PARP-1 Inhibitors
3 drugsAbout PARP-1
PARP-1, or poly (ADP-ribose) polymerase 1, is an enzyme crucial for DNA repair, genomic stability, and programmed cell death. It plays a key role in repairing DNA damage, maintaining genomic integrity, and regulating cell death pathways.
Human genetic studies provide strong validation for PARP-1 as a therapeutic target, with variants linked to clonal hematopoiesis (score 0.78) and cutaneous melanoma (score 0.77). Strong eQTL/pQTL signals further support its role in disease.
PARP-1 is targeted by 3 FDA-approved small molecule drugs, including ZEJULA, AKEEGA, and RUBRACA, all in oncology. GSK, Johnson & Johnson, and PHARMAAND are the key players in this space.
Strategic Insights
ℹ️ How we calculate- phase1 represents biological uncertainty with 58% completion.
Human Genetic Evidence Strong
Genetic evidence strongly supports PARP-1's role in diseases like clonal hematopoiesis and cutaneous melanoma.
Strong genetic support suggests that clinical trials targeting these genetically validated indications have a higher likelihood of success.
Evidence Across Diseases
10 totalGWAS and other genetic studies link PARP1 to 10 diseases.
🔗 Colocalization Evidence 20 strong
max H4: 1.00eQTL/pQTL signals for PARP1 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
The competitive landscape includes GSK, Johnson & Johnson, and PHARMAAND, each with an approved drug.
The presence of three companies indicates moderate market concentration, suggesting potential for new entrants with differentiated therapies.
Drug Modality Landscape
Modalities
Routes of Administration
PARP-1 is amenable to small molecule drugs, with oral options available for convenient dosing.
The exclusive use of small molecules suggests a potential opportunity for developing alternative modalities like antibodies or PROTACs.
Clinical Trials 442 trials
Completion by Phase
| Phase | Total | Completed | Failed | Active | Completion |
|---|---|---|---|---|---|
| Phase 1 | 146 | 73 | 34 | 39 | 68% |
| Phase 2 | 223 | 95 | 46 | 81 | 67% |
| Phase 3 | 59 | 21 | 3 | 35 | 88% |
| Phase 4 | 14 | 7 | 1 | 6 | 88% |
Top Sponsors
By Modality
Top Conditions
Phase 3 Readout Calendar Pro
4 Phase 3 trials testing approved PARP-1 drugs across all sponsors.
Coverage: trials whose intervention is an approved drug targeting PARP-1. 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 (2016 - 2023)
The approval timeline spans 8 years, from RUBRACA (2016) to AKEEGA (2023).
The recent approval of AKEEGA suggests continued interest and potential for further development in PARP-1 inhibition.
Pro Intelligence Preview
Deep insights for drug target analysis
Competitive Landscape
- • 3 companies competing
- • Market share by company
Full Drug Portfolio
- • All 3 approved drugs
- • Approval dates & indications
Genetic Validation
- • Full genetic evidence table
- • Effect sizes & directions
Approval Timeline
- • Full 3-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 339 clinical trials targeting PARP-1.
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