RET Inhibitors
14 drugsAbout RET
RET (RET Proto-Oncogene) is a receptor tyrosine kinase involved in cell growth, differentiation, and survival. It plays a crucial role in neural crest development and kidney organogenesis, activated by GDNF family ligands.
Human genetics strongly support RET as a drug target (max score 0.95), with variants linked to multiple endocrine neoplasia type 2 and hereditary neoplastic syndrome. Loss-of-function variants increase disease risk, suggesting activation may be therapeutically beneficial.
RET is targeted by 14 FDA-approved small molecule drugs including LENVIMA, CABOMETYX and RETEVMO. Four drugs are approved for oncology, while ten address other therapeutic areas, developed by 13 different companies.
Strategic Insights
ℹ️ How we calculate- Validated target with strong trial activity and 81% attractiveness score.
Human Genetic Evidence Strong
RET has strong genetic support with a maximum score of 0.95 linking it to multiple endocrine neoplasia.
Strong genetic evidence suggests RET-activating therapies have a higher probability of clinical success.
💡 Why activation?
- • Loss-of-function variants increase disease risk (OR > 1) — restoring function may help
- • 100% directional consistency across 2 traits
- • Strong signal in genetic, familial or congenital disease, endocrine system disease, cancer or benign tumor pathways
Cross-Disease Effects
Trade-off: LowDirection of Effect
100% alignedEvidence Across Diseases
20 totalGWAS and other genetic studies link RET to 40 diseases.
Loss-of-function causes disease; activation may help
🔗 Colocalization Evidence 20 strong
max H4: 1.00eQTL/pQTL signals for RET 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
Thirteen different companies have approved RET-targeting drugs, indicating a fragmented market.
The presence of many players suggests relatively low barriers to entry in the RET-targeting space.
| Drug | Company | Approved | Indications |
|---|---|---|---|
| RETEVMO | Eli Lilly | 2020 | 4 |
| STIVARGA | Bayer | 2012 | 3 |
| SORAFENIB TOSYLATE | YABAO PHARM | 2020 | 3 |
| SUNITINIB MALATE | Dr. Reddy's | 2021 | 3 |
| NEXAVAR | Bayer | 2005 | 3 |
| GAVRETO | RIGEL PHARMS | 2020 | 2 |
| ICLUSIG | Takeda | 2012 | 2 |
| RESNIBEN | AZURITY | - | 1 |
| ALECENSA | Roche | 2015 | 1 |
| COMETRIQ | EXELIXIS | 2012 | 1 |
| CAPRELSA | Sanofi | 2011 | 1 |
Drug Modality Landscape
Modalities
Routes of Administration
RET is amenable to small molecule drugs, with oral options available for convenient dosing.
Exploring alternative modalities like antibodies or PROTACs could provide a competitive advantage.
Clinical Trials 1,611 trials
Completion by Phase
| Phase | Total | Completed | Failed | Active | Completion |
|---|---|---|---|---|---|
| Phase 1 | 479 | 295 | 80 | 102 | 79% |
| Phase 2 | 861 | 360 | 168 | 326 | 68% |
| Phase 3 | 230 | 122 | 30 | 78 | 80% |
| Phase 4 | 41 | 24 | 4 | 13 | 86% |
Top Sponsors
By Modality
Top Conditions
Phase 3 Readout Calendar Pro
8 Phase 3 trials testing approved RET drugs across all sponsors.
Coverage: trials whose intervention is an approved drug targeting RET. 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 (2005 - 2021)
The first RET-targeting drug was approved in 2005, with the most recent approval in 2021.
The approval timeline indicates a sustained interest in RET as a drug target over the past 17 years.
Pro Intelligence Preview
Deep insights for drug target analysis
Competitive Landscape
- • 13 companies competing
- • Market share by company
Full Drug Portfolio
- • All 14 approved drugs
- • Approval dates & indications
Genetic Validation
- • Full genetic evidence table
- • Effect sizes & directions
Approval Timeline
- • Full 14-drug timeline
- • First-of-modality markers
Clinical Trials Analysis
- • Competition: High (15 sponsors)
- • 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 979 clinical trials targeting RET.
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