Target Evaluation
Assemble an evidence-backed profile for any gene or protein target from a single query. Synapse aggregates data from PubMed, ChEMBL, Open Targets, ClinicalTrials.gov, FAERS, STRING, and 10+ additional databases to produce a scored dossier covering druggability, disease associations, clinical landscape, safety liabilities, and molecular interactions. No data upload required: just a gene name.
Deliverables
Complete target dossier
A structured evidence profile covering every dimension of target assessment: druggability, disease associations ranked by evidence score, clinical trial landscape, drug interactions, and molecular interaction network. For GLP1R, the dossier spans 251 papers, 1,301 evidence items, 317 clinical trials, and 309 drug interactions, assembled and scored automatically from the query 'GLP1R'. Every claim links back to its source.
Translational gap analysis
Evidence mapped across the translational chain: basic research, preclinical, and clinical stages. This reveals where the evidence is strong and where it thins out. For GLP1R, the chain is complete: 580 basic research items, 404 preclinical, and 317 clinical. For less-studied targets, this analysis shows exactly which translational stages need more evidence before advancement.
EVIDENCE ITEMS BY TRANSLATIONAL STAGE
Contradiction report
Literature doesn't always agree. The dossier flags findings where evidence conflicts and computes concordance scores. For GLP1R, two conflicts were detected: AP2M1 (concordance 0.42) and coronary artery disease (concordance 0.33). Each conflict is annotated with the disagreeing sources, species, and experimental context so you can evaluate whether it's a genuine red flag or an artifact of differing experimental conditions.
CONCORDANCE SCORE (lower = more conflict)
Dashed line = 0.5 threshold. Scores below indicate conflicting evidence.
Prioritize targets by evidence strength before committing validation resources. Targets with high-scoring indications, complete translational chains, and few contradictions are the strongest candidates.
GLP1R target evaluation dossier
Complete translational chain: evidence spans basic research through clinical stages with no gaps.
| Entity | Concordance | Type |
|---|---|---|
| AP2M1 | 0.42 | Molecular interaction |
| Coronary Artery Disease | 0.33 | Disease association |
| Pathway | Score |
|---|---|
| Insulin secretion | 0.70 |
| Hormone signaling | 0.70 |
| Neuroactive ligand-receptor | 0.70 |
| cAMP signaling | 0.70 |
MULTI-TARGET COMPARISON: GLP1R vs EGFR vs IL13
| Target | Area | Papers | Trials | Drugs | Modalities | Translational |
|---|---|---|---|---|---|---|
| GLP1R | Metabolic | 251 | 317 | 309 | SM | Complete |
| EGFR | Oncology | 161 | 2,293 | 221 | SM, Ab, PROTAC, Other | Complete (4 gaps) |
| IL13 | Allergy | 60 | 73 | 20 | Ab (preferred) | Clinical focus |
| Pathway | Score |
|---|---|
| PI3K-Akt signaling | 0.70 |
| MAPK signaling | 0.70 |
| ErbB signaling | 0.70 |
| Ras signaling | 0.70 |
| JAK-STAT signaling | 0.70 |
| EGFR TKI resistance | 0.70 |
Methodology
Query multi-source databases
Synapse queries PubMed, ChEMBL, Open Targets, ClinicalTrials.gov, FAERS, STRING, DGIdb, PharmGKB, and 10+ additional databases simultaneously. For GLP1R, this returned 251 papers and data from every major drug-target and disease-target knowledgebase.
Extract and normalize evidence claims
Evidence claims are extracted from each source with full attribution. Claims are normalized across databases, resolving identifier differences, standardizing indication names, and reconciling conflicting taxonomies into a unified evidence model.
Score by evidence strength
Indications, drug interactions, and molecular interactions are scored by evidence strength using source quality, replication count, and directional consistency. GLP1R's top indications (hypertension, social isolation) score 1.00, the maximum possible.
Build translational chain
Evidence is categorized into translational stages: in vitro, in vivo, and clinical. The chain visualization reveals whether the target has evidence at each stage or has gaps that could slow development.
Detect contradictions
Where literature disagrees, the system computes concordance scores and surfaces the conflicting findings side-by-side. Each contradiction is annotated by species, model system, and disease stage for informed assessment.
Target personas
Target assessment scientist
Get a comprehensive evidence profile for any target in minutes instead of weeks of manual literature review.
Drug discovery project lead
Assess target maturity and evidence strength to make informed go/no-go decisions on validation campaigns.
BD&L analyst
Evaluate in-licensing opportunities with a complete evidence landscape for any target of interest.
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