DocStock

Final Feasibility Presentation

Roughly half of filled prescriptions are taken incorrectly, and nonadherence costs the U.S. an estimated $100–300 billion a year. DocStock is a smartphone and web app that turns a user's medications into one schedule with dose reminders, activity logging, refill alerts, and interaction checks. This deck covers the problem, the current versus proposed process flow, what the app will and will not do, how it compares to Medisafe, MyTherapy, and Round Health, the major functional components, and the customer, technical, security, and legal risks with their mitigations.

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Final version Team Pearl CS 410, Old Dominion University Fall 2026

Final Design Presentation

Where the feasibility presentation made the case for DocStock, the design presentation shows how it will be built. A work breakdown structure splits the project into user interface, algorithms, data management, and testing. Six algorithms, from dose scheduling to refill prediction, each get a description and a flow diagram, and an overview shows how much of each the prototype will build. A seven-table MySQL schema stores users, medications, schedules, dose history, supplies, notifications, and caregiver access. The real-world vs. prototype comparison spells out what the team will demo: login, medication setup, scheduling, reminders, refill alerts, and adherence reports. Drug interaction checking and caregiver support are saved for the full product. The deck closes with the first GUI mockups and user stories.

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Final version Team Pearl CS 410, Old Dominion University Fall 2026

Prototype Design Presentation

The prototype design presentation turns the design into a build plan. Based on feedback, caregiver support is now part of the prototype, and drug interaction checking will use a curated set of known interactions. The deck walks through a feature-by-feature real-world vs. prototype comparison, the major functional components, and the tools and technologies, then lays out an eight-sprint plan that builds DocStock from setup through final testing. It closes with risk charts that plot each risk by probability and impact.

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Working draft Team Pearl CS 410, Old Dominion University Fall 2026