App overview & operator
π± App Overview
This app is an AI-assisted pharmaceutical consultation tool that recommends over-the-counter (OTC) medicines in a chat format based on users' symptoms, physical condition, and lifestyle.
By combining proprietary algorithms with large language models, we aim to safely and flexibly recommend appropriate over-the-counter medicines for symptoms, creating an environment where everyone can practice self-medication with confidence.
π― Development Background
With aging population, increasing foreign tourists, and the spread of e-commerce sites, the demand for self-medication is growing year by year. However, language barriers and staff shortages prevent users from selecting appropriate medicines, raising safety concerns. Having worked at a drugstore myself, I have faced challenges with elderly people's varying hearing and comprehension abilities and language barriers for foreigners. To solve these issues, I developed a unique chat-based consultation tool that combines large language models with pharmaceutical knowledge.
π― Purpose
This app aims to help users correctly understand their symptoms and safely select appropriate over-the-counter medicines.
Through chat-based dialogue, we present over-the-counter medicine candidates and consultation guidelines for symptoms to promote self-medication.
It is also designed to be used as reference information before visiting pharmacies or making online purchases, and plays a role in helping with early medical consultation decisions.
This app does not replace diagnosis or guidance by doctors or pharmacists, but is positioned as a tool to assist users in making safe decisions.
π₯ Target Users
- General consumers who don't know which medicine to choose
- People who are too busy to visit pharmacies or residents of remote areas
- Foreign visitors who have difficulty consulting due to language barriers
- Elderly people and those with varying hearing and comprehension abilities
- Users considering purchases on e-commerce sites or online pharmacies
π― Key Features
- Natural Chat-based Consultation
Even without specialized knowledge, simply input symptoms in conversation format to get medicine recommendations. - Safety Assurance through AI Γ Pharmaceutical Knowledge
Combines pharmaceutical databases, pharmaceutical knowledge, and AI models for safe design that suppresses misinformation. - Medical Consultation Recommendation System
When dangerous symptoms or serious diseases are suspected, AI automatically recommends medical consultation. - Multi-language and Multi-environment Support
Planned support for Japanese, English, Chinese, and other languages.
Available on smartphones, tablets, PCs, and all devices and environments (iOS/Android/Windows/macOS/Chrome/Safari, etc.). - Secure Data Management
Input information is anonymized and not used for purposes other than medicine recommendations.
User privacy is the top priority in design.
πͺ App Strengths & Differentiators
- Balance of safety and flexibility through combined use of AI and proprietary algorithms
- Fusion of evidence-based recommendations and natural language understanding (LLM) dialogue capabilities
- Direct solution to on-site challenges such as staff shortages, language barriers, and information gaps
- Operability that anyone can use without confusion through simple UI design and easy introduction
βοΈ Proprietary Algorithm
The "Medicine Selection Algorithm," which is the heart of this app, consists of a proprietary algorithm that flexibly understands language through large language models and comprehensively evaluates elements such as drug efficacy, contraindications, user attribute information, and symptoms.
This enables evidence-based medicine selection rather than simple AI responses. AI responses always include "source information" and "warnings" to allow users to make their own judgments.
π οΈ Development Environment & Tools
- Backend: Python 3.9+, FastAPI (production web/API, ASGI), Jinja2 (templates), MeCab (Japanese morphological analysis)
- AI/NLP: OpenAI API (GPT-4o, GPT-4o-mini, etc.), rule-based NLU (hybrid recommendation system)
- Translation API: DeepL API (Multi-language support: Japanese, English, Chinese, Korean, high-speed translation)
- Database: PostgreSQL (Feedback persistence, session management, multi-instance support)
- Data Processing: Pandas, NumPy
- Frontend: HTML5, CSS3, JavaScript (ES6+), Vanilla JavaScript (no framework), Responsive Design
- Deployment: Google Cloud (e.g. Cloud Run); Gunicorn + uvicorn.workers.UvicornWorker (ASGI workers)
- Monitoring & Logging: psutil, JSONL format (structured logs), access analysis, performance monitoring
- Version Control: Git (GitHub)
π Future Outlook
We aim to strengthen collaboration with pharmacies, medical institutions, and local governments to utilize this as a digital support platform for regional healthcare.
We also plan expansions such as e-commerce site integration and medication guidance support functions to provide value to both users and sellers.
Ultimately, the goal of this app is to realize a society where "everyone can safely choose medicines anywhere."
π Pharmaceutical Database Sources
The pharmaceutical information used in this app references databases from the following public institutions:
- Japan Pharmaceutical Manufacturers Association (http://www.fpmaj.gr.jp)
- Japan Pharmaceutical Information Center (JAPIC) (https://www.japic.or.jp)
- Pharmaceuticals and Medical Devices Agency (PMDA) (https://www.pmda.go.jp)
π¨ Image Copyright
The copyright of illustrations used in this app belongs to Sofukore (Individual Operator), Tegakiz (γ¦γγγ£γ), and shigureni.
This app is for informational purposes only and is not medical advice. Please consult with a pharmacist or doctor when using medicines.
π€ Operator Information
Contact Information
Contact Email: weary-scoots.7y@icloud.com
Bug Report & Inquiry Form: https://forms.gle/UB8kZHd4VHenmRUN6
Technical Information
Development Languages & Technologies: Python 3.9+ / FastAPI (production ASGI) / MeCab (Japanese morphological analysis) / OpenAI API (GPT-4o, GPT-4o-mini, etc.) / DeepL API / PostgreSQL / Pandas / NumPy / HTML5 / CSS3 / JavaScript (ES6+)
Development Repository: https://github.com/32Lwk
Deployment: Google Cloud (e.g. Cloud Run) / Gunicorn + UvicornWorker (ASGI)
Publication Purpose
To support over-the-counter medicine selection and promote safe and easy medicine selection