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Predictive Responder & Dose Optimization SaMD

Generated design exploration based on the panel's verification.

Primary User Endocrinologists, obesity specialists, patients starting or titrating GLP-1 therapy
Success Outcome Improved treatment efficacy through personalized dosing • Reduced time to achieve clinical goals (e.g., target weight loss) • Cost savings by avoiding ineffective treatments or prolonged suboptimal dosing • Enhanced patient satisfaction by optimizing outcomes
Workflow Moment Addressing challenges like: Availability and integration of comprehensive genomic and clinical data • Robustness and interpretability of complex AI models • High regulatory scrutiny for predictive decision support influencing drug dosage • Ethical considerations around data privacy and potential for 'non-responder' labeling
1
Patient Profile & Data Setup
entry SCREEN
Device: Mobile Portrait
This screen allows the clinician to review the SaMD's purpose, confirm patient consent for data access, and ensure all necessary data sources are connected or initiated for the predictive analysis.

GLP-1 Optimizer: New Patient Setup

Personalizing GLP-1 therapy for optimal outcomes

How it Works

  • Leverages genetic, metabolic, EHR, and lifestyle data.
  • Predicts individual GLP-1 response and recommends optimal dose.
  • Minimizes trial-and-error, accelerates goal achievement.

Patient Data Access & Consent

Patient Name (text)
EHR Data (Clinical History, Labs) (checkbox)
Genomic Profile (if available) (checkbox)
Wearable/Lifestyle Data (Activity, Sleep) (checkbox)
I confirm the patient has provided informed consent for data sharing and analysis by this SaMD. (checkbox)

primary action

Initiate Predictive Analysis

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2
Personalized Dose Recommendation
core-action SCREEN
Device: Mobile Portrait
This is the core screen where the SaMD presents its predictive analysis for the patient's GLP-1 response and a tailored dose titration schedule. It emphasizes clarity and clinical decision support.

GLP-1 Optimization: [Patient Name]

Predicted Response & Recommended Titration

Patient Summary

  • Diagnosis: Type 2 Diabetes, Obesity (BMI 34)
  • Baseline Weight: 220 lbs (100 kg)
  • Baseline HbA1c: 8.5%

Predicted Outcome & Responder Type

  • Predicted Weight Loss (6 months): 18% (vs. typical 10-12%)
  • Predicted HbA1c Reduction (6 months): 2.0% (vs. typical 1.0-1.5%)
  • Responder Type: High Responder Profile

Recommended Dose Titration Schedule

Weeks 1-4: (text)
Weeks 5-8: (text)
Weeks 9-12: (text)
Week 13+ (Target Dose): (text)

Disclaimer

  • This recommendation is an assistive tool for clinical decision support. Always apply your professional medical judgment.

primary action

View Detailed Insights

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Detailed Insights & Action Plan
value-insight-handoff SCREEN
Device: Mobile Portrait
This screen provides deeper insights into why a specific recommendation was made, visualizes the predicted trajectory, and offers clear actions for the clinician to prescribe, share, or further manage the patient's plan.

Detailed Insights: [Patient Name]

Understanding the personalized GLP-1 strategy

Key Contributing Factors

  • Genomic Marker 'SLC19A3' indicates high GLP-1 receptor sensitivity.
  • Baseline HOMA-IR score suggests efficient insulin response with therapeutic intervention.
  • Early adherence to lifestyle recommendations from wearable data.

Predicted Trajectory (Weight Loss)

  • Graph: Visual comparison of predicted weight loss on recommended schedule vs. standard titration vs. non-responder profile. (Placeholder for visual chart)

Action Plan Options

form

Generate e-Prescription (1.7mg weekly titration) (primary_action)
Create Patient-Friendly Summary (primary_action)
Schedule Follow-up (primary_action)

primary action

Return to Patient Dashboard

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