PCSK9 Inhibitors
4 drugsAbout PCSK9
PCSK9 is a protein convertase that regulates LDL receptor levels, influencing cholesterol homeostasis. By binding to the LDL receptor, PCSK9 promotes its degradation, leading to higher circulating LDL cholesterol.
PCSK9 is a validated drug target with strong genetic support (max score 0.94) from 41 diseases. Loss-of-function variants in PCSK9 protect against hypercholesterolemia, coronary artery disease, and metabolic disease, supporting inhibition as a therapeutic strategy.
Four PCSK9-targeting drugs are FDA-approved, including PRALUENT, REPATHA, LEQVIO, and LEROCHOL. These include antibody (PRALUENT, REPATHA), siRNA (LEQVIO), and other biologic modalities, addressing metabolic and other therapeutic areas.
Strategic Insights
ℹ️ How we calculate- White space opportunity in Pharmacokinetics with only 3 trials.
Human Genetic Evidence Strong
PCSK9 has strong genetic support with a max score of 0.94 across 41 diseases.
The strong genetic support suggests a higher probability of clinical success for PCSK9-targeting therapies.
💡 Why inhibition?
- • Loss-of-function variants reduce disease risk (OR < 1)
- • 100% directional consistency across 3 traits
- • Strong signal in phenotype, cardiovascular disease, nutritional or metabolic disease pathways
- • 2/2 diseases show protective effect sizes
Cross-Disease Effects
Trade-off: LowDirection of Effect
100% alignedEvidence Across Diseases
20 totalGWAS and other genetic studies link PCSK9 to 41 diseases.
Inhibiting this target may be therapeutic
Inhibiting this target may be therapeutic
Effect Sizes
Genetic effect on disease risk. OR<1 or β<0 = loss-of-function is protective (inhibiting target may help).
🔗 Colocalization Evidence 20 strong
max H4: 1.00eQTL/pQTL signals for PCSK9 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
Four companies have approved PCSK9-targeting drugs, including Regeneron, Amgen, Novartis and LIB THERAPEUTICS, INC.
The presence of multiple players indicates a competitive market, requiring differentiation for new entrants.
| Drug | Company | Approved | Indications |
|---|---|---|---|
| LEROCHOL | LIB THERAPEUTICS, INC. | 2025 | 2 |
Drug Modality Landscape
Modalities
Routes of Administration
PCSK9 is exclusively targeted by antibodies, suggesting it may be a cell-surface or secreted protein.
The presence of siRNA modalities suggests an opportunity for novel delivery methods or combination therapies.
📈 Modality Evolution
Antibodies pioneered PCSK9 targeting (2015), with other biologics entering more recently (2025).
Clinical Trials 227 trials
Completion by Phase
| Phase | Total | Completed | Failed | Active | Completion |
|---|---|---|---|---|---|
| Phase 1 | 34 | 27 | 0 | 7 | 100% |
| Phase 2 | 42 | 32 | 3 | 6 | 91% |
| Phase 3 | 100 | 82 | 2 | 15 | 98% |
| Phase 4 | 51 | 22 | 12 | 17 | 65% |
Top Sponsors
By Modality
Top Conditions
Phase 3 Readout Calendar Pro
1 Phase 3 trial testing approved PCSK9 drugs across all sponsors.
Coverage: trials whose intervention is an approved drug targeting PCSK9. 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 (2015 - 2025)
The first PCSK9 inhibitor was approved in 2015, with the most recent approval in 2025.
The recent approval suggests continued interest and potential for further innovation in PCSK9-targeting therapies.
Pro Intelligence Preview
Deep insights for drug target analysis
Competitive Landscape
- • 4 companies competing
- • Market share by company
Full Drug Portfolio
- • All 4 approved drugs
- • Approval dates & indications
Genetic Validation
- • Full genetic evidence table
- • Effect sizes & directions
Approval Timeline
- • Full 4-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 155 clinical trials targeting PCSK9.
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