B

Chronic Disease Medication-Diet Integrated Rule Board

3.85

Derivation Chain

Step 1 Personalized chronic disease medication and diet management
→
Step 2 Checking dietary restriction conflicts across different prescriptions
→
Step 3 Generating integrated allowed/prohibited food rules by condition combination

Problem

A 56-year-old patient managing hypertension, diabetes, and hyperlipidemia simultaneously is prescribed an ARB (hypertension), metformin (diabetes), and a statin (hyperlipidemia). Hypertension calls for a low-sodium diet, diabetes requires low-carb, and hyperlipidemia demands low-fat. Designing meals that satisfy all three constraints requires cross-referencing each condition's guidelines, plus tracking drug-food interactions like the grapefruit-statin conflict. The result is that patients either give up on one guideline or fall into nutritional imbalance.

Solution

Users enter their conditions and current medications on a web interface, and the system generates integrated dietary rules (allowed/caution/prohibited foods) for their specific combination of conditions, with drug-food interaction warnings. It answers practical questions like 'Can I have pork belly for dinner tonight?' based on the user's conditions and medications. It operates on rule-based filtering, not nutritionist-level advice.

Target: Adults aged 50–65 managing 2 or more chronic conditions simultaneously, who feel confused about self-directed meal planning
Revenue Model: Up to 2 conditions free. 3+ conditions + full drug-food interaction database + weekly meal recommendations at KRW 3,900/month (~$3).
Ecosystem Role: Supplier
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
3.0/5
U Urgency
5.0/5
M Market
4.0/5
R Realizability
4.0/5
V Validation
3.0/5
NUMR-V Scoring System
N Novelty1-5How uncommon the service is in market context.
U Urgency1-5How urgently users need this problem solved now.
M Market1-5Market size and growth potential from proxy indicators.
R Realizability1-5Buildability for a small team with realistic constraints.
V Validation1-5Validation signal quality from competition and demand data.
Each dimension is scored 1-5 and weighted into grade S/A/B/C/D.
SaaS N=.15 U=.20 M=.15 R=.30 V=.20 Senior N=.25 U=.25 M=.05 R=.30 V=.15

Feasibility (69%)

Tech Complexity
29.3/40
Data Availability
20.0/25
MVP Timeline
20.0/20
API Bonus
0.0/15
Feasibility Breakdown
Tech Complexity/ 40Difficulty of core implementation stack.
Data Availability/ 25Practical availability and cost of required data.
MVP Timeline/ 20Expected time to ship a usable MVP.
API Bonus/ 15Bonus for viable public API leverage.
Total 100 points; below 50% is filtered out.

Market Validation (53/100)

Competition
8.0/20
Market Demand
6.2/20
Timing
14.0/20
Revenue Signals
9.0/15
Pick-Axe Fit
10.5/15
Solo Buildability
5.0/10
Validation Breakdown
Competition/ 20Signal quality from competitor landscape.
Market Demand/ 20Demand proxies from search and mention patterns.
Timing/ 20Fit with current shifts in tech, behavior, and regulation.
Revenue Signals/ 15Reference evidence for monetization viability.
Pick-Axe Fit/ 15How well the concept serves participants in a trend.
Solo Buildability/ 10Practicality for lean-team implementation.
Total 100 points; below 50 is filtered out.

Technical Requirements

Backend [medium] Frontend [low] Data Pipeline [medium]
Dashboard