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When AI-based neuroimaging analysis and neurotech Startups prepare for MFDS (Ministry of Food and Drug Safety) Medical device approval, determining whether their product is Class 2 or Class 3, whether clinical trials are required, and the scope of GMP certification takes 3-6 months and $15K-$37K in Legal and regulatory consulting fees.
Users input product type, functionality, target conditions, and data types. The system references MFDS medical device classification DB and prior approval case DB to automatically provide expected classification, approval pathway, required clinical trial scale, GMP requirements, and estimated timeline. Includes comparative analysis with actual approval timelines of similar products.
| 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. |
| 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. |
| 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. |