c-KIT Inhibitors
7 drugsAbout c-KIT
c-KIT, a receptor tyrosine kinase, is crucial for cell survival, proliferation, and differentiation. As a cell surface receptor, it initiates intracellular signaling upon binding stem cell factor (SCF). Aberrant c-KIT activation, often via mutations, is implicated in oncology and other diseases.
Human genetic studies strongly support c-KIT as a therapeutic target (max score 0.92), with variants linked to cutaneous mastocytosis, piebaldism and gastrointestinal stromal tumor. Loss-of-function variants are associated with increased risk for cutaneous mastocytosis and piebaldism, while protective for gastrointestinal stromal tumor, suggesting multiple therapeutic strategies.
c-KIT is targeted by 7 FDA-approved small molecule drugs, including IMKELDI, DASATINIB and PHYRAGO, across oncology and other therapeutic areas. Approvals span from SPRYCEL in 2006 to DANZITEN in 2024, with multiple companies developing c-KIT inhibitors.
Strategic Insights
ℹ️ How we calculate- White space opportunity in Multiple Myeloma with only 3 trials.
- phase1 represents biological uncertainty with 58% completion.
c-KIT Genetic Evidence Strong
Strong genetic evidence supports c-KIT's role in multiple diseases, with a maximum score of 0.92.
The strong genetic support may increase the probability of clinical trial success for c-KIT targeted therapies.
💡 Why activation?
- • Loss-of-function variants increase disease risk (OR > 1) — restoring function may help
- • 67% directional consistency across 3 traits
- • Strong signal in hematologic disease, immune system disease, integumentary system disease pathways
Cross-Disease Effects
Trade-off: ModerateDirection of Effect
67% alignedEvidence Across Diseases
18 totalGWAS and other genetic studies link KIT to 18 diseases.
Loss-of-function causes disease; activation may help
Loss-of-function causes disease; activation may help
🔗 Colocalization Evidence 20 strong
max H4: 1.00eQTL/pQTL signals for KIT 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 c-KIT Drugs
Seven companies have approved c-KIT targeting drugs, including Apotex, Novartis and SHORLA ONCOLOGY.
The presence of multiple players suggests a moderately competitive landscape with potential for strategic partnerships.
| Drug | Company | Approved | Indications |
|---|---|---|---|
| PHYRAGO | HANDA THERAP | 2023 | 2 |
| DANZITEN | AZURITY | 2024 | 1 |
| TASIGNA | Novartis | 2007 | 1 |
| FOTIVDA | AVEO PHARMS | 2021 | 1 |
c-KIT Drug Modality Landscape
Modalities
Routes of Administration
c-KIT 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.
c-KIT Clinical Trials 468 trials
Completion by Phase
| Phase | Total | Completed | Failed | Active | Completion |
|---|---|---|---|---|---|
| Phase 1 | 154 | 87 | 44 | 23 | 66% |
| Phase 2 | 227 | 114 | 55 | 57 | 67% |
| Phase 3 | 63 | 32 | 15 | 16 | 68% |
| Phase 4 | 24 | 16 | 3 | 5 | 84% |
Top Sponsors
By Modality
Top Conditions
c-KIT Drug Approval Timeline (2006 - 2024)
c-KIT drug approvals span 19 years, from 2006 to 2024, indicating sustained interest.
The recent approval of DANZITEN suggests continued opportunity for novel c-KIT inhibitors despite existing therapies.
Pro Intelligence Preview
Deep insights for drug target analysis
Competitive Landscape
- • 7 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: 10 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 221 clinical trials targeting c-KIT.
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