Real programs. Real validation data.
Client identities are anonymized at their request, but every metric below is from a closed engagement with downstream wet-lab or clinical evidence confirmation.
- 80–90%
- Average cost reduction
- 3–6 mo
- Average time savings
- 87%
- Wet-lab prediction accuracy
- 100%
- On-time delivery rate
Five programs across discovery modalities
Select a case study to read the full engagement timeline, ranked deliverables, validation outcomes, and lessons learned.
AI-Accelerated Drug Discovery for SARS-CoV-2 Protease Inhibitors
Mid-stage biotech hit identification for a novel coronavirus protease inhibitor program.
- 20×
- Faster than traditional HTS
- 87.5%
- Cost savings vs. HTS
Next-Generation EGFR Inhibitors for T790M-Resistant Non-Small Cell Lung Cancer
Clinical-stage oncology team needed novel inhibitors active against gatekeeper-mutant EGFR after an $1.8M HTS campaign stalled.
- 3.5×
- Faster than prior HTS campaign
- 90%
- Cost savings vs. prior campaign
Codon-Optimized CRISPR Guide Design for Liver-Targeted Gene Therapy
Series A gene therapy startup needed high-specificity guide RNAs for a liver-targeted therapeutic with no in-house computational team.
- 10 days
- End-to-end delivery
- 95%+
- On-target specificity (top 5)
Neutralizing Antibody Discovery Against RSV F-Protein Prefusion State
Vaccine biotech needed developable neutralizing antibodies against respiratory syncytial virus for a passive immunization program.
- 4 wks
- Computational delivery
- 340×
- Larger search vs. phage display
Multi-Omics Target Discovery for Rheumatoid Arthritis
Pharma discovery group needed a ranked, validated target list to prioritize a new autoimmune portfolio before Q4 gate review.
- 3 wks
- Computational delivery
- 847
- Targets evaluated
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