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Drug Discovery from Bench to Artificial Intelligence: Treating the Rare and Ignored

Monday April 06, 2020

2:00 pm - 3:30 pm Eastern Time (ET)

Room 15 B

DDD NEU TCP

Chair :

Khalid Garman
National Institutes of Health

Keith Pennypacker
University of Kentucky



Developing new drugs is a time-consuming process with an average cost of $2.6 billion. Research funding is more readily directed toward developing new therapies for common and manageable conditions, but there is less financial incentive to pursue treatments for neuropathologies and rare diseases. As a result, treatment is available only for 5% of rare diseases and drug development programs for neurological diseases such as stroke have been abandoned by pharmaceutical industry. In this symposium, we will explore different modalities of drug discovery for rare and ignored diseases including bench to bedside, high throughput small molecule screening, and artificial intelligence.

Speakers

Matthew Hall - National Center for Advancing Translational Sciences (NCATS), NIH

Biochemical and Cell-based Assays for Automated, Small Molecule, High-Throughput Screening to Identify Therapeutic Avenues for Rare and Drug-resistant Cancers

Sean Ekins - Collaborations Pharmaceuticals, Inc.

Machine Learning for Rare and Neglected Disease Drug Discovery

Keith Pennypacker - University of Kentucky

Machine Learning to Determine Therapeutic Targets in Blood Biomarkers from the Ischemic Stroke Patients

Shajila Siricilla - Vanderbilt University Medical Center

Identification of FDA Approved Drugs and their Synergistic Combinations as Potent and Selective Regulators of Uterine Contractility for Therapeutic Control of Preterm Labor

Ashraf Uz-Zaman - Texas Tech University Health Sciences Center

Discovery and Structure-activity Relationship Study of Novel Series of Mono-amine Transporter Inhibitors for the Treatment of Neurodegenerative Diseases