Garden has launched BLOOM (Branching Lookup Optimized for Organic Molecules), a Markush structure search engine designed to give AI drug-design teams near-instant verification of small-molecule IP landscapes. This enables researchers to iterate on candidates with legal certainty integrated directly into the discovery process. As AI models generate molecules faster than ever, BLOOM eliminates the bottleneck of verifying what’s already covered before investing lab time and resources.

BLOOM leverages a graph-based, agentic traversal to compare Markush queries against millions of SMILES strings, filtering out invalid candidates based on local atom and bond features. It then provides color-coded mapping that confirms atom- and bond-level compliance, transforming verification from a manual burden into a streamlined, automated step.

In benchmark testing, BLOOM demonstrated an average 32.44× speed improvement over traditional core-extraction string search methods (0.047 ms vs. 1.491 ms per comparison). It also identified correct matches that string-based approaches missed, including a single-hit query across a multi-million-record corpus. This allows IP-aware go/no-go decisions to happen during the ideation phase, rather than weeks later.

BLOOM reduces false positives that often occur with legacy search methods, which frequently misinterpret nuanced bond counts and structural positioning. By automating and scaling IP verification, research teams avoid tedious, atom-by-atom validation.

The engine is fully integrated with Garden’s patent database: every SMILES match links directly to underlying patent records, while Garden’s AI agent can summarize, compare, and refine result sets. BLOOM supports workflows ranging from rapid novelty triage to in-depth freedom-to-operate analysis, seamlessly aligned with model-driven molecular design.

“AI can propose thousands of viable chemistries in minutes. BLOOM closes the loop by telling you what’s already fenced off instantly,” said Adi Sidapara, Founder and CEO of Garden. “You get IP-aware exploration without slowing down discovery.”

“Small changes around an R-group can define patentability,” added Kavin Sivakumar, Ph.D., Founding ML Researcher at Garden. “BLOOM’s graph reasoning captures those subtleties at speed, so IP checks no longer throttle design.”

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