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IDEA/COMPANY FORMATION: Discovering Curative Therapies for Parkinson’s Disease with Machine Learning

Host: Dr. Katharina Volz, CEO and Founder, OccamzRazor

Expert Contributor: Alexander Levy, EIR at Silicon Valley Bank, Co-Founder and former COO, Atomwise

 

We see significant potential at the convergence of AI and neuroscience to find disease-modifying treatments for Parkinson’s Disease (PD) and other complex diseases. To cure a complex and multifactorial disease like PD, we need to go beyond targeting just a single gene or a single disease mechanism. Analysis of unstructured and structured biomedical datasets (e.g., published literature, preclinical and clinical trial results) can yield a knowledge graph representing all known information about PD. This graph can be used to drive downstream therapeutic insight, augment decision-making in biomedical research, and generate strategic therapeutics development. Join us in exploring this exciting application of machine learning for therapeutic discovery.

Suggested Pre-reads

1) Natural language processing pipeline published with Stanford at ACL, the #1 ranked publishing venue for NL

2) General overview for AI for drug discovery