by Bajpai Labs · Target discovery
Ranked targets before chemistry in 2–4 weeks.
TargetIQ replaces months of internal bioinformatics with a multi-omics AI engine that delivers 8–15 druggable targets—with full evidence dossiers—before a single screen runs.
Delivery pipeline
- Multi-Omics Integration01GWAS · scRNA-seq · proteomics · knowledge-graph GNN scoring
- Druggability & Safety02Structural tractability · liability filters · competitive landscape
- Ranked Dossiers038–15 priority targets · evidence tables · portfolio gate deck
- 847+
- Targets evaluated per program
- 3–6×
- Faster than internal bioinformatics
- 2–4 wks
- Typical delivery
Most programs fail because the wrong target was chosen—not because chemistry was slow.
FTE bioinformatics teams spend months producing GWAS gene lists without druggability, safety, or competitive context.
Lengthy internal debates and incomplete evidence delay portfolio gates and push programs past funding milestones.
200+ GWAS hits without dossiers, pathway context, or gate-ready deliverables leave leadership unable to commit budget.
A multi-omics target discovery engine that ranks druggable targets before any chemistry begins.
- 01
Define your indication
Provide disease area, modality preference, proprietary cohorts, and any internal target lists to reconcile.
- 02
AI engine runs
Multi-omics integration, knowledge-graph GNNs, druggability scoring, and pathway analysis.
- 03
Ranked dossiers delivered
8–15 priority targets with evidence tables, competitive briefs, and portfolio gate presentation.
Built for decisions, not dashboards.
Every architectural choice in TargetIQ serves one goal: get your team to the right target decision before committing chemistry budget.
Most teams screen against the wrong target. TargetIQ optimizes for decision quality: surfacing the 8 to 15 targets worth investing in, not hundreds of GWAS hits.
Targets are ranked by concordance across genetic, expression, and pathway layers—not single-source lists that fail at portfolio gate.
Every priority target ships with a full evidence dossier, competitive brief, and validation plan your committee can act on immediately.
You work with the architects who built the pipeline, not a sales team relaying requirements to a black box.
The science behind target discovery.
Multi-omics integration, knowledge-graph neural networks, and druggability modeling from Bajpai Labs.
Graph neural networks over curated gene–pathway–disease networks propagate disease signals and surface targets missed by single-omics analysis.
GWAS, bulk and single-cell RNA-seq, proteomics, and eQTL colocalization fused into composite disease relevance scores.
Structural tractability, modality fit, known ligand classes, and AlphaFold pocket analysis for every ranked target.
Disease pathway reconstruction, bypass detection, and resistance subtype mapping for oncology and complex indications.
Essential-gene databases, knockout phenotypes, and tissue expression breadth remove high-liability targets pre-gate.
Clinical trial, patent, and approved-drug mapping per target—white-space analysis included in every dossier.
Methodology
Evidence Integration Loop
Each target scored by genetic, expression, pathway, and single-cell evidence—not single-source lists.
Committee outcomes and validation results refine scoring models for follow-on indication expansions.
Essential-gene and tissue liability filters remove unsafe targets before they reach your gate deck.
Research rigor. Commercial speed.
TargetIQ combines multi-omics bioinformatics, knowledge-graph AI, and portfolio gate experience that most point-tool vendors lack.
- Gate-ready deliverables
Evidence dossiers, competitive briefs, and decision frameworks—not gene lists in a spreadsheet.
- Multi-omics + GNN depth
Knowledge-graph neural networks surface targets missed by GWAS-only or expression-only analysis.
- Production accountability
Ranked targets with full technical documentation your committee can take straight into budget allocation.
- Direct line to leadership
You work with the architects who built the engine, not a sales team.
Target intelligence services
Four capabilities. One decision engine.
From multi-omics target discovery through resistance mapping and portfolio gate packages, each capability shares the same knowledge-graph infrastructure and senior team.
All services- 00
Multi-Omics Target Discovery
GWAS · scRNA · GNNStart hereCross-cohort meta-analysis, knowledge-graph GNN scoring, and genetic colocalization. Delivers ranked targets with full evidence dossiers before any chemistry begins.
Engagements typically $75K–$200K per programSee capabilities - 01
Druggability & Safety Assessment
Structure · liabilityStructural tractability, modality fit, essential-gene safety filters, and competitive landscape briefs per target.
Engagements typically $50K–$125K per programSee capabilities - 02
Resistance Pathway Mapping
Oncology · bypassResistance subtype clustering, pathway bypass detection, and combination target ranking with biomarker stratification panels.
Engagements typically $175K–$300K per programSee capabilities - 03
Portfolio Gate Decision Packages
Dossiers · gate deckGate-ready presentation decks, evidence tables, validation roadmaps, and budget allocation frameworks for investment committees.
Engagements typically $100K–$250K per programSee capabilities
by Bajpai Labs
Ready to gate the right targets?
30-minute intro call with the Bajpai Labs team. No pitch deck—just a scoping conversation on your indication and timeline.