Louisiana Initiative Launches AI Drug Discovery for ALS

A collaborative initiative, the Louisiana AI Drug Development Infrastructure for ALS (LADDIA), has been launched by Answer ALS, uniting Tulane University, Pennington Biomedical Research Center, and GATC Health to accelerate artificial intelligence-powered drug discovery for amyotrophic lateral sclerosis (ALS) and other neurodegenerative diseases. Led by Dr. Jeffrey Keller of Pennington Biomedical and Dr. Aron Culotta of Tulane, the project will leverage Louisiana’s institutions and the open-access Neuromine Data Portal – the world’s largest ALS dataset – alongside GATC Health’s proprietary AI platform to identify potential therapeutic targets. The initiative will unfold in two phases, aiming to generate joint research publications, data-driven discoveries, and establish a roadmap for long-term collaboration, with identified biomarkers to be shared with the research community.

Louisiana’s Collaborative Initiative for AI-Driven Drug Discovery

The Louisiana AI Drug Development Infrastructure for ALS (LADDIA) represents a collaborative initiative uniting Tulane University, Pennington Biomedical Research Center, and GATC Health, a tech-bio innovator specialising in artificial intelligence applications for drug discovery utilising large-scale multiomics data. This effort is supported by a commitment from the State of Louisiana to foster neuroscience research and innovation, with the overarching aim of accelerating AI-powered drug discovery for amyotrophic lateral sclerosis (ALS) and other neurodegenerative diseases. Dr. Jeffrey Keller of Pennington Biomedical and Dr. Aron Culotta of Tulane will lead a statewide network connecting researchers with expertise in artificial intelligence, drug discovery, neuroscience, and clinical care.

The initiative will unfold in two phases, beginning with the establishment of a collaborative foundation through recruitment of local talent and alignment of institutional strengths. Phase Two will activate this foundation to advance collaborative projects, optimise AI models, and generate impactful scientific output across participating institutions. GATC Health will contribute its proprietary AI platform to identify druggable ALS targets with high predictive accuracy, leveraging the open-access Neuromine Data Portal, the world’s largest ALS dataset, to facilitate real-time collaboration and identify potential therapeutic pathways.

Benchmarks for LADDIA include joint research publications, data-driven discoveries, and a shared roadmap for long-term collaboration, positioning Louisiana as a leader in AI-driven medical innovation. The model driving LADDIA and GATC is also intended to be scalable, offering a framework for applying AI to other complex diseases, such as Alzheimer’s and chronic pain, through public-private partnerships, while biomarkers identified through this collaboration will be shared with the research community. The ultimate goal is to identify and prioritise therapeutic targets using AI-driven insights, contributing to ALS drug discovery.

Establishing the LADDIA Infrastructure

Phase One of the initiative will focus on establishing the collaborative foundation, including recruitment of local talent and alignment of institutional strengths, preparing the infrastructure for AI-enabled drug discovery. Phase Two will activate this foundation to advance collaborative projects, optimise AI models, and generate impactful scientific output across participating institutions.

The Pennington Biomedical Research Center, a campus within the Louisiana State University System, conducts research related to obesity, diabetes, cardiovascular disease, cancer, and dementia, and currently employs over 600 personnel across 44 clinics and research laboratories. The initiative’s model, driven by LADDIA and GATC, is intended to be scalable, offering a framework for applying AI to other complex diseases, such as Alzheimer’s and chronic pain, through public-private partnerships.

Expanding the Model to Other Diseases

The model driven by LADDIA and GATC is also intended to be scalable, offering a framework for applying AI to other complex diseases, such as Alzheimer’s and chronic pain, through public-private partnerships. This scalability extends beyond ALS, suggesting a broader application of the collaborative infrastructure and AI tools developed through the initiative.

The initiative’s framework is designed to be adaptable, providing a potential model for addressing other complex diseases beyond those initially targeted. This suggests that the collaborative approach and technological advancements generated by LADDIA could have implications for a wider range of medical research areas.