# ROI Analysis: Precision Medicine MCP Platform

Comprehensive return on investment analysis for institutional funders and hospital decision-makers.

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## Executive Summary

This platform enables **multi-modal synthesis** — integrating genomics, spatial transcriptomics, multi-omics, imaging, and clinical data in ways manual workflows cannot achieve at scale. All tools are accessible via natural language (no coding required). Every AI-generated result requires **clinician APPROVE/REVISE/REJECT** before clinical use, with HIPAA-compliant architecture (de-identification, 10-year audit trails, VPC isolation).

**Projected Payback Period:** First 2-3 patients analyzed
**Projected Annual ROI:** $313,700 (100 patients) | $1,568,500 (500 patients)
**Cost per Patient:** $324-702 total (compute + personnel) vs. $6,000-9,000 traditional manual analysis

> **Important:** All ROI figures in this document are **modeled projections** based on workflow comparisons with traditional bioinformatics analysis. They have not yet been validated in a clinical pilot with real patient data. A funded pilot is required to confirm these estimates.

> **Cost methodology:** See [Cost Analysis](../reference/shared/cost-analysis.md) for detailed cost breakdowns by analysis mode.

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## Cost Comparison: Traditional vs. MCP Platform

### Per-Patient Analysis Cost

| Component | Traditional Manual | MCP Platform | Savings |
|-----------|-------------------|--------------|---------|
| **Bioinformatics Labor** | $6,000-9,000<br/>(40 hours × $150-225/hr) | $300-600<br/>(oversight: 2 hours × $150-300/hr) | **$5,700-8,400** |
| **Compute Resources** | $200-500<br/>(HPC cluster time) | $24-104<br/>(GCP Cloud Run + storage) | **$176-398** |
| **API/LLM Costs** | $0 | $1-3<br/>(Claude tokens) | **-$3** |
| **Total Per Patient** | **$6,200-9,500** | **$324-702** | **$5,875-8,796** |

**Modeled Average Savings:** **$3,098-3,176 per patient** (projected, pending clinical validation)

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## Annual Operating Costs

### Pilot Deployment (100 Patients/Year)

| Cost Category | Annual Cost | Notes |
|--------------|-------------|-------|
| **GCP Infrastructure** | $12,000 | Cloud Run, storage, networking |
| **Claude API Tokens** | $100-200 | Claude tokens per patient |
| **Compute (per analysis)** | $2,400-10,400 | $24-104 × 100 patients |
| **Support & Maintenance** | $10,000 | Updates, bug fixes, monitoring |
| **Training & Documentation** | $5,000 | Initial year only |
| **Total Annual** | **$29,500-37,400** | |

**Savings:** $600,000 (traditional) - $37,400 (MCP) = **$562,600/year**

### Production Deployment (500 Patients/Year)

| Cost Category | Annual Cost | Notes |
|--------------|-------------|-------|
| **GCP Infrastructure** | $24,000 | Scaled compute resources |
| **Claude API Tokens** | $500-1,000 | Claude tokens per patient |
| **Compute (per analysis)** | $12,000-52,000 | $24-104 × 500 patients |
| **Support & Maintenance** | $20,000 | Dedicated support engineer |
| **Epic FHIR Integration** | $15,000 | Initial setup + maintenance |
| **Total Annual** | **$71,500-111,000** | |

**Savings:** $3,000,000 (traditional) - $111,000 (MCP) = **$2,889,000/year**

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## Investment Tiers & Returns

### Tier 1: Pilot ($50,000)

**Initial Investment:**
- Infrastructure setup: $15,000
- 3 production servers deployment: $10,000
- Training & documentation: $10,000
- 6-month pilot program: $15,000

**Year 1 Returns (100 patients):**
- Savings: $562,600
- ROI: **11.3x return**
- Payback: **1 month**

**5-Year NPV (assuming 100 patients/year):**
- Cumulative savings: $2.8M
- Cumulative costs: $187K
- **Net value: $2.6M**

