Garden Launches BLOOM to Make AI Drug Design IP-Aware in Real Time
BLOOM uses a graph-based, agentic traversal to compare Markush queries against millions of SMILES strings, short-circuiting invalid candidates via local atom and bond features. The system then delivers color-coded mapping that confirms atom- and bond-level compliance, turning verification from a manual chore into a built-in step.
In benchmark testing, BLOOM delivered an average 32.44× speed improvement over a standard core-extraction string search (0.047 ms vs. 1.491 ms per comparison) while finding correct matches that string methods missed, including a designed single-hit query across a multi-million-record corpus. For IP-aware design loops, that means go/no-go decisions during ideation, not weeks later.
BLOOM also reduces false positives that plague legacy approaches, which often fail on nuanced bond counts and positioning, saving teams from time-consuming, atom-by-atom checks. With BLOOM, verification is automatic and scalable.
The engine is integrated with Garden's patent database: every SMILES match links to underlying patent records, and Garden's AI agent can summarize, compare, and help prune result sets. BLOOM supports workflows from rapid novelty triage to freedom-to-operate analysis directly alongside model-driven 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
Availability
To request access or a demo, contact [email protected].
About Garden
Garden builds patent intelligence tools that accelerate R&D and legal decision-making by pairing high-quality data with advanced search and verification.
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SOURCE Garden
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