GRIDS

GRIDS brings together world renowned experts from across the globe to discuss recent developments and unique challenges in the field of lysosomal storage disorders and/or rare genetic diseases.

1.703.261.6220

 Keynote Presentation: Derya Unutmaz, MD, The Jackson Laboratories, CT “Exploring the limits of AI in Medicine”

Nanotechnology:

1. Regulation of lysosomal function by nanotechnology

2. Lysosome dysfunction as an emerging nanomaterial toxicity

3. Blood-brain barrier delivery for lysosomal storage disorders with IgG-lysosomal enzyme fusion proteins

4. Lysosomal therapies and drug delivery strategies: Liposomes and nanoparticles

Organoids and Lab-Grown ModelS:

1. Modeling neuronopathic storage disorders with patient-derived culture systems

2. Evaluation of microglia from GBA1 iPSC Cell lines

3. Engineered heart tissue and organoids for inherited cardiac diseases (Fabry disease)

4. Generation of a brain organoid platform to study neuronopathic GD and therapeutic strategies

Theranostics in Lysosomal Disorders:

1. Exploring fluorescent techniques to analyze the morphology, positioning, and function of lysosomes

2. Mitochondrial and lysosomal dynamics by fluorescent microscopy

3. Targeting mechanisms using GAGs for bone-directed therapies

4. The application of prime editing as a therapeutic strategy in Rare Diseases

Current issues in Gene Therapies for Lysosomal Disorders:

1. Lentivirus and AAV vectors to develop GT in MPS IV

2. AAV-mediated gene therapy for Sialidosis

3. Developing a gene transfer therapy for neuronopathic disorders (MPS3c)

4. Patient preferences for GT or Future of the funding and reimbursement of Gene Therapy for adult-onset

The expanded applications of AI in Lysosomal Disorders:

1. Opportunities and challenges for deep learning in cell research: Creating virtual cells

2. Open-Labeled Clinical Trial Using a Second-Generation Artificial-Intelligence-Based Therapeutic Regimen

in Patients with Gaucher Disease Treated with Enzyme Replacement Therapy

3. Evaluating osteonecrosis using AI-based technology

4. Assessment of bone involvement using the applications of Machine Learning