ABL Inhibitors
1 drugsStrategic Insights
ℹ️ How we calculate- White space opportunity in Accelerated Phase Chronic Myelogenous Leukemia, BCR-ABL1 Positive with only 4 trials.
ABL Genetic Evidence Strong
💡 Why inhibition?
- • Loss-of-function variants reduce disease risk (OR < 1)
- • 100% directional consistency across 1 traits
- • Strong signal in musculoskeletal or connective tissue disease, genetic, familial or congenital disease, hematologic disease pathways
Cross-Disease Effects
Trade-off: LowDirection of Effect
100% alignedEvidence Across Diseases
9 totalGWAS and other genetic studies link ABL1 to 9 diseases.
🔗 Colocalization Evidence 20 strong
max H4: 1.00eQTL/pQTL signals for ABL1 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 ABL Drugs
ABL Drug Modality Landscape
Modalities
Routes of Administration
ABL is amenable to small molecule drugs, with oral options available for convenient dosing.
ABL Clinical Trials 262 trials
Completion by Phase
| Phase | Total | Completed | Failed | Active | Completion |
|---|---|---|---|---|---|
| Phase 1 | 70 | 41 | 13 | 15 | 76% |
| Phase 2 | 158 | 57 | 31 | 69 | 65% |
| Phase 3 | 30 | 13 | 7 | 10 | 65% |
| Phase 4 | 4 | 3 | 1 | 0 | 75% |
Top Sponsors
By Modality
Top Conditions
Phase 3 Readout Calendar Pro
4 Phase 3 trials testing approved ABL drugs across all sponsors.
Coverage: trials whose intervention is an approved drug targeting ABL. Pre-approval candidates with development codes (e.g. AZD0901, MK-7240) are not yet linked. Anchored on CT.gov primary completion date.
ABL Drug Approval Timeline (2012 - 2012)
Pro Intelligence Preview
Deep insights for drug target analysis
Competitive Landscape
- • 1 companies competing
- • Market share by company
Full Drug Portfolio
- • All 1 approved drugs
- • Approval dates & indications
Genetic Validation
- • Full genetic evidence table
- • Effect sizes & directions
Approval Timeline
- • Full 1-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 246 clinical trials targeting ABL.
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