# Clinical Evidence Compiler

*/Opportunities/Clinical_Evidence_Compiler*

## Opportunity Overview

**Wedge**: Target mid-market medical device companies updating existing Class IIa and IIb clinical evaluation reports. This niche faces strict recurring deadlines and straightforward literature requirements, enabling fast proof of value and adoption. Expand subsequently into complex Class III pre-market approvals and eventually adjacent pharmaceutical systematic literature reviews.
**Timing**: Long-context large language models and citation-grounded retrieval architectures now reliably extract structured clinical endpoints from dense medical PDFs. This overcomes the hallucination barrier that previously blocked automated regulatory drafting.
**Why This I C P**: Mid-market MedTech regulatory teams face hard EU MDR compliance deadlines and lack the budget for massive internal clinical affairs headcounts. They rely heavily on expensive third-party consultancies, driving immediate willingness to adopt an automated alternative.
**Size Of Prize**: Roughly 30,000 global medical device manufacturers spend an average of $50,000 annually on specialized labor or external consultants for clinical literature compilation, creating a $1.5B addressable opportunity.
**Gap Narrative**: Regulatory affairs teams at medical device manufacturers spend hundreds of manual hours compiling Clinical Evaluation Reports to comply with regulatory requirements. Existing literature review tools serve academic researchers and fail to extract the specific safety and performance endpoints required for audit-ready compliance documents.
**Defensibility**: Defensibility stems from workflow lock-in and a compounding database of regulatory auditor feedback. As the system processes successful submissions, it maps specific Notified Body preferences to document structures, creating an increasingly specialized generation engine that generic models cannot replicate.
**Why This Thesis**: A Service-as-Software thesis aligns directly with the buyer mandate to produce a finalized, compliant document rather than adopt a new research tool. They buy the completed report, transferring the heavy lifting of literature screening and data extraction entirely to the system.

## Opportunity Linked Thesis

**Thesis**: [Agent](/Theses/Agent)

## Opportunity Linked I C P

**Icp**: [Medical Device Manufacturer](/CompanyTypes/Medical_Device_Manufacturer)

## Opportunity Market Sizing

_Illustrative — target and order-of-magnitude estimate figures, not an achieved track record (this Thing is concept-stage)._

**S A M**: ~$1.2B-$1.5B (US and EU mid-to-large medical device manufacturers facing complex MDR and FDA reporting requirements)
**S O M**: ~$30M-$50M
**T A M**: ~20,000 global medical device manufacturers × ~$150k/yr ≈ $3B
**Growth Rate**: ~12-18%/yr, driven by stricter EU MDR clinical evaluation requirements and expanded FDA post-market surveillance mandates
**Paid Comparable Spend**: ~$150k-$250k/yr spent on outsourced medical writers, regulatory consultants, and manual literature review tooling

## Opportunity Incumbents

- [DistillerSR](/Products/DistillerSR) — Tool
- [Veeva Vault Clinical](/Products/Veeva_Vault_Clinical) — Tool
- [Covidence](/Products/Covidence) — Tool
- [Contract Research Organizations](/Products/Contract_Research_Organizations) — Service
- [Microsoft Excel](/Products/Microsoft_Excel) — Spreadsheet
- [In-House Templates](/Products/In-House_Templates) — DIY

## Opportunity Win Conditions

**Kill Thresholds**:
- Citation error rate > 0.5% after first 30 days
- Manual edit ratio exceeds 40% of generated text
- Average time to produce a draft CER > 72 hours
- Fewer than 3 paid pilots converted at $50k+ annualized within 90 days
**Leading Metrics**:
- Time from data ingestion to first drafted Clinical Evaluation Report section
- Citation accuracy rate against source literature
- Manual edit ratio per 1000 generated words
- Number of literature sources processed per hour
- User sessions completing a full EU MDR formatting check
**What Proves Right**: Medical device regulatory affairs teams upload their post-market surveillance data and the system outputs draft Clinical Evaluation Reports that pass internal quality reviews without structural edits. Cohorts retain at over 85% after generating their third report and enterprise compliance teams execute $100k annual contracts for continuous surveillance automation.
**What Proves Wrong**: Regulatory writers spend more time fixing incorrect citations in the generated text than they would writing the documents from scratch. Compliance officers block deployment due to data lineage concerns and demand manual verification of every source before regulatory submission.

## Opportunity Build Profile

**Hardest Part**: Extracting structured safety and performance metrics from highly variable, unstructured academic PDFs, specifically nested tables, with absolute traceability to the source text and zero hallucination risk.
**Min Viable Scope**: Focus strictly on parsing PDFs to generate the State of the Art literature data extraction matrix for EU MDR Class IIa devices. Deliberately exclude automated narrative generation, post-market surveillance data integration, and direct submission portal connections.
**Cold Start Problem**: High-accuracy extraction requires thousands of manually annotated clinical papers mapped to regulatory reporting formats. Break this by partnering with medical writing consultancies to ingest their historical completed Clinical Evaluation Reports alongside the raw source literature as initial training pairs.
**Time To First Value**: 1-2 weeks; gated by uploading the initial literature search results and processing the first batch of PDFs into a validated extraction matrix.
**Data Moat Available**: true
**Technical Difficulty**: High

## Neighborhood

### Where the gap lives

- [Prior Authorization Specialist](/Agents/Prior_Authorization_Specialist) — latent gap · Agents

### Incumbent in

- [Microsoft Excel](/Software/Microsoft_Excel) — incumbent in · Software
- [In-House Templates](/Products/In-House_Templates) — incumbent in · Products
- [Veeva Vault Clinical](/Products/Veeva_Vault_Clinical) — incumbent in · Products
- [Contract Research Organizations](/Products/Contract_Research_Organizations) — incumbent in · Products
- [Covidence](/Products/Covidence) — incumbent in · Products
- [DistillerSR](/Products/DistillerSR) — incumbent in · Products

### Applies thesis

- [Medical Device Manufacturer](/CompanyTypes/Medical_Device_Manufacturer) — applies thesis · CompanyTypes

### Embodies

- [Agent](/Theses/Agent) — embodies · Theses

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