Si-gul scans genomic, clinical, and literature data to rank drug targets by validated confidence scores — so your team knows where to commit before the first assay.
Scope the disease area and biological question. Si-gul builds the search space around your therapeutic hypothesis.
Genomic, clinical, and literature evidence is synthesised across Open Targets, UniProt, ClinVar, ClinicalTrials.gov, and PubMed.
Receive a structured PDF report with confidence scores, LLM-generated narrative, and actionable next steps — ready for your team or investors.
Every drug target is scored across genetic association, clinical evidence, druggability, safety signal, and literature strength — giving you a composite confidence score you can defend in an investor meeting.
Beyond raw scores, Si-gul generates plain-language summaries of the evidence for each target — translating database outputs into science your BD team can read and act on.
Every analysis produces a branded, investor-ready PDF with ranked targets, score breakdowns, data provenance, and recommended next steps. No data wrangling required.
No enterprise contract, no six-month onboarding. Submit your indication, get your report. Designed for lean R&D teams who need answers in days, not quarters.
Pre-Series A teams who need to shortlist targets for their first IND without a full computational biology team on payroll.
Principal investigators translating basic research into commercial drug discovery who need structured evidence synthesis fast.
Contract research organisations that need rapid target shortlisting as a deliverable for their own biotech clients.
We're onboarding a small cohort of early-stage biotech teams. Drop your email and we'll reach out.
Thanks! We'll be in touch within 48 hours.