Aptamer Therapeutics is a biotech startup innovating in smart drug delivery through AI and biosensor integration. While their flagship product utilizes microneedle-based systems, this project focuses exclusively on developing a supporting AI system for dose prediction that can be integrated with various delivery mechanisms in the future.

Aptamer Therapeutics is developing a web-based AI application to calculate optimal drug dosages based on individual patient characteristics, including sex, weight, and age. This project will involve building a prototype that can interpret input values and suggest safe and effective medication dosage ranges in real-time.

Project Topics

• Artificial Intelligence
• Web Development
• HealthTech
• UX/UI Design
• Data Science & Machine Learning
• Software Prototyping

Project Details

Overview:

Students will help design and develop a responsive web application that uses AI logic or rules-based algorithms to calculate personalized medication dosages based on a patient’s biological inputs (e.g., sex, weight, age). The goal is to reduce overdose/underdose risks while maintaining efficacy.

Key Tasks:

• Research dosage ranges for selected medications
• Build AI logic (rules-based or ML model) to estimate minimum and maximum safe doses
• Develop a simple web front-end for input/output
• Ensure algorithm explains dose logic (transparency)
• Test input-output flow and ensure accuracy of dosage recommendations

Deliverables:

• A functional prototype of the AI-powered dosage web application
• Documentation of AI logic used for predictions (rules or ML model)
• Testing report with use case validation
• UX wireframes and basic UI
• Final presentation and hand-off materials

Student Experience Level:

Intermediate to Advanced — Some experience with web development and data modeling preferred

Tools/Technologies Used:

• Python or JavaScript (for AI logic)
• Web frameworks like Flask, Django, or React
• UI tools (Figma, Bootstrap, etc.)
• GitHub for version control
• Optional: TensorFlow or scikit-learn if machine learning is used

Learning Outcomes

Students will:

• Learn how to develop and implement AI for real-world health applications
• Gain experience building full-stack web apps for medical use cases
• Understand user experience needs for health tech tools
• Interpret pharmacological data and apply it to software logic
• Work with a startup innovating in personalized healthcare

Project Timeline

• Ideal Start Date: Flexible
• Duration: 6–8 weeks
• Hours per Week: 6–10 hours/week
• Suggested Milestones:

1. Week 1–2: Research medication logic + define MVP scope
2. Week 3–4: Build and test AI engine + wireframes
3. Week 5–6: Build front-end and integrate with back-end
4. Week 7–8: Testing, documentation, and final demo

Student Interaction

• Weekly Zoom or email check-ins with Aptamer's CEO or project manager
• GitHub repo access and live shared docs
• Midpoint feedback session and final demo presentation

Eligibility / Prerequisites (Optional)

Ideal candidates will:

• Have experience with Python, JavaScript, or web app development
• Understand basic pharmacology or be open to quick research
• Be comfortable working with data or healthcare-related variables