Deadline: 2019-05-31 Award: $500,000 Open to: US citizen or permanent resident 18+*
This Challenge aims to reward and spur innovative solutions to the development of machine learning algorithms that would aid the discovery of novel analgesics and/or treatments for opioid addiction and overdoses. For example, an algorithm can be developed to identify side groups and/or include ratio of bond types or atom types in a molecule in order to identify signatures that are less likely to trigger addiction.
This Challenge requires submission of only a detailed description of the design of the algorithms, not the final working versions. The ultimate goal is to utilize the data from Challenge 1 and Challenge 2 during the envisioned Reduction-to-Practice Challenge to provide proof-of-concept and design, synthesize, optimize and test novel compounds that are less likely to trigger addiction or are able to treat addiction/overdose. Optimized novel small-molecule leads would be tested for their bioactivity using physiologically relevant models developed in Challenge 4 in order to provide proof-of-concept for therapeutic hypotheses to treat pain, addiction and overdose.