Dopa-decarboxylase Inhibitors
2 drugsAbout Dopa-decarboxylase
Dopa-decarboxylase (AADC) is an enzyme that catalyzes the synthesis of key neurotransmitters like dopamine and serotonin in the CNS. It decarboxylates L-DOPA to dopamine and 5-hydroxytryptophan to serotonin, playing a crucial role in neurotransmitter production.
Dopa-decarboxylase is a drug target for CNS disorders, evidenced by six FDA-approved drugs. However, there is currently no genetic evidence directly linking dopa-decarboxylase variations to specific diseases.
Six FDA-approved small molecule drugs target dopa-decarboxylase, including NORTHERA, DROXIDOPA, CREXONT, RYTARY, DUOPA and VYALEV. These drugs, developed by companies like LUNDBECK, Aurobindo Pharma, IMPAX and AbbVie, are all indicated for CNS disorders.
Strategic Insights
ℹ️ How we calculate- White space opportunity in Autonomic Failure with only 1 trials.
Human Genetic Evidence Strong
There is no genetic evidence data available for dopa-decarboxylase.
Lack of genetic validation may increase the risk of clinical trial failure; consider prioritizing targets with stronger genetic support.
💡 Why activation?
- • Loss-of-function variants increase disease risk (OR > 1) — restoring function may help
- • 100% directional consistency across 2 traits
- • Strong signal in genetic, familial or congenital disease, nutritional or metabolic disease pathways
Cross-Disease Effects
Trade-off: LowDirection of Effect
100% alignedEvidence Across Diseases
20 totalGWAS and other genetic studies link DDC to 23 diseases.
Loss-of-function causes disease; activation may help
🔗 Colocalization Evidence 20 strong
max H4: 1.00eQTL/pQTL signals for DDC 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 drugs targeting dopa-decarboxylase, with LUNDBECK, Aurobindo Pharma, IMPAX, and AbbVie leading the market.
The market is moderately concentrated, suggesting potential entry barriers for new competitors.
Drug Modality Landscape
Modalities
Routes of Administration
Only one approved drug targets Dopa-decarboxylase, using small molecule modality.
Exploring alternative modalities like antibodies or gene therapies could provide a competitive advantage.
Clinical Trials 44 trials
Completion by Phase
| Phase | Total | Completed | Failed | Active | Completion |
|---|---|---|---|---|---|
| Phase 1 | 17 | 11 | 3 | 3 | 79% |
| Phase 2 | 10 | 4 | 4 | 1 | 50% |
| Phase 3 | 8 | 6 | 2 | 0 | 75% |
| Phase 4 | 9 | 7 | 2 | 0 | 78% |
Top Sponsors
By Modality
Top Conditions
Top Drugs
Drug Approval Timeline (2014 - 2014)
The first drug was approved in 2014 (NORTHERA), and the most recent was in 2024 (VYALEV), spanning 11 years.
The recent approval suggests continued interest, but monitor for market saturation.
Pro Intelligence Preview
Deep insights for drug target analysis
Competitive Landscape
- • 2 companies competing
- • Market share by company
Full Drug Portfolio
- • All 2 approved drugs
- • Approval dates & indications
Genetic Validation
- • Full genetic evidence table
- • Effect sizes & directions
Approval Timeline
- • Full 2-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 19 clinical trials targeting Dopa-decarboxylase.
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