EPIC-X 2026 Grant Application: Gap Analysis & Prioritization

Generated: 2025-12-22 Status: Phase 2 of Quality Review Verification

Executive Summary

This document categorizes all missing data identified in the quality review checklist by impact on evaluation scoring and identifies quick wins that can be filled immediately from existing company systems.

Overall Status: 71% Complete, 29% Data Gaps

• Quick Wins Available: 12 data points can be filled immediately
• Critical Blockers: 8 data points preventing submission
• High-Value Data: 15 data points improving scoring
• Supporting Data: 10 data points enhancing narrative

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Category 1: CRITICAL BLOCKERS (Prevent Submission)

These gaps must be filled before submission. Without them, the application is incomplete or contains unverifiable claims.

Gap	Section	Impact	Data Source	Owner	Est. Hours
PC-042 Fitzpatrick equity data	2, 6	10 pts	MISSING - Referenced 5 times but doesn't exist	Medical Data Science	4h
Historical revenue 2022-2024	3	5 pts	Finance team financial statements	CFO	0.5h
Revenue projections 2025-2027	3	5 pts	Finance team financial model	CFO	1h
Management team details (5 leaders)	4	8 pts	HR records + LinkedIn	HR + Leadership	2h
Clinical study identification (which 7?)	2	8 pts	Clinical team clarification	Clinical Lead	1h
ISO 13485 certificate number & date	4	3 pts	Regulatory files	Regulatory Lead	0.5h
CE MDR certificate number & date	4	3 pts	Regulatory files	Regulatory Lead	0.5h
FDA 510(k) predicate device	2	3 pts	FDA submission documents	Regulatory Lead	0.5h

Total Critical Blockers: 8 gaps, 45 points at stake, ~12 hours to resolve

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Category 2: QUICK WINS (Can Fill Immediately)

These data points exist in company systems (Holded, Factorial, implementation plans) and can be filled without additional research.

Gap	Current Value in Application	Actual Value in System	Source	Action Required
Hospital contract values	"EUR 192K+ in contracts"	EUR 600K+ in contracts	Holded invoices (Janssen EUR 220K+, Boehringer EUR 127K, Sagimet EUR 156K)	Update Section 3 with accurate totals
Team size (FTEs)	"31 FTEs" (unverified)	28 active FTEs	Factorial employee list (62 total, 28 active)	Verify and update Section 4
Team gender composition	"UPDATE: % women"	~39% women (11 women / 28 active)	Factorial employee data	Fill Section 4 diversity table
Women in leadership	"UPDATE: % women in leadership"	~40% women in leadership (Andy + 10 women identified, need role breakdown)	Factorial + org chart	Fill Section 6 table
Current office location	Generic "Spain"	Bilbao, Basque Country, Spain	Company records	Update Section 4
Company founding date	Not explicitly stated	2019 (inferred from clinical studies)	Corporate records	Add to Section 1
Clinical study patient counts (partial)	"UPDATE: n patients per study"	Partial data available: JNJ_2025 (250 patients), JNJ_2025_RETRO (85K images)	Implementation plans GP-009/r-009-001	Fill available counts, mark others for clinical team
AEMPS license number	"UPDATE: AEMPS license #"	ES-MD2021-0027 (confirmed)	Regulatory files	Fill Section 2
MHRA registration	"UK MHRA registered"	Needs specific reg #	Regulatory files	Request from Regulatory team
ANVISA registration	"Brazil ANVISA registered"	Needs specific reg #	Regulatory files	Request from Regulatory team
Board Chair appointment date	"UPDATE: date Andy joined Board"	Needs confirmation	Corporate minutes	Request from Andy/Legal
LinkedIn metrics	"UPDATE: followers/engagement"	Can be retrieved immediately	Andy's LinkedIn profile	Request from Andy

Total Quick Wins: 12 data points, can be completed in 2-3 hours with data already in systems

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Category 3: HIGH-VALUE DATA (Improve Scoring)

These gaps significantly impact evaluation scores but require coordination with technical teams.

Gap	Section	Impact	Data Source	Owner	Est. Hours
SOTA melanoma accuracy benchmark	2	4 pts	Medical literature review	Medical Data Science	2h
SOTA psoriasis accuracy benchmark	2	4 pts	Medical literature review	Medical Data Science	2h
Gender performance comparison (4 conditions)	2	5 pts	Validation study re-analysis	Medical Data Science	3h
Clinical publication citations (6+ papers)	3	5 pts	Clinical team bibliography	Clinical Lead	1h
Publication DOIs and impact factors	3	3 pts	Clinical team bibliography	Clinical Lead	1h
Customer retention rate	3	4 pts	Commercial team CRM analysis	Commercial Lead	1h
Market research source (TAM USD 4.7B)	3	3 pts	Commercial team records	Commercial Lead	0.5h
FHIR implementation details	2	4 pts	Engineering documentation	Engineering Lead	2h
CNN architecture specifics	2	4 pts	Engineering documentation	Engineering Lead	2h
Healthcare equity baseline metrics	3	4 pts	Public health data research	Medical Data Science	2h
AI bias testing methodology	2	5 pts	Validation protocol documentation	Medical Data Science	2h
Clinical study hospital names	2	3 pts	Clinical team records	Clinical Lead	1h
Clinical study exact dates	2	3 pts	Clinical team records	Clinical Lead	1h
Clinical study publication status	2	3 pts	Clinical team records	Clinical Lead	1h
Team diversity breakdown (technical roles)	4, 6	4 pts	HR records + role analysis	HR	1h

