Chronic Condition Drug-Food Interaction Alert

3.55

Derivation Chain

Step 1 Longitudinal tracking and interpretation of Health Checkup results

→

Step 2 The problem of starting medication after a chronic disease diagnosis from a checkup

→

Step 3 The problem of unknowing exposure to risks from interactions between medications and everyday foods/supplements

Problem

A 52-year-old patient with hypertension and diabetes takes 3–5 daily medications (aspirin, metformin, blood pressure drugs, etc.) without knowing how they interact with common foods and supplements (grapefruit, green juice, red ginseng, omega-3, etc.). Grapefruit can raise calcium channel blocker (blood pressure medication) blood levels to dangerous amounts; vitamin K-rich green juice reduces warfarin efficacy; and red ginseng interacts with blood pressure medications. Pharmacists explain individual interactions, but there is no way to check the combined risk of 'today's food + supplements + medications' in real time. Tens of thousands of ER visits per year among those aged 50+ result from harmful combinations.

Solution

Users input their current medication list (by name or photo capture), and the service analyzes drug-drug interactions and generates a list of foods and dietary supplements to avoid. When users log a meal or supplement, the system instantly displays that day's combination risk using a traffic light system (green/yellow/red). When a dangerous combination is detected, it recommends alternative foods.

Target: Ages 45–60, taking 3+ medications for at least one chronic condition (hypertension, diabetes, hyperlipidemia), also taking dietary supplements

Revenue Model: Interaction lookup for up to 3 medications free. Full medication + food + supplement integrated analysis for 1,900 KRW/month (~$1.40). B2B for pharmacies and dietary supplement companies.

Ecosystem Role: Consumer

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

3.0/5

U Urgency

5.0/5

M Market

4.0/5

R Realizability

3.0/5

V Validation

3.0/5

NUMR-V Scoring System

N Novelty	1-5	How uncommon the service is in market context.
U Urgency	1-5	How urgently users need this problem solved now.
M Market	1-5	Market size and growth potential from proxy indicators.
R Realizability	1-5	Buildability for a small team with realistic constraints.
V Validation	1-5	Validation signal quality from competition and demand data.

SaaS N=.15 U=.20 M=.15 R=.30 V=.20 Senior N=.25 U=.25 M=.05 R=.30 V=.15

Feasibility (65%)

Tech Complexity

24.0/40

Data Availability

20.8/25

MVP Timeline

20.0/20

API Bonus

0.0/15

Feasibility Breakdown

Tech Complexity	/ 40	Difficulty of core implementation stack.
Data Availability	/ 25	Practical availability and cost of required data.
MVP Timeline	/ 20	Expected time to ship a usable MVP.
API Bonus	/ 15	Bonus for viable public API leverage.

Market Validation (51/100)

Competition

8.0/20

Market Demand

6.2/20

Timing

14.0/20

Revenue Signals

7.5/15

Pick-Axe Fit

10.5/15

Solo Buildability

5.0/10

Validation Breakdown

Competition	/ 20	Signal quality from competitor landscape.
Market Demand	/ 20	Demand proxies from search and mention patterns.
Timing	/ 20	Fit with current shifts in tech, behavior, and regulation.
Revenue Signals	/ 15	Reference evidence for monetization viability.
Pick-Axe Fit	/ 15	How well the concept serves participants in a trend.
Solo Buildability	/ 10	Practicality for lean-team implementation.

Technical Requirements

Frontend [medium] Backend [medium] Data Pipeline [medium]

Dashboard