Mu opioid receptor Agonists
7 drugsAbout Mu opioid receptor
The Mu opioid receptor (MOR) is a GPCR in the brain, spinal cord, and GI tract that mediates opioid analgesic effects. Activation reduces pain, but also carries a risk of dependence and respiratory depression.
Human genetics strongly support MOR as a drug target, with variants linked to opioid use disorder (score 0.86) and skeletal abnormalities (score 0.80). Gain-of-function variants are protective against opioid use disorder, suggesting activation is beneficial.
MOR is targeted by 32 FDA-approved small molecule drugs, including RELISTOR and MOVANTIK. Seventeen drugs are indicated for pain, while fifteen target other conditions.
Strategic Insights
ℹ️ How we calculate- White space opportunity in Pain Management with only 4 trials.
Human Genetic Evidence Strong
Genetic evidence strongly supports OPRM1, with a max score of 0.86 linking it to opioid use disorder.
Strong genetic support suggests clinical trials targeting genetically-validated indications have increased probability of success.
💡 Why activation?
- • Gain-of-function variants reduce disease risk — enhancing activity may help
- • 100% directional consistency across 1 traits
- • Strong signal in psychiatric disorder pathways
Cross-Disease Effects
Trade-off: LowDirection of Effect
100% alignedEvidence Across Diseases
14 totalGWAS and other genetic studies link OPRM1 to 14 diseases.
Activating this target may be therapeutic
🔗 Colocalization Evidence 20 strong
max H4: 1.00eQTL/pQTL signals for OPRM1 colocalize with these GWAS traits, providing causal evidence that gene expression changes drive disease risk.
Understanding these scores
Association Score (0-1): Combines all evidence types (genetic, literature, drugs, animal models). Higher = more evidence linking target to disease. This is a ranking heuristic, not a confidence score.
L2G Score: Open Targets uses a machine learning model (Locus-to-Gene) to predict which gene is causal at each GWAS locus. L2G=0.5 means ~50% probability of being the causal gene. Only associations with L2G > 0.05 are included.
Odds Ratio (OR): From gene burden studies (UK Biobank, AstraZeneca PheWAS). Measures how loss-of-function variants affect disease risk. OR<1 = protective (inhibiting target may help), OR>1 = risk (losing function causes disease).
Beta (β): Effect size for continuous traits. β<0 = protective, β>0 = risk.
Clinical Translation (~1.8x): Based on Nelson et al. 2015: drug targets with genetic evidence have ~2x higher success rates in clinical trials. We estimate: Strong support (score ≥0.7) → ~1.8x, Moderate (0.3-0.7) → ~1.3x, Weak → baseline.
Colocalization (H4): Tests whether a GWAS signal and an eQTL/pQTL signal share the same causal variant. H4 is the posterior probability that both traits are associated AND share a causal variant. H4 > 0.8 = strong evidence that gene expression/protein levels drive disease risk. This links genetic variation → gene expression → disease, supporting the target-disease connection.
Top Drugs
Twenty-two companies have approved drugs targeting MOR, with Hikma and Fresenius Kabi as leading players.
The fragmented competitive landscape suggests relatively low barriers to entry for new market participants.
| Drug | Company | Approved | Indications |
|---|---|---|---|
| ULTIVA | Viatris | 1996 | 1 |
| VIBERZI | AbbVie | 2015 | 1 |
| XTAMPZA ER | COLLEGIUM PHARM INC | 2016 | 1 |
| METHADONE HYDROCHLORIDE | Hikma | 1947 | - |
Drug Modality Landscape
Modalities
Routes of Administration
Mu opioid receptor is amenable to small molecule drugs, with oral options available for convenient dosing.
Exploring alternative modalities like antibodies or peptides could provide a competitive advantage in this space.
Clinical Trials 854 trials
Completion by Phase
| Phase | Total | Completed | Failed | Active | Completion |
|---|---|---|---|---|---|
| Phase 1 | 163 | 139 | 9 | 14 | 94% |
| Phase 2 | 193 | 128 | 36 | 27 | 78% |
| Phase 3 | 176 | 134 | 20 | 21 | 87% |
| Phase 4 | 322 | 217 | 55 | 44 | 80% |
Top Sponsors
By Modality
Top Conditions
Top Drugs
Phase 3 Readout Calendar Pro
1 Phase 3 trial testing approved Mu opioid receptor drugs across all sponsors.
Coverage: trials whose intervention is an approved drug targeting Mu opioid receptor. Pre-approval candidates with development codes (e.g. AZD0901, MK-7240) are not yet linked. Anchored on CT.gov primary completion date.
Drug Approval Timeline (1947 - 2016)
1. Methadone Hydrochloride Injection is indicated for the...
The first drug targeting MOR was approved in 1943 (HYCODAN), with the most recent approval in 2023 (BRIXADI).
The long approval history indicates a mature market, but recent approvals suggest continued innovation opportunities.
Pro Intelligence Preview
Deep insights for drug target analysis
Competitive Landscape
- • 6 companies competing
- • Market share by company
Full Drug Portfolio
- • All 7 approved drugs
- • Approval dates & indications
Genetic Validation
- • Full genetic evidence table
- • Effect sizes & directions
Approval Timeline
- • Full 7-drug timeline
- • First-of-modality markers
Clinical Trials Analysis
- • Competition: High (15 sponsors)
- • White space: 6 underexplored indications
- • Success rates by condition
Full summary • All drugs • Genetic evidence • Trials • Timeline
How We Calculate These Metrics
Target Attractiveness Score
A 0-100 score based on trial activity, sponsor diversity, and completion rates. Calculated from 490 clinical trials targeting Mu opioid receptor.
Completion rate: Percentage of trials that reached their planned endpoint. Trials terminated early, withdrawn, or suspended are not counted—these often indicate safety issues, lack of efficacy, or strategic pivots.
- Highly Attractive (80+): High trial activity, many sponsors, strong completion rates
- Attractive (60-79): Good trial activity and validation
- Moderate (40-59): Moderate interest from sponsors
- Low (under 40): Limited trial activity or validation concerns
Strategic Insights
Auto-generated insights based on trial analytics including competition intensity, white space opportunities, modality shifts, and failure patterns. We analyze trial sponsors, phases, indications, and outcomes.
Risk Signals
- High Competition: Many sponsors competing for this target (may reduce market opportunity)
- High Failure Risk: Low trial completion rates suggest development challenges
- Low Validation: Limited trial activity or poor outcomes indicate uncertain viability
- White Space Available: Underexplored indications present opportunities