- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT05769465
MAP THE SMA: a Machine-learning Based Algorithm to Predict THErapeutic Response in Spinal Muscular Atrophy (MAP_THE_SMA-01)
Spinal Muscular Atrophy (SMA) is caused by the homozygous loss of the Survival Motor Neuron (SMN) 1 gene, which leads to degeneration of spinal alpha-motor neurons and muscle atrophy. Three treatments have been approved for SMA but the available data show interpatient variability in therapy response and, to date, individual factors such as age or SMN2 copies,cannot fully explain this variance.
The aim of this project is:
- collect clinical data and patient-reported outcome measures (PROM) from patients treated with nusinersen, risdiplam, onasemnogene abeparvovec,
- identify novel biomarkers and RNA molecular signature profiling,
- develop a predictive algorithm using artificial intelligence (AI) methodologies based on machine learning (ML), able to integrate clinical outcomes, patients' characteristics, and specific biomarkers.
This effort will help to better stratify the SMA patients and to predict their therapeutic outcome, thus to address patients towards personalized therapies.
Study Overview
Status
Conditions
Intervention / Treatment
Study Type
Enrollment (Estimated)
Contacts and Locations
Study Contact
- Name: Comitato Etico
- Phone Number: 0630156124
- Email: comitato.etico@policlinicogemelli.it
Study Locations
-
-
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Roma, Italy, 00168
- Recruiting
- Fondazione Policlinico Universitario Agostino Gemelli IRCCS
-
Contact:
- Giorgia Coratti, PhD
- Email: giorgia.coratti@unicatt.it
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Child
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- confirmed genetic diagnosis of SMA (5q)
- clinical phenotype of type I or II or III;
- able to provide (patient/caregiver) written informed consent
Exclusion Criteria:
- None
Study Plan
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
---|---|
Patients treated with nusinersen
|
Patients will be enrolled if exposed to nusinersen, risdiplam, onasemnogene abeparvovec
|
Patients treated with risdiplam
|
Patients will be enrolled if exposed to nusinersen, risdiplam, onasemnogene abeparvovec
|
Patients treated with onasemnogene abeparvovec
|
Patients will be enrolled if exposed to nusinersen, risdiplam, onasemnogene abeparvovec
|
Patients naive from disease modifying treatments
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Time Frame |
---|---|
Collect clinical data and patient-reported outcome measures (PROM) from patients treated with nusinersen, risdiplam, onasemnogene abeparvovec
Time Frame: 30 months
|
30 months
|
Identify novel biomarkers and RNA molecular signature profiling
Time Frame: 30 months
|
30 months
|
Develop a predictive algorithm using artificial intelligence (AI) methodologies based on machine learning (ML), able to integrate clinical outcomes, patients' characteristics, and specific biomarkers
Time Frame: 24 months
|
24 months
|
Collaborators and Investigators
Investigators
- Principal Investigator: Giorgia Coratti, PhD, Fondazione Policlinico Universitario Agostino Gemelli IRCCS
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- 5488
- GR-2021-12374579 (Other Grant/Funding Number: Italian Health Ministry)
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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-
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