Total High-Value Data: 15 gaps, 57 points at stake, ~29 hours to resolve

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Category 4: SUPPORTING DATA (Enhance Narrative)

These gaps improve the quality and credibility of the narrative but have lower direct impact on scoring.

Gap	Section	Impact	Data Source	Owner	Est. Hours
Co-founder 2 details	4	2 pts	Cap table + LinkedIn	Legal/HR	0.5h
Co-founder 3 details	4	2 pts	Cap table + LinkedIn	Legal/HR	0.5h
Andy's Forbes category	6	1 pt	Forbes 30 Under 30 list	Andy	0.1h
Andy's speaking engagements 2023-2024	6	2 pts	Calendar/conference log	Andy	0.5h
Andy's media features	6	2 pts	PR team records	Andy/Marketing	1h
Andy's personal vision statement	6	3 pts	Andy's input	Andy	1h
Board strategic decision examples	6	2 pts	Board meeting minutes	Andy/Legal	1h
Specific hospital partnership examples	3	2 pts	Commercial team case studies	Commercial Lead	1h
Patient testimonials/quotes	3	2 pts	Clinical team records	Clinical Lead	1h
Regulatory authority correspondence	2	2 pts	Regulatory files	Regulatory Lead	1h

Total Supporting Data: 10 gaps, 20 points at stake, ~9 hours to resolve

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Impact Analysis by Section

Section 2 (Excellence & Innovation) - 40 Points Max

• Current Status: 75% complete (30/40 points secured)
• Critical Blockers: PC-042 (10 pts), Clinical study details (8 pts) = 18 pts at risk
• Quick Wins: AEMPS license (1 pt), Patient counts partial (2 pts) = 3 pts gain
• High-Value: SOTA benchmarks (8 pts), Gender performance (5 pts), AI bias testing (5 pts) = 18 pts potential gain
• Maximum Achievable: 40/40 points if all gaps filled

Section 3 (Impact & Market) - 25 Points Max

• Current Status: 64% complete (16/25 points secured)
• Critical Blockers: Historical revenue (5 pts), Projections (5 pts) = 10 pts at risk
• Quick Wins: Hospital contracts update (2 pts) = 2 pts gain
• High-Value: Publications (8 pts), Customer retention (4 pts), Market source (3 pts) = 15 pts potential gain
• Maximum Achievable: 25/25 points if all gaps filled

Section 4 (Implementation & Capacity) - 35 Points Max

• Current Status: 71% complete (25/35 points secured)
• Critical Blockers: Management team (8 pts), Certificates (6 pts) = 14 pts at risk
• Quick Wins: Team size (2 pts), Gender composition (3 pts) = 5 pts gain
• High-Value: Team diversity breakdown (4 pts) = 4 pts potential gain
• Maximum Achievable: 35/35 points if all gaps filled

Section 6 (Women Leadership) - 10 Points Max

• Current Status: 40% complete (4/10 points secured)
• Quick Wins: Board Chair date (1 pt), LinkedIn metrics (1 pt) = 2 pts gain
• High-Value: None specific to this section
• Supporting: Vision statement (3 pts), Speaking engagements (2 pts) = 5 pts gain
• Maximum Achievable: 10/10 points if all gaps filled

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Recommended Data Collection Sprint

Phase 1: IMMEDIATE (Today) - 3 Hours

Goal: Fill all quick wins with data already in company systems

1. Update contract values (30 min)

   • Extract Holded invoice totals
   • Update Section 3 with EUR 600K+ figure
   • Add specific customer names (Janssen, Boehringer, Sagimet)

2. Update team metrics (1 hour)

   • Confirm Factorial data: 28 active FTEs, ~39% women
   • Update Section 4 team size table
   • Fill Section 6 gender composition table
   • Identify women in leadership roles

3. Fill regulatory data (1 hour)

   • Add AEMPS license number: ES-MD2021-0027
   • Request MHRA and ANVISA reg numbers from Regulatory team
   • Add available patient counts from implementation plans

4. Update company details (30 min)

   • Add founding year: 2019
   • Update office location: Bilbao, Basque Country, Spain
   • Request LinkedIn metrics from Andy

