REGAIMUS

Multiple Sclerosis (MS), the leading cause of non-traumatic disability in young adults in the western world, is characterized by an auto-immune driven destruction of myelin. While current treatments successively target harmful inflammation, no drug has yet been approved to promote remyelination, which is the prototypic example of a regenerative process in the central nervous system (CNS). Despite its efficacy in animal models, remyelination often fails in MS, with only a minority of people with multiple sclerosis (PwMS) having the ability to extensively remyelinate their lesions, whereas individual profiles of spontaneous remyelination were clearly shown to act as key drivers of neurodegeneration and disability accrual. Therefore, the search for treatments that promote remyelination nowadays emerges as an urgent therapeutic challenge.

Through experimental pipelines, several lead compounds have been identified, a few having already been applied in early phase remyelination trials. Building on promising but still mitigated results (a slight improvement of conduction velocity in the visual system, a frenetic search for more potent promyelinating drugs is underway, and an increasing number of commonly prescribed drugs (several dizains) belonging to various unrelated pharmacological classes have been discovered. However, the growing number of candidates excludes that all will be part of a phase 2 trial, exposing to the risk of missing the best option for patients. One alternative might be adaptative platform trials but the selection of compounds will still face the lack of human data supporting their prioritization. This major gap, that currently drastically slow down the development of regenerative trials in MS, would be successively overcome by well conducted real life studies performed on large samples of PwMS.

In this project we will take advantage of the French OFSEP registry, the world largest database that combines longitudinal clinical data together with a unique dataset of MRI acquisitions acquired according to a standardized protocol. We will generate individual remyelination profiles for each subject, leveraging on a novel and innovative imaging metrics, the Myelin4all-NET, developed by our research group through a multistep generative artificial intelligence approach, and that now allows large scale and automated quantification of myelin content within cross-sectional or / and longitudinal clinical MRI datasets. Applying Myelin4all-NET to our population on T1 and FLAIR images will capture individual remyelination profiles of PwMS and serve as the primary outcome of the project. We will then perform a multiscale study and combine these indices with longitudinal clinical data from the OFSEP registry that will be linked to National Health Data System SNDS, and unravel the demographic, clinical, imaging and comorbid factors associated with good remyelination profiles. This will also include a data driven screen for potential treatment associated with remyelination. We will finally perform for the first time a series of emulated trials aiming at unmasking the promyelinating efficacy of treatments regimen prescribed in real life. The candidate drugs (or family of drugs according to their putative mechanisms of action) tested will include molecules validated in experimental research as well as potential hits identified by our global SNDS-OFSEP analysis. A causal inference framework will aim at estimate causal effects of interventions with observational data. The consortium joint for the purpose of the project will gather cutting edge expertise in artificial intelligence, data curation, neuroimaging processing, statistics, target trial emulation, cellular pharmacology, and MS knowledge to ensure its success. Overall, the REGAIMUS will translate therapeutic promyelinating hypothesis towards real life concrete clinical results and should considerably accelerate the development of regenerative approaches for PwMS.