### Tier 2: Production ($75,000/year)

**Annual Investment:**
- Full 17-server deployment: $25,000
- Epic FHIR integration: $15,000
- Hospital IT coordination: $20,000
- Training (20 users): $15,000

**Year 1 Returns (500 patients):**
- Savings: $2,889,000
- ROI: **38.5x return**
- Payback: **<2 weeks**

**5-Year NPV (assuming 500 patients/year):**
- Cumulative savings: $14.4M
- Cumulative costs: $555K
- **Net value: $13.8M**

### Tier 3: Multi-Site ($150,000/year)

**Annual Investment:**
- 3-5 hospital deployment: $75,000
- Multi-site coordination: $30,000
- IRB support & publications: $25,000
- Advanced features development: $20,000

**Year 1 Returns (2,500 patients across 5 sites):**
- Savings: $14,445,000
- ROI: **96.3x return**
- Payback: **<1 week**

**5-Year NPV (assuming 2,500 patients/year):**
- Cumulative savings: $72.2M
- Cumulative costs: $750K
- **Net value: $71.5M**

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## Time Savings Analysis

### Bioinformatician Time Freed

**Traditional Approach:**
- 100 patients × 40 hours = **4,000 hours/year**
- Equivalent to **2 full-time bioinformaticians**

**MCP Platform:**
- 100 patients × 2 hours (oversight) = **200 hours/year**
- **3,800 hours freed** for novel research

**Value of Freed Time:**
- 3,800 hours × $175/hour average = **$665,000/year**
- Can support **2-3 additional research projects**

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## Clinical Impact: Faster Treatment Decisions

### Time to Actionable Results

| Stage | Traditional | MCP DRY_RUN (demo) | MCP Production |
|-------|------------|-------------------|----------------|
| Clinical & Genomic | 12-20 hours | 4-6 min | 15-30 min |
| Multi-omics integration | 12-16 hours | 5-8 min | 30-60 min |
| Spatial analysis | 8-12 hours | 4-6 min | 45-90 min |
| Imaging analysis | 4-8 hours | 3-5 min | 40-90 min |
| Report generation | 4-8 hours | 5-8 min | 15-30 min |
| **Total** | **40-64 hours** | **25-35 min** | **2-5 hours** |

**Clinical Benefit:**
- **Same-day results** vs. 5-8 business days
- Faster treatment initiation = **improved patient outcomes**
- Reduced time to clinical trial enrollment

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## Scalability Analysis

### Cost per Patient by Volume

| Annual Volume | Cost per Patient | Total Annual Cost | Annual Savings |
|--------------|------------------|-------------------|----------------|
| 50 patients | $748 | $37,400 | $281,300 |
| 100 patients | $374 | $37,400 | $562,600 |
| 250 patients | $284 | $71,000 | $1,479,000 |
| 500 patients | $222 | $111,000 | $2,889,000 |
| 1,000 patients | $186 | $186,000 | $5,814,000 |

**Key Insight:** Economies of scale kick in at 250+ patients/year

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## Risk-Adjusted ROI

### Scenarios & Probabilities

| Scenario | Probability | Year 1 Savings (100 patients) | Expected Value |
|----------|-------------|------------------------------|----------------|
| **Best Case** (Full adoption) | 30% | $562,600 | $168,780 |
| **Base Case** (80% adoption) | 50% | $450,080 | $225,040 |
| **Worst Case** (50% adoption) | 20% | $281,300 | $56,260 |

**Expected Value (100 patients):** **$450,080**
**ROI (risk-adjusted):** **9.0x return** on $50K investment

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## Comparison to Alternative Solutions

### Traditional Bioinformatics Pipeline

**Pros:**
- Highly customizable
- No external API dependencies
- One-time development cost

**Cons:**
- 40+ hours per patient
- Requires PhD-level expertise
- Hard to maintain across multiple data types
- Not accessible to clinicians

