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Therapy Training AI-Agent: Synthetic Patients for Clinical Education

Enabling safe practice with diverse patient presentations through AI-generated synthetic patients

Healthcare EducationClinical Training

The Challenge

Training therapists requires extensive practice with diverse patient presentations, but access to real patients—especially those with complex or rare conditions—is limited and ethically constrained. Traditional role-playing lacks the psychological depth needed to prepare trainees for challenging clinical encounters.

Our Approach

We developed an AI agent that generates realistic synthetic patients for therapy training. Based on detailed clinical parameters ("Regieanweisungen")—diagnosis, demographics, trauma history—the system creates psychologically consistent patient personas for full therapeutic sessions. This enables safe practice with extreme cases that would be difficult to access in traditional training.

Technical Achievement

The synthetic patient agent delivers sophisticated training experiences:

Dynamic Patient Personas

Maintains psychological consistency with realistic defense mechanisms and transference patterns

Responsive Behaviors

Adapts emotional responses to interventions, from resistance to breakthrough moments

Clinical Authenticity

Exhibits inconsistent narratives, gradual trust-building, and realistic therapeutic pacing

Crisis Simulation

Enables practice with crisis situations and emergency scenarios

Customizable Complexity

Adjusts from straightforward to highly complex presentations (borderline personality, severe PTSD, psychosis)

Lessons Learned

Creating believable synthetic patients requires emotional authenticity beyond clinical accuracy. Success came from encoding the messy human reality of psychological distress, not just diagnostic criteria. The AI must be challenging enough for learning value while remaining therapeutically responsive. Clear positioning as a training tool—not a replacement for real patient contact—ensures appropriate educational use.