collaborators came together to showcase how new technologies, shared data, and bold partnerships are shaping the next generation of ALS discoveries.

Explore some of the key takeaways from the presentations and panel discussion below:

Fernando Vieira, MD | ALS TDI

Potentiating ALS Breakthroughs

Key Takeaways:

  • ALS TDI is advancing a portfolio of diverse therapeutic approaches, balancing high-risk, high-reward projects with those that strengthen the broader ALS research ecosystem.
  • Drug discovery efforts span multiple modalities, including small molecules, biologics, and emerging platforms like mRNA/LNP delivery, to address different disease pathways.
  • ALS TDI’s “Drug Discovery Engine” integrates cell biology, pharmacology, and clinical translation to move promising treatments efficiently toward trials.
  • Collaboration remains central — through shared data, model development, and biomarker discovery — to “lift all boats” across the ALS research field.
  • The institute continues to prioritize patient impact over profit, ensuring resources are directed where they can make the most meaningful difference.
  • ALS TDI will continue to build on this momentum through collaboration, open data sharing, and the expansion of our research team and capabilities.

Alan Premasiri, MS | ALS TDI

Collaboration Fueling Discoveries: The ARC Study’s Impact in 2025

Key Takeaways:

  • The ARC Study now includes data from more than 1,800 participants, making it one of the largest real-world ALS datasets in existence.
  • ARC integrates data including voice recordings, wearable device data, blood samples, and EHR data — creating a holistic picture of ALS progression.
  • Recent collaborations have harmonized ARC data with Answer ALS, allowing cross-study comparison and accelerating global research access.
  • New analytic tools and tasks are being added to capture the elements of ALS progression that matter most to participants.
  • Future efforts include expanding data harmonization, accessibility, and clinical collaboration to fuel new discoveries and improve trial design.

Danielle Boyce, MPH, DPA | ALS TDI

Turning Anecdotes into Evidence: Answering the ALS Community’s Questions with Big Data

Key Takeaways:

  • ALS TDI is transforming real-world data, including EHRs and self-reported data from the ARC Study, into actionable scientific evidence.
  • Preliminary findings show higher rates of autoimmune conditions prior to diagnosis among people with ALS, suggesting new potential risk factors to explore.
  • Integrating multiple data “domains” (clinical, genetic, and lifestyle) strengthens ALS TDI’s ability to run large-scale genome-wide association studies (GWAS) and other studies that utilize biological data.
  • By sharing insights openly through the ALS Real-World Evidence (RWE) portal and ALS TDI GitHub resources, ALS TDI is helping the entire research community use these data.
  • The work underscores the institute’s commitment to transparency, data sharing, and collaboration in understanding ALS causes and progression.

Panel Discussion

Value of Collaborative Data and Resource Sharing to Advance ALS Research

Moderator: Danielle Boyce, MPH, DPA, Principal Investigator, Real World Evidence, ALS TDI Panelists: Fernando Vieira, M.D., CEO/CSO, ALS TDI; Tonya Gilbert, Ph.D., Executive Director of Translational Research, Eikonizo; Irina Antonijevic, M.D., Ph.D., Chief Medical Officer, Trace Neuroscience; Tris Dyson, Founder and Managing Director, Challenge Works

Key Takeaways:

  • Panelists emphasized that large-scale, multi-institutional collaborations — including the Healy ALS Platform Trial, the ARC Data Commons, and Answer ALS — are accelerating the identification of genetic targets, biomarkers, and therapeutic candidates.
  • While most organizations recognize the value of collaboration, differing data governance structures, funding models, and priorities can slow progress.
  • Harmonizing protocols, consent language, and data formats will make it easier to combine and reuse data across future studies.
  • Speakers stressed the ethical responsibility to share data transparently, ensuring participants see their contributions drive tangible progress.
  • Artificial intelligence and synthetic data modeling hold promise for overcoming data-sharing barriers, but must be guided by validation, transparency, and human oversight.

Amalia Papanikolaou, PhD and Tris Dyson | Challenge Works

Unlocking Data. Unlocking Treatments

Key Takeaways:

  • Challenge Works has launched the Longitude Prize on ALS, a global competition using artificial intelligence to identify new therapeutic targets for ALS.
  • The £8 million, five-year prize invites multidisciplinary teams worldwide to analyze the world’s largest combined ALS dataset — including whole-genome, multi-omics, and longitudinal clinical data.
  • Participants will compete in three stages — Discovery, Prioritization, and Validation – culminating in a £1 million grand prize in 2031 for the team identifying the most promising, validated therapeutic target.
  • The initiative provides teams with secure cloud-based computing environments preloaded with bioinformatics tools and compute credits to democratize access to cutting-edge ALS research data, including ALS TDI’s ARC Study Data.
  • By linking molecular, genetic, and clinical data through AI, the Longitude Prize aims to accelerate target discovery, patient stratification, and biomarker identification — bringing the field closer to precision ALS treatments.

Rebecca James, PhD | Eikonizo Therapeutics

The Evolution of HDAC6 as a Therapeutic Target for ALS

Key Takeaways:

  • Eikonizo has developed next-generation, highly selective HDAC6 inhibitors (EKZ-102) designed to improve neuronal transport, reduce protein buildup, and limit inflammation in ALS models.
  • Preclinical studies in SOD1, TDP-43, and C9orf72 models show robust neuroprotection, improved motor function, and reduced disease pathology.
  • The compounds demonstrate strong CNS penetration and target engagement, overcoming safety and selectivity limitations of earlier HDAC6 inhibitors.
  • In collaboration with ALS TDI, the team is conducting preclinical validation and biomarker development to guide upcoming Phase 1b/2 proof-of-concept trials in ALS.
  • The shared goal is to combine Eikonizo’s mechanistic drug expertise with ALS TDI’s data-driven patient insights to accelerate translation from lab to clinic.

Michael J. Mitchell, PhD | University of Pennsylvania

Lipid Nanoparticles for Overcoming Biological Barriers to mRNA Delivery to the Brain

Key Takeaways:

  • Mitchell Lab and ALS TDI are collaborating to design new lipid nanoparticles (LNPs) that can safely and efficiently deliver therapeutic mRNA to the brain — a key step toward developing mRNA-based treatments for ALS.
  • The team developed a high-throughput blood–brain barrier (HTS-BBB) screening platform to rapidly test thousands of LNP formulations for their ability to cross into the brain and deliver genetic cargo to neurons.
  • Using this approach, they identified several novel LNP candidates (C12-306 and C12-494) that outperformed current clinical standards in delivering mRNA across the BBB and into neuronal cells.
  • These LNPs successfully delivered ALS-relevant therapeutic mRNAs (including STMN2 and C9orf72) to neuronal cells, demonstrating proof-of-concept for treating neurodegenerative diseases through targeted mRNA delivery.
  • Ongoing work aims to optimize and validate these LNPs in vivo, paving the way for next-generation RNA-based therapies that can reach the central nervous system — a long-standing challenge in ALS drug development.

Watch the Summit Recordings!

Thank you to all of our presenters, participants, and attendees for making this year’s ALS TDI Summit both informative and inspiring.

You can now watch the full Summit presentations, including the Leadership Award presentations, on YouTube.


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