AI-based Progression and Medication Response Prediction Study in Parkinson's Disease

AI-based Progression and Medication Response Prediction Study in Parkinson's Disease

The study aims to provide initial PoC validation data of two AI models to predict disease progression and treatment side effects in PD patients using as input patients' demographic, clinical and genetic information, as well as digital biomarker measurements in daily living collected via a smartwatch and a mobile application.

Inclusion Criteria:

• Parkinson's disease diagnosis according to MDS criteria (Postuma et al., 2015)
• Disease duration ranging from 5 to 10 years
• Age 40-80
• Patients in stages 2 and 3 of the Hoehn and Yahr (a functional disability scale) in the ON condition
• The participant is using a compatible smartphone
• Written informed consent

Exclusion Criteria:

• Atypical Parkinsonian Syndrome
• Second-line device-aided treatments
• Patients with >4 daily doses of L-DOPA
• Daily levodopa equivalent dose > 1500 mg
• Ongoing hallucinations requiring short-term treatment adjustment
• Inability to provide informed consent or participate in the study
• Inability to use the smartwatch and/or the mAI-Care app - as judged by investigator
• Lacking motivation to participate in study procedures - as judged by investigator
• Under adult autonomy protection system, legal guardianship or incapacitation
• Pregnant and breast-feeding women