Drug REpurposing with Artificial intelligence for Muscular disorderS

According to World Health Organization, to date, fewer than 6% of rare diseases (RDs) have an approved treatment option.

In the light of this observation, it appears crucial to develop disruptive approaches that allow to find treatments for multiple RDs.

To achieve this goal, DREAMS will start from 5 rare neuromuscular disorders (NMD) that share common pathophysiological characteristics related to dysfunctions of autophagy and desmin disorganization.

Using skeletal muscle cells derived from induced pluripotent stem cells (skMC-iPSC), DREAMS will i) identify shared biomarkers of the 5 diseases and ii) perform a high throughput drug screen on all 5 diseases.

Through a first Artificial Intelligence (AI) based solution, the output of the drug screening will be used to find drug targets shared between the diseases.

A second AI based solution will be used to find drug candidates (repurposable drugs and new molecular entities) for these shared drug targets.

A third AI-based solution will be used to find additional diseases that could be treated through the shared drug targets, in order to extend the indications for the most promising drug candidates.

Following their discoveries, the promising drug candidates will be tested for efficacy and safety in both iPSC and mouse models of the 5 NMDs and additional diseases.

In parallel, DREAMS will design an adaptive clinical trial to prepare the final stages of drug development of these novel drug candidates with multiple indications.

Together, these technological and conceptual innovations will allow the DREAMS consortium to i) develop therapies to treat multiple NMDs and related diseases, ii) to create a novel clinical design that generates a regulatory pathway for drugs that treat heterogeneous groups of patients suffering from RDs iii) to further the scientific understanding of commonalities in RDs, and iv) to create a reusable drug development platform to discover safe and effective treatments for RDs in general.