A
GLP-1 Side Effect Self-Tracker
3.85
Derivation Chain
Step 1
Novo Nordisk obesity drug competition intensifying
→
Step 2
Side effect monitoring needs for weight-loss medication users
→
Step 3
Tool for users to log and track daily side effects and share with doctors at appointments
Problem
The number of GLP-1 weight-loss medication users (Wegovy, Mounjaro, etc.) is surging, but there's no systematic way to log side effects like nausea, vomiting, and constipation — so patients report vaguely at appointments ('my stomach was a bit off yesterday'). Doctors can't obtain the side effect frequency, severity, and pattern data needed for dosage adjustments, leading to conservative prescribing and unnecessarily prolonged dose escalation periods (averaging 2–4 extra weeks).
Solution
Users log daily side effects in under 1 minute (symptom type, severity 1–10, linked to meals and exercise). The app auto-generates weekly trend charts by dosage period and a visit-ready summary report for their doctor. Reports can be shared via KakaoTalk or QR code, and dose escalation timing recommendation alerts are also provided.
NUMR-V Scores
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 (78%)
Data Availability
23.1/25
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 (59/100)
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 [low]
AI/ML [low]