Trusted by Multiple Top-20 Global Pharmaceuticals and Pioneering Biotechs.
Why Sable?
Safety-First Intelligence for Modern Discovery. Evaluating targets requires balancing efficacy, tractability, and safety. But speed in target selection is worthless if it leads to a faster wrong answer. Historically, teams cross-referenced these domains manually, frequently treating safety as a late-stage gatekeeper rather than an early decision tool. We built Sable to integrate rigorous, mechanism-aware safety profiling directly into the early discovery loop.
Expert-Driven Data Engineering
We built a curated data layer that harmonises 35+ sources into a unified target intelligence tool. Instead of wasting time cleaning messy public databases, your team gets instant, connected insights.
Before Sable
Using Sable
Siloed Evaluation: Time spent jumping between separate tools to evaluate safety, efficacy evidence, and other factors.
Unified Intelligence: A multi-dimensional view combining biological validation, clinical precedents, and mechanism-aware safety metrics in a single framework.
Manual Data Scavenging: High-value discovery teams wasting days manually extracting data from literature and unstructured databases or paid tools that only answer part of the question.
Automatic Synthesis: Data is aggregated, harmonised, and ready for you to analyse.
Delayed Reporting: Weeks spent translating raw findings into a structured, decision-ready safety assessment.
Instant Information: Structured, referenced safety assessments generated directly from harmonised data, ready to act on.
Isolated Assessments: Individual reviewers working in disconnected documents, with expert edits and feedback lost or overwritten.
Collaborative Auditing: Comment, tag, and edit risks directly within a collaborative report, with a fully auditable trail of every change.
Static Decision Making: Target profiles are frozen in static slide decks that become obsolete as new data is published.
Living Knowledge Base: A dynamic workspace that actively flags new literature, filings, and clinical updates across your pipeline.
High-Risk Blindspots: Missing and contradictory evidence or hidden liabilities until late-stage optimisation.
Systematic De-risking: A standardised framework ensuring every candidate target is rigorously vetted against all criteria early.