Pipelines, Bioinformatics and Biomarkers: an update on Collaborative Network Awards

The Alliance-funded Collaborative Network Awards are multi-year grants that are fueling international networks of researchers and institutions, working together to make crucial breakthroughs in understanding and treating progressive MS. They aim to accelerate progress in:

  • Drug discovery programs that identify and validate molecular and cellular targets and screen and characterize drug candidates, which may be either repurposed or first-in-human drugs;
  • The discovery, advancement and validation of new or existing biological or imaging biomarkers; and,
  • Proof-of-concept trials and trial designs, including, but not limited to trials in remyelination, neuroprotection, enhanced plasticity.

In September 2016 during the European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS), we announced the three projects that have been selected to receive a total investment of €12.6 million over three years. Below is an update on the three projects’ progress.

Project 1

Development of a drug discovery pipeline for progressive MS

Principal Investigator: Francisco Quintana, Ph.D., Brigham and Women’s Hospital (U.S) in collaboration with 8 Investigators from the U.S., Canada, Israel and Sanofi Genzyme

The goal of Dr. Francisco Quintana’s project is to identify drug candidates that may be effective therapies for progressive MS. The project’s central idea is that targeting the innate immune system in the central nervous system will uncover effective therapeutic approaches for progressive MS. While the innate immune system normally functions to protect the body from infections, Dr. Quintana and others have found that innate immune cells in the central nervous system promote disease activity in MS and other diseases. To date, Dr. Quintana’s Network team have been examining in more detail enzymes in a cell signaling pathway that are the target of the drug miglustat and are potentially druggable targets to block the destructive properties of some innate immune cells. The team is also currently evaluating miglustat in cells and are considering a simple clinical trial to administer miglustat and examine the cerebrospinal fluid.

They have further completed testing a “library” of 500 compounds that can penetrate the blood-brain barrier, alongside identifying an additional compound, which mediates signaling between different cells. Subsequently they have started testing an additional 3,000 molecules from an FDA “library”. From the beginning of their respective projects, Dr. Quintana and Dr. Martino (see bioinformatics project below) have established strong communications and plan ongoing discussions regarding each project’s drug identification systems.

Project 2

Bioinformatics and cell reprogramming to develop an in vitro platform to discover new drugs for progressive multiple sclerosis (BRAVEinMS)

Principal Investigator: Gianvito Martino, M.D., Division of Neuroscience, San Raffaele Hospital Milan (Italy) in collaboration with 13 Investigators from Italy, France, Germany, Europe, Canada and the U.S.

The BRAVEinMS team is working to identify molecules that may have a protective role in nerve cells or neurons and/or the capacity to promote myelin repair.

The short-term goals for this project are to have, by mid-Spring, a definitive list of molecules that can be tested in mice using new procedures being developed by the Martino team. The team is expecting to shortly begin testing neurons and oligodendrocytes derived from hiPSCs (human induced pluripotent stem cells). By the end of August 2018, the team expects to develop outcome measures to best evaluate the results of the assays.

Project 3

Identifying a biomarker of disability progression for use in clinical trials

Principal Investigator: Douglas Arnold, M.D., McGill University (Canada) in collaboration with 16 investigators from The Netherlands, U.K., U.S., and Switzerland.

Douglas Arnold, M.D. of McGill University is developing the next generation of tools for measuring disease progression in progressive MS by pioneering the development of magnetic resonance imaging (MRI) markers that signal disease progression, and adapting these for use in early (phase 2) clinical trials of progressive MS treatments. Dr. Arnold’s research examines the underlying idea that brain injury-associated disease progression in MS is detectable by MRI prior to its identification by physicians in a clinic visit.

Using data from previously completed clinical trials, the group has been working on developing machine learning tools (also known as artificial intelligence) to automatically predict future disease activity from images acquired from Relapsing Remitting MS (RRMS) patients. Although they have been focusing on RRMS patients for now, the machine learning tools that they are developing will be transferable to the context of progressive MS patient images. They have been asking whether new lesions seen on MRI might predict future disease activity or changes in Expanded Disability Status Scale (EDSS) scores. The team has also been creating computer tools to share and control quality of the data they are generating. Finally, the team is in discussions to add more images (equaling more data) to their database which will help in developing even more robust algorithms.

Additional items to note include:

1)            A conference publication linked to this project:

Doyle, D. Precup, D.L. Arnold, T. Arbel, “Predicting Future Disease Activity and Treatment Responders for Multiple Sclerosis Patients using a Bag-of-Lesions Brain Representation”, in Proceedings of the 20th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2017), Quebec City, Quebec, Canada, September 2017.

2)            The team has found an unexpected challenge hiring staff for machine learning work. In short, the Artificial Intelligence field has exploded in recent years and they are competing with companies such as Google and Facebook for talent. They are preparing hiring and staffing strategies to manage the strength of the research teams.

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