Biased Mu-Opioid Receptor Analgesics to Prevent Overdose and Opioid Use Disorders

NIH RePORTER · NIH · UH3 · $109,995 · view on reporter.nih.gov ↗

Abstract

Approximately 100 million people in the United States suffer from pain with 9 to 12 million individuals suffering from chronic or persistent pain.1 With opioids remaining at the forefront of treatment, it has become clear that opioid abuse and opioid overdose have emerged as significant and complicated public health challenges. Drug overdose from opioids is the leading cause of accidental death in the U.S. with an estimated 100 individuals a day dying from opioid overdose due to respiratory depression.2 Although multiple factors are unquestionably responsible for the increase in the use and abuse of opioids, there is a pressing need for an effective opioid analgesic that also addresses the significant issues surrounding opioid abuse liability and overdose fatalities. Advances in our understanding of the pharmacological mechanisms associated with signaling of G-protein coupled receptors have resulted in the knowledge that activation of the mu-opioid receptor (MOR) mediates both the therapeutic and adverse effects and does so through pharmacologically distinct signaling pathways. The adverse effects associated with morphine and other MOR agonists have been traced to action through the β-arrestin pathway, while analgesia is tied to the G-protein pathway. G-protein specific agonists that avoid activation of β-arrestin signaling and its associated negative consequences provide novel strategies for the development of pathway specific or ‘biased’ drugs designed to selectively produce analgesia while eliminating unwanted adverse effects that include respiratory depression, abuse liability, and constipation. Mebias Discovery, Inc. has developed a novel platform and has identified highly ‘biased’ MOR agonists that are effective analgesics but are devoid of opioid induced adverse effects. Mebias’ preclinical studies of its IND candidate MEB-1170 has shown efficacy in 3 pain models without the known opioid adverse effects (respiratory depression, tolerance to analgesia, sedation, constipation) shown by marketed MOR drugs. In addition, MEB-1170 shows promise in abuse liability models (self-administration, drug discrimination, condition place preference, withdrawal) suggesting it could be a game changer as a non-addictive analgesic to replace Scheduled II opioids in pain management. 1 Califf, Robert M., Janet Woodcock, and Stephen Ostroff." A proactive response to prescription opioid abuse." New England Journal of Medicine 374, no.15 (2016): 1480-1485. 2 "Opioid overdose." Centers for Disease Control and Prevention. August 30, 2017. Accessed January 12, 2018. https://www.cdc.gov/drugoverdose/epidemic/index.html

Key facts

NIH application ID
10749222
Project number
3UH3DA047700-05S2
Recipient
MEBIAS DISCOVERY, INC.
Principal Investigator
JAMES E. BARRETT
Activity code
UH3
Funding institute
NIH
Fiscal year
2023
Award amount
$109,995
Award type
3
Project period
2018-09-15 → 2023-08-31