AI's real capabilities in drug discovery and identifies where it works best with humans in the loop.

Data Preparation

Selects appropriate datasets and publications, separate signal from noise, and build chains of evidence across papers without human intervention.

Execution & Synthesis

Clean and structure messy biomedical data (single-cell, bulk-sequencing), cross-references hundreds of publications, and verifies results.

End-to-End Execution

Chain tasks into complete workflows that deliver ready-to-use insights that are reproducible, complete with citations, to a skilled-human standard.

Our Framework for Evaluation

The Turing-AGI Standard

T2D2 tests multi-step, agentic workflows. The system must maintain scientific meaning over complex tasks.

Economically Useful Work

The standard isn't plausible answers but the work that functions in real R&D pipelines.

Expert-Led Benchmarks

Judges AI performance against the output of expert computational biologists using objective metrics.

Evidence-Based Discovery

T2D2 identifies where AI, humans, or hybrid workflows delivers best results.

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What Makes Polly KG Unique

Natural Language Querying

Explore complex biological systems efficiently, without code or manual searches.

Advanced AI Insights

Get custom target scoring and linkage prediction for precise, multi-indication targeting.

Data-Scarce Adaptability

Excels where traditional KGs fail, providing solutions for non-model organisms and limited data.

Accelerated Discovery

Achieve 75% faster hypothesis generation (months to hours), cutting target ID to just 6 months.

Advanced AI Insights

Get custom target scoring and linkage prediction for precise, multi-indication targeting.

Data-Scarce Adaptability

Excels where traditional KGs fail, providing solutions for non-model organisms and limited data.

Accelerated Discovery

Achieve 75% faster hypothesis generation (months to hours), cutting target ID to just 6 months.

Our Dynamic, Secure Architecture

Our unique, multi-layered architecture ensures you always have the most relevant, secure, and up-to-date information.

Base Knowledge Graph (Base KG)

Broad, regularly updated public knowledge.

Proprietary Layer

Securely integrates your sensitive internal data.

Context Layer

Tailored and frequently refreshed for specific use cases.

The Most Scalable & Comprehensive Knowledge Landscape

Polly KG is built for the future of biology, designed to evolve with your research needs

Scalable Data Landscape

Built on millions of nodes and relationships, integrating 20+ sources, including the largest single-cell data collection.

Cross-Species Capabilities

Unify knowledge across over 50 species, extending insights beyond human-centric data.

Trusted by the World's Leading Biopharma Players

Ready to
Accelerate Your Discovery