Problem Hypotheses

• Assumption: Patients actively search for trials beyond their doctor's advice.
  Risk: High
  Target: 60% of patients report self-searching.
• Assumption: Medical jargon on ClinicalTrials.gov prevents patients from understanding eligibility.
  Risk: Critical
  Target: 80% cite "understanding requirements" as top barrier.
• Assumption: Geographic/logistical barriers are a primary reason for dropout.
  Risk: Medium
  Target: 50% abandon due to distance/travel costs.

Solution Hypotheses

• Assumption: Patients trust AI to translate complex medical criteria accurately.
  Risk: Critical
  Target: 70% rate AI summary as "Helpful" or "Very Helpful".
• Assumption: Users are willing to input health data (FHIR or manual) for better matches.
  Risk: High
  Target: 40% complete onboarding questionnaire.
• Assumption: "Logistics Helper" (travel/hotels) is a deciding feature vs. just finding the trial.
  Risk: Medium
  Target: Feature ranks in top 3 desired needs.

Business Hypotheses

• Assumption: Patients will pay $9.99/mo for tracking and notifications.
  Risk: Critical
  Target: 5% conversion from free to paid.
• Assumption: Pharma/Hospitals value "qualified leads" over raw volume.
  Risk: High
  Target: 3 B2B partners express interest in pilot.
• Assumption: CAC via patient communities/support groups is viable.
  Risk: Medium
  Target: CAC < $15 via organic content.

Part 1: The Journey (15 min)

• • "Walk me through your diagnosis story. When did you first look for treatments beyond standard care?"
• • "Who is involved in your treatment decisions? Do you research alone or with a caregiver?"
• • "What is your biggest fear or frustration right now regarding your treatment options?"

Part 2: The Search (20 min)

• • "Tell me about the last time you searched for a clinical trial. Where did you go?"
• • "Show me (on your phone) how you currently search for health information. What do you type?"
• • "Describe a time you found a trial but couldn't join. What stopped you?"
• • "How do you feel when you read the 'Elibility Criteria' on government sites?"

Part 3: The Solution (15 min)

• • "If an app could translate medical jargon into plain English, how would that change your behavior?"
• • "Would you trust an AI to tell you that you qualify for a trial without a doctor reviewing it first?"
• • "What is more important: finding the 'best' trial globally, or one 'good enough' that is close to home?"

Part 4: Value & Money (10 min)

• • "Have you ever paid for a health app or service? Which one and why?"
• • "If this tool saved you 10 hours of research and found a viable trial, what would that be worth to you?"
• • "What would make you recommend this tool to a friend?"

Screening Questions (Top of Funnel)

Purpose: Filter for qualified users and build the research pool.

1. Which of the following best describes you? (Patient, Caregiver, Clinician)
2. Have you or your loved one looked for a clinical trial in the last 12 months?
3. What is the primary condition you are researching?
4. How difficult was it to understand if you qualified for trials you found? (1-5 Scale)

Validation Questions (Bottom of Funnel)

Purpose: Quantify pain severity and price sensitivity.

1. Rank these features in order of importance: [Plain Language, Matching, Logistics, Tracking]
2. What tools do you currently use to track your health?
3. Van Westendorp: At what price would this tool be too expensive to consider?
4. Van Westendorp: At what price would you assume the quality is too low?

Hypothesis & Setup

We will drive traffic to a simple landing page describing the value proposition. The goal is to measure intent via email signups for early access.

Recommended Wizard of Oz MVP

Simulate the AI experience manually to validate the output quality before coding.

1. User fills out a Google Form (Condition, Zip, Basic History).
2. Founder manually queries ClinicalTrials.gov API.
3. Founder uses ChatGPT to "translate" the top 3 matches into plain English.
4. Founder emails a personalized "Trial Report" PDF to the user.

Fake Door Test

Test demand for specific features before they exist.

Implementation: On the landing page or a blog post about "Traveling for Care," include a button labeled "Calculate Travel Stipend."

Interaction: When clicked, show a modal: "We are building this tool. Join the waitlist to be the first to know when it launches."