SYNAPSE

Disease Landscape Assessment

Map an indication from a single query. Synapse aggregates validated targets, the competitive treatment landscape, clinical trial activity, biomarker coverage, genetic basis, and unmet need into a structured landscape report. Enter a disease name and get a scored, source-attributed view of the entire indication.

What You Get

Deliverables

Validated target list

All validated targets for the indication, ranked by evidence strength with mechanism-of-action annotations. Each target entry includes its disease association score, the sources supporting it, and whether the evidence comes from clinical, preclinical, or genetic data. For the GLP1R landscape, 286 disease associations were scored, with hypertension and social isolation reaching the maximum score of 1.00.

Weight LossHeart FailureType 2 DiabetesObesityCoronary Artery DiseasePrediabetesInflammationHypertension00.20.40.60.810.810.810.810.810.810.900.901.00

Treatment landscape

Drugs grouped by treatment line and development phase, cross-referenced against trial data. The landscape covers 317 clinical trials across Phase 1-4, with status breakdowns showing which are recruiting, active, or completed. Drug-indication relationships are mapped so you can see exactly which compounds target which conditions and how far along they are.

020406080100Phase 1Phase 2Phase 3Phase 4CompletedActiveRecruiting

Unmet need assessment

An integrated score combining epidemiology data, treatment gaps, and genetic underpinnings. This identifies indications where existing treatments are insufficient and where the target biology suggests a viable intervention. The assessment highlights whitespace opportunities: conditions with strong biological rationale but thin clinical development.

AlbiglutideLixisenatideLiraglutideDulaglutideTirzepatideSemaglutideExenatide0510152025308122621182429
DECISION ENABLED

Evaluate indication attractiveness and identify whitespace opportunities. Indications with high unmet need, strong target-disease associations, and limited competition represent the best strategic opportunities.

Sample Output

GLP1R disease landscape: associations, trials, and competitive field

GLP1R: Disease Associations (Top 12 of 286)scored by evidence
Ovarian NeoplasmsBipolar DisorderMajor Depressive DisorderMetabolic SyndromeWeight LossHeart FailureType 2 DiabetesObesityCoronary Artery DiseasePrediabetesInflammationHypertension00.20.40.60.810.800.800.800.810.810.810.810.810.810.900.901.00
Clinical evidence Preclinical only
Clinical Trial Distribution: 317 TrialsPhase 1–4
Trials020406080100Phase 1Phase 2Phase 3Phase 4CompletedActiveRecruiting
Drug Interaction Landscape309 interactions
DrugScorePapers
Exenatide1.0029
Semaglutide0.9524
Tirzepatide0.9218
Dulaglutide0.9021
Liraglutide0.8826
Lixisenatide0.7512
Albiglutide0.708

CROSS-THERAPEUTIC-AREA DISEASE COMPARISON

EGFR (Oncology) + IL13 (Allergy): Disease Associations2 additional targets
Colorectal CancerGlioblastomaNSCLCAtopic DermatitisNasal PolypsAllergic DiseaseAtopic Asthma00.20.40.60.810.700.700.770.700.720.811.00
EGFR (oncology) IL13 (allergy)
Therapeutic Area Comparison3 landscapes
TargetAreaTop DiseaseScoreDiseasesTrials
GLP1RMetabolicHypertension1.00286317
EGFROncologyNSCLC0.771482,293
IL13Allergy/InflammationAtopic Asthma1.0014373
How It Works

Methodology

STEP 1

Map validated targets from literature and registries

Synapse aggregates target-disease associations from literature, trial registries, and genetic databases. Each association is scored by evidence strength, replication, and directional consistency.

STEP 2

Score targets by evidence strength

Targets are ranked using a composite score that weights source quality, replication count, and evidence type (genetic, clinical, preclinical). Mechanism-of-action annotations provide biological context.

STEP 3

Build treatment landscape

Drugs are grouped by treatment line and mapped across development phases. Trial data from ClinicalTrials.gov provides enrollment, status, sponsor, and primary endpoint information for each entry.

STEP 4

Compute unmet need score

Epidemiology data, treatment gaps, and genetic underpinnings are integrated into a composite unmet need metric. High scores indicate conditions where current treatments are insufficient despite biological rationale.

STEP 5

Identify whitespace opportunities

The platform highlights indications where evidence is strong but clinical development is sparse, representing strategic opportunities for entry. Conversely, it flags crowded areas where differentiation will be challenging.

Who This Is For

Target personas

Indication strategist

Assess the competitive and scientific landscape for any indication to inform portfolio decisions.

Market access analyst

Understand the treatment landscape, unmet need, and competitive dynamics before market entry planning.

Portfolio lead

Compare indications by evidence strength, competitive density, and strategic fit to allocate development resources.