DPP-4 Inhibitors
19 drugsAbout DPP-4
Dipeptidyl Peptidase-4 (DPP-4) is an enzyme that inactivates incretin hormones, which regulate blood glucose. Inhibiting DPP-4 prolongs incretin action, improving glucose control. This makes DPP-4 a clinically validated target for type 2 diabetes.
Human genetic studies provide strong support for DPP4 as a therapeutic target (max score 0.77). Variants are linked to intelligence (0.77) and smoking initiation (0.74). Strong eQTL/pQTL signals further support the link between DPP4 and disease.
DPP-4 is targeted by 16 FDA-approved small molecule drugs, including NESINA, JENTADUETO and GLYXAMBI. These drugs primarily address metabolic conditions, though some are being explored in other therapeutic areas.
DPP-4 Genetic Evidence Strong
DPP4 has strong genetic support with a max score of 0.77 linked to intelligence.
The strong genetic support suggests a higher probability of clinical success for DPP4-targeting drugs.
Evidence Across Diseases
20 totalGWAS and other genetic studies link DPP4 to 23 diseases.
🔗 Colocalization Evidence 20 strong
max H4: 1.00eQTL/pQTL signals for DPP4 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 DPP-4 Drugs
Six companies have approved DPP-4 drugs, including Takeda, Boehringer Ingelheim and Dr. Reddy's.
The presence of multiple established players suggests a moderately competitive market with potential entry barriers.
| Drug | Company | Approved | Indications |
|---|---|---|---|
| LINAGLIPTIN AND METFORMIN HYDROCHLORIDE | Dr. Reddy's | 2021 | 1 |
| JENTADUETO XR | Boehringer Ingelheim | 2016 | 1 |
| KAZANO | Takeda | 2013 | 1 |
| JANUMET XR | Merck | 2012 | 1 |
| ZITUVIO | ZYDUS LIFESCIENCES | 2023 | 1 |
| TRIJARDY XR | Boehringer Ingelheim | 2020 | 1 |
| TRADJENTA | Boehringer Ingelheim | 2011 | 1 |
| ZITUVIMET | ZYDUS LIFESCIENCES | 2023 | 1 |
| STEGLUJAN | Merck | 2017 | 1 |
| NESINA | Takeda | 2013 | 1 |
| JENTADUETO | Boehringer Ingelheim | 2012 | 1 |
| JANUVIA | Merck | 2006 | 1 |
| JANUMET | Merck | 2007 | 1 |
| SITAGLIPTIN PHOSPHATE | Novartis | 2025 | - |
| SAXAGLIPTIN | Aurobindo Pharma | 2023 | - |
| DAPAGLIFLOZIN AND SAXAGLIPTIN HYDROCHLORIDE | MSN | 2026 | - |
DPP-4 Drug Modality Landscape
Modalities
Routes of Administration
DPP-4 is amenable to small molecule drugs, with oral options available for convenient dosing.
Exploring alternative modalities like antibodies or peptides could provide a competitive advantage.
DPP-4 Clinical Trials 1,541 trials
Completion by Phase
| Phase | Total | Completed | Failed | Active | Completion |
|---|---|---|---|---|---|
| Phase 1 | 365 | 300 | 23 | 41 | 93% |
| Phase 2 | 376 | 211 | 74 | 89 | 74% |
| Phase 3 | 376 | 286 | 38 | 48 | 88% |
| Phase 4 | 424 | 296 | 53 | 72 | 85% |
Top Sponsors
By Modality
Top Conditions
Top Drugs
Phase 3 Readout Calendar Pro
7 Phase 3 trials testing approved DPP-4 drugs across all sponsors.
Coverage: trials whose intervention is an approved drug targeting DPP-4. Pre-approval candidates with development codes (e.g. AZD0901, MK-7240) are not yet linked. Anchored on CT.gov primary completion date.
DPP-4 Drug Approval Timeline (2006 - 2025)
The first DPP-4 inhibitor, JANUVIA, was approved in 2006, with the most recent, BRYNOVIN, in 2025.
The continued approval of DPP-4 inhibitors indicates sustained interest and potential for further market growth.
Pro Intelligence Preview
Deep insights for drug target analysis
Competitive Landscape
- • 10 companies competing
- • Market share by company
Full Drug Portfolio
- • All 19 approved drugs
- • Approval dates & indications
Genetic Validation
- • Full genetic evidence table
- • Effect sizes & directions
Approval Timeline
- • Full 19-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 899 clinical trials targeting DPP-4.
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