Phase 2: CRITICAL (Next 2 Days) - 12 Hours

Goal: Resolve all critical blockers preventing submission

1. Medical Data Science Team (4 hours)

   • Priority 1: Resolve PC-042 discrepancy
     • Option A: Generate Fitzpatrick equity analysis from existing validation data
     • Option B: Remove PC-042 references and use alternative equity metrics
     • Option C: Acknowledge data limitation and provide roadmap

2. Finance Team (1.5 hours)

   • Provide 2022-2024 actual revenue
   • Provide 2025-2027 revenue projections with assumptions

3. HR + Leadership Team (2 hours)

   • Compile management team details:
     • CTO: Name, background, key achievements
     • Head of Medical Data Science: Name, background, key achievements
     • Head of Regulatory: Name, background, key achievements
     • Head of Commercial: Name, background, key achievements
     • CFO: Name, background, key achievements

4. Clinical Team (1 hour)

   • Identify which 7 implementation plans are clinical validation studies
   • Provide patient counts (n), exact dates, hospital names for each
   • Clarify publication status

5. Regulatory Team (0.5 hours)

   • Provide ISO 13485 certificate number and issue date
   • Provide CE MDR certificate number and clearance date
   • Provide FDA 510(k) predicate device name

6. Andy Aguilar (1 hour)

   • Confirm Board Chair appointment date
   • Provide personal vision statement (2-3 paragraphs on women in AI/healthcare)

Phase 3: HIGH-VALUE (Next 3-5 Days) - 29 Hours

Goal: Maximize evaluation score with high-impact data

1. Medical Data Science Team (13 hours)

   • SOTA benchmarks for melanoma and psoriasis
   • Gender performance comparison analysis (4 conditions)
   • AI bias testing methodology documentation
   • Healthcare equity baseline metrics research

2. Clinical Team (4 hours)

   • Compile 6+ publication citations with DOIs
   • Add hospital names and exact study dates
   • Confirm publication status

3. Engineering Team (4 hours)

   • Document FHIR implementation details
   • Specify CNN architecture (layers, parameters, training approach)

4. Commercial Team (2.5 hours)

   • Calculate customer retention rate from CRM
   • Cite market research source for TAM claim
   • Compile hospital partnership case studies

5. HR Team (1 hour)

   • Break down team diversity by technical vs. non-technical roles

Phase 4: SUPPORTING (Next Week) - 9 Hours

Goal: Enhance narrative quality and credibility

1. Andy Aguilar (3 hours)

   • Speaking engagements log 2023-2024
   • Media features list
   • Board strategic decision examples

2. Legal/HR (1 hour)

   • Co-founder 2 & 3 details from cap table

3. Marketing/Clinical/Regulatory (5 hours)

   • Patient testimonials
   • Regulatory authority correspondence examples

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Success Metrics

Milestone 1: Quick Wins Complete (Today)

• All 12 quick wins filled
• Section 3 updated with EUR 600K+ contracts
• Section 4 updated with 28 FTEs, ~39% women
• Section 6 updated with gender composition
• Completion status: 71% → 78%

Milestone 2: Critical Blockers Resolved (2 Days)

• PC-042 discrepancy resolved
• Historical revenue added
• Management team details complete
• Clinical studies identified and detailed
• All certificates numbered and dated
• Completion status: 78% → 92%

Milestone 3: High-Value Data Added (5 Days)

• SOTA benchmarks added
• Gender performance comparison added
• Publications cited
• Customer retention rate calculated
• Technical specifications documented
• Completion status: 92% → 100%

Milestone 4: Supporting Data Complete (7 Days)

• Andy's vision statement added
• Co-founder details added
• All narrative enhancements complete
• Final quality review passed
• Expected Score: 85-95 points (out of 100)

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Risk Assessment

HIGH RISK

• PC-042 Fitzpatrick equity data doesn't exist: Referenced 5 times in application. Must either generate analysis, replace with alternative metrics, or acknowledge limitation. Risk of credibility loss if not addressed.
  • Mitigation: Medical Data Science team priority task, 4-hour sprint
  • Backup: Use alternative equity metrics from existing validation data

MEDIUM RISK

• Clinical study vs. commercial contract confusion: Implementation plans mix validation studies with commercial deployments. Need clear delineation.
  • Mitigation: Clinical team 1-hour clarification session
  • Backup: Focus on the 7 studies with clearest validation protocols

LOW RISK

• Contract values understatement: Application claims EUR 192K+ but Holded shows EUR 600K+. Easily correctable, actually strengthens application.
  • Mitigation: Quick win, update today
  • Impact: Positive correction

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Recommendation

Execute 3-phase sprint:

1. Today: Fill all 12 quick wins (3 hours) → 78% complete
2. Next 2 days: Resolve 8 critical blockers (12 hours) → 92% complete
3. Next 3-5 days: Add high-value data (29 hours) → 100% complete

Total effort: 44 hours across 8 teams over 5 days

Expected outcome: 100% complete application with 85-95 point competitive score

Critical path: PC-042 resolution → Must decide today whether to generate, replace, or acknowledge