Neurodiagnoses Logo Neurodiagnoses
Research Platform: Academic & Clinical Research
⚠️ FOR RESEARCH USE ONLY - Not Validated for Clinical Diagnostic Use

Use Cases: Academic Research + Clinical Research

Neurodiagnoses serves both academic research and clinical research workflows with the same validated science (0.0% deviation). Our Freemium model provides open access for research while offering premium features for clinical research investigations.

This platform supports clinical research but is not a validated medical device or diagnostic tool for clinical use.

Freemium Model: Choose Your Workflow

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Academic / Research

FREEMIUM (Open Access)

Use Case:

You have a research cohort (n=50-500 patients) and want to validate multi-omic causal hypotheses (e.g., "Does APOE ε4 manifest molecularly in my cohort?").

What You Get:

  • ✓ Cohort-level validation dashboards (62.5% / 37.5%)
  • ✓ Statistical analysis (t-tests, correlations, Cohen's d)
  • ✓ Interactive visualizations (scatter plots, heatmaps)
  • ✓ AI Co-pilot for data exploration
  • ✓ Manuscript-ready results tables

Typical Workflow:

  1. 1. Upload cohort CSV (genetics + proteomics + imaging)
  2. 2. View pre-loaded validation results (62.5% causal, 37.5% spatial)
  3. 3. Explore data with AI Co-pilot (ask questions, generate plots)
  4. 4. Export results for publication

Why Free? We believe validated multi-omics research should be accessible to all scientists worldwide. Our mission is to democratize precision medicine research.

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Clinical Research

PREMIUM (Subscription) ⚠️ Research Use Only

Primary Tool:

Case Analyzer

Use Case:

You are a clinical researcher and need a comprehensive analysis report for an individual patient in a research study on Alzheimer's disease or related dementia.

What You Get:

  • ✓ 5-step guided analysis workflow
  • ✓ Template-based data ingestion (zero errors)
  • ✓ Individual causal validation score (binary: validated/not validated)
  • ✓ Individual spatial concordance score (region-specific)
  • ✓ Research report with detailed findings
  • ✓ HIPAA/GDPR-compliant data handling

Typical Workflow:

  1. 1. Create patient case (patient ID)
  2. 2. Upload genetics (VCF or manual APOE/TREM2)
  3. 3. Upload omics (proteomics CSV using template)
  4. 4. Upload imaging (FreeSurfer volumes CSV using template)
  5. 5. Receive comprehensive diagnostic report

Why Premium? Clinical research-grade individual analysis requires HIPAA/GDPR infrastructure, 24/7 uptime, and secure data handling. Subscription supports this infrastructure.

⚠️ For research purposes only - Not for clinical diagnostic use

The Best of Both Worlds

Because both workflows use the same unified validation methodology, research and clinical research results are scientifically congruent. You can trust that discoveries in the Data Lab will translate to the Case Analyzer.

Academic Research Path (Data Lab)

Same patient, same data → Unified validation (context: cohort)

Result: 62.5% validation (t-test, p=0.018)

Clinical Research Path (Case Analyzer)

Same patient, same data → Unified validation (context: individual)

Result: 62.5% validation (binary: validated)

Deviation: 0.0% (Guaranteed by consistent methodology)

Example Scenarios

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Scenario 1: Neuroscience PhD Researcher

Question: "In my cohort (n=120), does APOE ε4 carrier status correlate with elevated CSF tau and hippocampal atrophy?"

Tool: Interactive Data Lab (Freemium)

Result: Upload cohort CSV → View causal validation dashboard (62.5%, 5/8 biomarkers significant, p < 0.05) → Export results for manuscript → Cite Neurodiagnoses research platform in methods

⚠️ For research purposes only

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Scenario 2: Clinical Research Neurologist

Question: "My research subject (68 years old) has APOE ε4/ε4, elevated CSF pTau, and MRI showing hippocampal atrophy. Is this causal chain validated?"

Tool: Case Analyzer (Premium) - Research Use Only

Result: Follow 5-step wizard → Upload genetics, proteomics, imaging CSVs → Receive research analysis report → Causal validation: VALIDATED (genetic risk actively manifesting molecularly) → Spatial concordance: HIGH (tau pathology correlating with hippocampal volume loss)

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Scenario 3: Bioinformatician (Custom Analysis)

Question: "I want to run custom Python code to explore the relationship between specific proteomic markers and brain network connectivity."

Tool: Studio (Freemium)

Result: Access cloud-based Jupyter environment → Pre-loaded libraries (scipy, pandas, networkx) → Access Neurodiagnoses validation methods → Combine with custom connectivity analysis → Export results

Industrial Services Use Cases

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Early Screening: Risk Stratification

Scenario: A pharmaceutical company wants to identify high-risk individuals for a prevention trial targeting early-stage Alzheimer's disease.

Service: Early Screening API

Input: Patient demographics, CSF biomarkers (ATN profile), plasma biomarkers, genetic factors (APOE, PRS)

Output: Risk stratification (5 levels), conversion probability, time-to-event estimates, survival curves. Enables precise patient selection for prevention trials.

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Clinical Trials: Enrollment Optimization

Scenario: A CRO needs to optimize enrollment for a Phase 3 trial by stratifying patients based on biomarker profiles and identifying surrogate endpoints.

Service: Clinical Trials API

Input: Trial criteria, patient cohort data with longitudinal biomarker measurements

Output: Stratified enrollment recommendations, biomarker-based patient groups, surrogate endpoint candidates with validation metrics. Reduces enrollment time and improves trial efficiency.

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Gene Therapies: Target Identification

Scenario: A biotech company is developing gene therapies for rare neurodegenerative diseases and needs to identify optimal therapeutic targets.

Service: Gene Therapy API (powered by GeneForge)

Input: Genetic variant data, patient clinical profile

Output: Therapeutic susceptibility scores, prioritized gene therapy targets, pathway analysis, therapeutic recommendations. Accelerates target selection and prioritization.

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Target Discovery: Pathway Analysis

Scenario: A pharmaceutical R&D team wants to identify novel therapeutic targets by analyzing multi-omics data from disease cohorts.

Service: Target Discovery API

Input: Multi-omics data (proteomics, transcriptomics), disease context

Output: Activated pathways, prioritized therapeutic targets, mechanistic hypotheses, pathway maps. Enables data-driven target discovery and hypothesis generation.

Industrial Services Features

  • ✓ Multi-omics integration (genomics, transcriptomics, proteomics)
  • ✓ Explainable AI with transparent visualizations
  • ✓ Validation by design (causal and spatial validation)
  • ✓ Secure data governance
  • ✓ Batch-effect mitigation
  • ✓ Multi-cohort cross-validation
  • ✓ API access for integration
  • ✓ Exportable reports

Ready to Start?

Whether you're a researcher, clinical researcher, or bioinformatician, Neurodiagnoses has a workflow for you.

⚠️ All tools are for research purposes only - Not validated for clinical diagnostic use