ChemoBuddy
Developed in collaboration with Mayo Clinic Oncology, a companion app for cancer patients, designed for their lowest-energy moments.
Mayo Clinic Observership Awardee
Category
Healthcare
Client
Mayo Clinic
Duration
10 Weeks
Tool
Figma
Background
Meet ChemoBuddy
ChemoBuddy is a patient-centered digital companion for people undergoing chemotherapy, developed as a Mayo Clinic Observership project in collaboration with Mayo Clinic Oncology. The concept started from a simple observation: chemotherapy patients are handed hundreds of pages of generic information at exactly the moment they have the least energy, focus, and emotional bandwidth to use it. ChemoBuddy closes that gap by reducing cognitive load, offering just-in-time guidance, and helping patients manage symptoms and treatment between clinical visits.
Outcomes
What Changed
95%
of participants completed the core tasks in the prototype without assistance
40%
reported feeling less anxious navigating the experience than with traditional information sources
30%
increase in accuracy when logging and describing symptoms using the visual tracker
85%
longer engagement during testing sessions, average interaction time rose from 4.2 to 7.8 minutes
Problem
The Weight of a Bad Day
Chemotherapy patients navigate far more than medical treatment; the emotional and cognitive weight of the disease compounds over time. Five problems kept surfacing:
Design challenge
How might I design an experience that helps chemotherapy patients understand and manage their treatment when their energy, focus, and emotional capacity are at their lowest?
My role
Where I Came In
I led end-to-end research and design for ChemoBuddy, from literature review, competitive analysis, and role-play research to persona development, ideation, and low- and high-fidelity design. My oncology mentor, Dr. Umar, served as my clinical sounding board throughout: he helped simulate patient and caregiver scenarios without direct patient access and reviewed the accuracy of the symptom guidance in the final product.
My contribution
What I owned
Working within a 7-person team, these were the three pieces I owned end to end from concept through clinical validation.
Multimodal education content
Designing the education library so patients could learn the same information through video, text, or audio, depending on what they had the energy for.
Symptom tracking
Designing the logging flow and severity indicators that helped patients tell the difference between "watch this" and "call someone."
Chatbot experience
Scoping and designing the conversational flow as an educational, supportive layer only, working with Dr. Umar's clinical review to keep every response appropriate.
Research
Research Without a Waiting Room
A 10-week effort to understand how chemotherapy patients absorb information, manage fear, and lean on the people around them.
I worked through three tracks in parallel: a literature review, a competitive teardown of existing tools, and structured role-play with my oncology mentor to simulate what patients and caregivers actually go through. What started as a goal to simplify patient education became something bigger: understanding how people process information and depend on others when they're at their lowest.
Literature Review
Week 1–2
Competitive Analysis
Week 3
Role-Play Research
Week 4-5
Data Synthesis
Week 6-7
Literature review
Before sketching a single screen, I wanted to know what the research already said about how chemotherapy patients process information and engage with digital health tools.
What are mHealth cancer apps doing well, and where are they falling short for patients managing treatment day to day?
How does symptom tracking affect patient-reported outcomes during chemotherapy?
Does digital patient education actually improve treatment adherence, or just information recall?
Where can a chatbot contribute safely and usefully in an oncology context, and where should it stop?
Reviewed 11 peer-reviewed oncology studies and digital health journals focusing on: mHealth cancer apps, symptom management & patient-reported outcomes (PROs), digital education tools and treatment adherence, and early experiments with chatbots in oncology.
Key findings
INSIGHT 1
Health literacy alone doesn't guarantee patients follow a plan when information is complex or emotionally charged.
INSIGHT 2
Multimodal education, audio, video, and simplified text, leads to significantly higher engagement than text-only formats.
INSIGHT 3
Chatbots work best as educational and supportive tools, not diagnostic engines.
Key research insights
What the Research Was Really Saying
How information is delivered matters as much as what it says
of participants completed the core tasks in the prototype without assistance
Existing tools are fragmented and reactive
reported feeling less anxious navigating the experience than with traditional information sources
Patients want a clear next step, and fatigue sets in fast
increase in accuracy when logging and describing symptoms using the visual tracker
Chatbots work best as educational and supportive tools
longer engagement during testing sessions, average interaction time rose from 4.2 to 7.8 minutes
From insight to feature
Mapping the flow
Low-fidelity wireframes
I built low-fidelity wireframes to test layout, navigation, and information hierarchy specifically against the cognitive and emotional state of a chemotherapy patient, not just to sketch the interface. This is where the conversational-onboarding decision took shape, and where I mapped the core flows: onboarding, dashboard, chatbot, symptom tracking, and patient profile, before investing in visual design.
What Shipped
High-fidelity design, with goals
The final visual system carried through the same principles: calm, predictable, accessible, easy to scan.
Onboarding - A Calm Start
Dashboard - Personalized Treatment Overview
Chatbot - Context-Aware Support
Symptom Tracking - Making Self-Monitoring Easier
Patient Profile - Centralizing Essential Info
Future scope
Role-based caregiver access - Structured permission levels so caregivers get exactly the visibility they need, without exposing the patient's full record.
Real-time data sync - Direct connection to hospital systems so treatment updates, appointments, and reports stay current without manual entry.
Cross-device support - Extending the same experience beyond mobile, so patients can access it wherever's most convenient for them.
