RareCollab Analysis
Transforming Rare Disease Diagnosis with AI-Powered Multi-Modal Integration
RareCollab combines genomic, transcriptomic, and phenotypic data with advanced AI agents to accelerate definitive diagnoses for Mendelian disorders.
Executive Impact
RareCollab's innovative approach yields significant improvements in diagnostic accuracy and efficiency, critical for families navigating the diagnostic odyssey.
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Top-5 Diagnostic Accuracy
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Improvement in Top-5 Accuracy
0 cases
UDN Proband Cohort
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
77%
Top-5 Diagnostic Accuracy Achieved by RareCollab
| Approach | Top-1 Accuracy | Top-5 Accuracy |
|---|---|---|
| RareCollab | 46% | 77% |
| RareCollab-Diagnostic Engine | 38% | 65% |
| AI-MARRVEL | 30-38% | 45-57% |
| Exomiser | 25-26% | 35-45% |
Impact on Difficult Cases: Highly Likely Diagnoses
For diagnostic variants classified as Highly Likely (often reflecting atypical presentations or incomplete evidence), RareCollab recovered 75% within the top five, a 17-point improvement over AI-MARRVEL. This highlights the benefit of integrating RNA-seq and high-resolution evidence interpretation in challenging scenarios.
Enterprise Process Flow
Raw Data Input (WES/WGS, RNA-seq, Phenotypes)
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Bioinformatics Pipelines (Variant Calling, Expression/Splicing Quant)
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Unified Feature Table
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Diagnostic Engine (DNA-centric ranking backbone)
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LLM Specialist Labs (RNA, Phenotype, Database, Literature)
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Integration Engine (Tier Assignment)
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Confidence Reviewer
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Prioritized Diagnostic Variants
Role of LLM Specialist Labs
The four LLM Labs (RNA, Phenotype, Database, Literature) complement the DNA-centric backbone by adding high-resolution, context-aware interpretation. They collectively explain most of RareCollab's diagnostic decisions, with the RNA Lab identifying supportive transcriptomic abnormalities for 41% of diagnostic variants.
Stable
Performance across different LLM backbones (gpt-oss-20B, llama3-8B, etc.)
| LLM Backbone | Top-1 Recall | Top-5 Recall |
|---|---|---|
| gpt-oss-20B (default) | 46% | 79% |
| gpt-oss-120B | 44% | 79% |
| gemma-3-27B | 42% | 74% |
| llama3-8B | 41% | 74% |
Advanced ROI Calculator
Estimate the potential impact of integrating AI-powered diagnostic systems into your research or clinical workflow. Input your team's current manual analysis workload to see projected savings and reclaimed hours.
Projected Annual Savings
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Hours Reclaimed Annually
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Implementation Roadmap
Our phased implementation strategy ensures a smooth transition and optimal integration of RareCollab into your existing operations.
Phase 1: Needs Assessment & Customization
Detailed analysis of your current diagnostic workflow, data infrastructure, and specific requirements to tailor RareCollab for maximum impact.
Phase 2: Data Integration & Model Fine-tuning
Secure integration of your genomic, transcriptomic, and phenotypic data, followed by fine-tuning of AI models to optimize performance for your patient cohort.
Phase 3: Pilot Deployment & Validation
Rollout of RareCollab on a pilot set of cases with rigorous validation against known diagnoses and expert review, ensuring accuracy and reliability.
Phase 4: Full-Scale Operation & Ongoing Support
Seamless deployment across your organization with continuous monitoring, performance enhancements, and dedicated support from our AI specialists.
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