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