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.

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Key information

Conditions

PARKINSON DISEASE (Disorder) Basal Ganglia Diseases Brain Diseases Central Nervous System Diseases Movement Disorders Nervous System Diseases Neurodegenerative Diseases Parkinson Disease Parkinsonian Disorders Synucleinopathies

Age range

40 year–80 year

Sex eligibility

All sexes

Study type

Observational

Primary location

University Hospital of Toulouse, Toulouse, France

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

Smartwatch and mobile application

Device

Wearing a smartwatch and using a mobile application for one year

Primary outcomes

Classification performance of the Parkinson's disease (PD) progression prediction model

Time frame: Between baseline and 12 months

Classification performance of the model in predicting observed motor disease progression, defined as a binary outcome: the condition of a patient is classified as worsened if either the Movement Disorder Society Unified Parkinson's Disease (MDS-UPDRS) rating scale part III score in ON-state increases by more than 3 points (>3), or the Levodopa Equivalent Daily Dose (LEDD) increases by more than 10%.

Secondary outcomes

Usability of the mAI-Care app

Time frame: 12 month visit

System Usability Scale score of end-users (PD patients)
Usability of the mAI-Insights app

Time frame: 12 month visit

System Usability Scale score of end-users (clinicians)

Study contacts

Contact information is provided by the study sponsor or research team.

Margherita FABBRI, MD

CONTACT

[email protected]

0561776039 ext. +33

Sponsors and collaborators

Lead sponsor

University Hospital, Toulouse

Other

Collaborators

Aristotle Univ. of Thessaloniki (Greece)

Registry information

Acronym: AI-PMP

Important dates

Study start: 2025
Primary completion: 2027
Study completion: 2027
First posted: Sep 24, 2025
Registry last updated: Sep 24, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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