**Cost:** $6,000-9,000 per patient

### Commercial Precision Medicine Platforms

**Examples:** Foundation Medicine, Tempus, Guardant Health

**Pros:**
- Clinically validated
- Comprehensive reports
- CLIA/CAP certified

**Cons:**
- Limited to genomics (no spatial/imaging integration)
- $3,000-7,500 per test
- Black-box algorithms
- No natural language interface

**Cost:** $3,000-7,500 per patient (genomics only)

### MCP Platform (This Solution)

**Pros:**
- Multi-modal synthesis (genomics + spatial + imaging + clinical) analyzed together — previously infeasible at scale
- Clinician-in-the-Loop: every result requires APPROVE/REVISE/REJECT before clinical use
- Natural language interface — no coding required for complex bioinformatics tools
- HIPAA-compliant with de-identification, 10-year audit trails, VPC isolation
- 2-5 hours per patient production (vs. 40 hours traditional); 25-35 min DRY_RUN demo
- Open source and transparent

**Cons:**
- Requires initial infrastructure setup (GCP org + Azure AD prerequisites may add 3-6 months)
- 2 of 17 servers are mocked (see [Server Registry](../reference/shared/server-registry.md)); real data available via external connectors
- Not yet FDA-approved or clinically validated on real patient data
- Depends on commercial AI APIs (Claude/Gemini) — mitigated by dual-provider support
- Cost savings are modeled projections, not yet measured in production

**Cost:** $324-702 per patient (all modalities) — projected, pending validation

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## Non-Financial Benefits

### Research Productivity
- **2-3 additional projects per year** per bioinformatician
- **Faster grant deliverables** = higher renewal rates
- **More publications** from freed research time

### Patient Care
- **Same-day treatment decisions** vs. 5-8 days
- **Broader access** to precision medicine (more patients can afford analysis)
- **More personalized** treatment recommendations

### Institutional Reputation
- **Cutting-edge technology** adoption
- **AI-augmented bioinformatics** leadership position
- **Attract top researchers** and clinicians

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## Sensitivity Analysis

### Key Variables

| Variable | Impact on ROI | Sensitivity |
|----------|---------------|-------------|
| **Patient volume** | High | +10% volume = +$56K savings |
| **Traditional analysis cost** | High | +$1,000 cost = +$100K savings |
| **GCP compute costs** | Low | +20% cost = -$2K savings |
| **Claude API costs** | Very Low | +100% cost = -$100 savings |
| **Adoption rate** | Medium | +10% adoption = +$56K savings |

**Most Critical Factor:** Patient volume (economies of scale)

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## Funding Recommendations

### For Academic Medical Centers
**Recommended Tier:** Production ($75K/year)
- 500+ cancer patients per year
- Research publications important
- Training bioinformaticians a priority

### For Community Hospitals
**Recommended Tier:** Pilot ($50K)
- 50-100 patients per year
- Prove value before full investment
- Reduces minimum viable team from ~10 FTEs to ~3 (the key enabler for community hospitals)
- Partner with academic center

### For Multi-Hospital Systems
**Recommended Tier:** Multi-Site ($150K/year)
- Economies of scale across 3-5 sites
- Shared infrastructure and training
- Collaborative research opportunities

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## Questions for Evaluation

1. **What is your current annual volume** of patients requiring precision medicine analysis?
2. **What is your current cost** per patient for multi-omics analysis?
3. **How many bioinformaticians** are currently doing manual analyses?
4. **What is your average time** from sample collection to treatment decision?
5. **Do you have existing GCP infrastructure** or need new setup?

Contact us to discuss your specific institutional needs and ROI projections.

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**Related Resources:**
- 📊 [Executive Summary](EXECUTIVE_SUMMARY.md)
- 💰 [Funding Opportunities](./FUNDING.md)
- 🏥 [Hospital Deployment Guide](../for-hospitals/README.md)

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**Last Updated:** 2026-02-24
