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DTSTAMP:20260522T150122Z
LOCATION:C2/3/4 Ballroom
DTSTART;TZID=America/Chicago:20181113T083000
DTEND;TZID=America/Chicago:20181113T170000
UID:submissions.supercomputing.org_SC18_sess322_post222@linklings.com
SUMMARY:OpeNNdd: Open Neural Networks for Drug Discovery: Creating Free an
 d Easy Methods for Designing Medicine
DESCRIPTION:Bryce Kroencke (American River College); Shawn Shacterman (Uni
 versity of California, Berkeley); Nicholas Pavini (American River College)
 ; Benjamin Samudio (American River College, Sierra College); and Silvia Cr
 ivelli (Lawrence Berkeley National Laboratory)\n\nBringing new medicines t
 o patients can be prohibitively expensive in terms of time, cost, and reso
 urces.  This leaves many diseases without therapeutic interventions.  In a
 ddition, new and reemerging diseases are increasing in prevalence across t
 he globe at an alarming rate.  The speed and scale of medicine discovery m
 ust be increased to effectively meet this challenge.  OpeNNdd is a neural 
 network platform bringing together people, machine learning, and supercomp
 uting to solve the challenge of creating medicines.  We have developed a n
 ovel neural network which quickly and accurately models candidate medicine
 s interacting with a disease target, a metric to delineate its domain of a
 pplicability, and a process that communicates neural network results to pa
 rticipants in a readily interpretable way.  OpeNNdd leverages the scale of
  supercomputing, the power and speed of neural networks, and the creativit
 y of people across the globe in an open and collaborative way to protect a
 nd improve global health.\n\nRegistration Category: Tech Program Reg Pass,
  Exhibits Reg Pass\n\n
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