Psynary
🌍 GLOBAL RESEARCH

Validated Across 3 Continents

Psynary is powered by the largest anonymized dataset for treatment optimization in depression.

458+
Patients
Across 3 Continents
🇦🇺
Australia
Specialist Services
🇳🇿
New Zealand
Public Health
🇯🇵
Japan
Private Clinics

Global Reach

Our research spans diverse healthcare systems and cultural contexts to ensure universal applicability.

458+ Patients

Data from Australia, New Zealand, and Japan contributing to our dataset.

Diverse Settings

Includes public mental health services and private clinics.

Cross-Cultural Validity

Ensures cross-cultural validity and broad applicability.

Research Locations

🇦🇺

Australia

Specialist and community psychiatric services

🇳🇿

New Zealand

Public mental health facilities

🇯🇵

Japan

Private clinics and specialized centers

Why Scale Matters

Large-scale data enables robust machine learning and validates our approach across diverse populations.

High Statistical Power

Enables machine learning models with high statistical power and reliability.

Global Validation

Validates Psynary across diverse health systems and cultural contexts.

Clinical Confidence

Provides clinicians with confidence that insights are globally relevant.

Dataset Distribution

458
Neural Network Study
2022 Comprehensive
259
OptiMA1 Study
Japan + New Zealand
🇦🇺Australia~150 patients
🇯🇵Japan~200 patients
🇳🇿New Zealand~108 patients

Research Highlight

Our dataset represents the largest collection of treatment optimization data in its class.

Neural Network Study

2022 Comprehensive Analysis

458
Patients
Largest dataset in its class

OptiMA1 Study

Japan + New Zealand Dataset

259
Patients
Multi-national validation

📊 Largest Dataset in Its Class

Study Scope

Total Patients:458+
Countries:3
Healthcare Settings:10+
Data Points:15,000+

Clinical Impact

ML Model Accuracy:98%
Cross-Cultural Validity:Confirmed
Clinical Settings:Public & Private
Treatment Optimization:Validated

Join Our Global Research Network

Be part of the largest treatment optimization dataset and contribute to advancing mental health care worldwide.