PITMS
Research type
Research Study
Full title
Predicting Individual Treatment responses towards personalised medicine in Multiple Sclerosis
IRAS ID
257366
Contact name
Olga Ciccarelli
Contact email
Sponsor organisation
University College London
Clinicaltrials.gov Identifier
UCL Data Protection, Z6364106/2019/03/203
Duration of Study in the UK
2 years, 11 months, 28 days
Research summary
Our goal is to predict the individual response to disease-modifying treatments in Multiple Sclerosis (MS) by translating machine learning into clinical practice. This is the first step towards personalised medicine in MS.
We aim to collect data from all manifestations of MS that may influence the individual treatment response in the NHS and translate machine learning techniques into clinical practice in order to generate a tool which gives the probability that an individual patient will receive benefit from a specific treatment.
The output of this project is a software prototype that gives the probability of responding to a drug (or the probability of developing side effects) and therefore guides treatment choice in the individual patients.
This project will bring access to an advanced technology directly to NHS patients and will help doctors to decide the most appropriate treatment for MS patient. The impact of a personalised approach to MS treatment will translate into benefits at a personal and societal level and on the NHS.
REC name
Wales REC 6
REC reference
19/WA/0157
Date of REC Opinion
17 Jun 2019
REC opinion
Further Information Favourable Opinion