Reimagining psoriasis care through AI-powered digital therapeutics
"It starts with a single patch. Then another."
25 patient interviews · 12 provider interviews · 75+ studies reviewed
"I have 4 different creams, and I can never remember which one goes where. By the time I figure it out, 20 minutes have passed."
"I canceled my beach wedding because I didn't want people staring at my arms in photos forever."
"I can't tell if I'm actually getting better or if I'm just used to seeing it."
"Is it stress? Diet? Weather? I have no idea what makes it worse. It feels random."
A 37-percentage point discrepancy between perceived and actual adherence. This invisibility prevents effective intervention.
15 apps analyzed using MARS-G framework
125 million patients. Three critical failures.
5 core principles guiding every design decision
Evidence-based features validated by research, not just intuitive UI
Shift from tracking what happened to predicting what will happen
Address bio-psycho-social complexity, not just visible symptoms
Design for B2B2C model, enabling clinical collaboration
Accessibility, health equity, and digital divide from Day 1
Synthesized from 25 in-depth patient interviews
"I'm so busy that I forget to apply my creams until I'm already in bed"
"I've had psoriasis for 20 years—another app won't cure me"
"I want to understand my body's patterns and optimize naturally before resorting to medications"
18-month systematic design methodology
Four core innovations. Click to explore.
3 rounds · 45 participants · iterative improvement
WCAG AA compliant · Inter typeface · Calming color palette
Reusable components from the PsoriAssist iOS prototype
Color selection with real-time contrast checking and accessibility validation
Inline and modal expansion modes for content hierarchy
Collapsible sections for progressive disclosure
Watch each feature in action
Quick actions on the home screen provide one-tap access to the most common tasks. The "Take Photo" button is prominently placed because consistent photo documentation is the foundation of effective psoriasis tracking.
Smart notifications arrive at the optimal time based on your routine. Research shows topical medication adherence drops to 30% within weeks—our reminder system is designed to break that cycle.
Our machine learning model continuously analyzes your data—photo history, medication adherence, weather patterns, and stress indicators—to identify early warning signs of an approaching flare-up.
HIPAA-compliant · Scalable · AI/ML pipeline
Interactive prototypes. Try them yourself.
Full iOS 17 prototype with 8 interactive screens. Swipe to navigate, pull to refresh.
Evolution from MVP to comprehensive digital health platform
Interested in collaborating on digital health solutions?